Price Action Smart Money Concepts [BigBeluga]THE SMART MONEY CONCEPTS Toolkit
The Smart Money Concepts [ BigBeluga ] is a comprehensive toolkit built around the principles of "smart money" behavior, which refers to the actions and strategies of institutional investors.
The Smart Money Concepts Toolkit brings together a suite of advanced indicators that are all interconnected and built around a unified concept: understanding and trading like institutional investors, or "smart money." These indicators are not just randomly chosen tools; they are features of a single overarching framework, which is why having them all in one place creates such a powerful system.
This all-in-one toolkit provides the user with a unique experience by automating most of the basic and advanced concepts on the chart, saving them time and improving their trading ideas.
Real-time market structure analysis simplifies complex trends by pinpointing key support, resistance, and breakout levels.
Advanced order block analysis leverages detailed volume data to pinpoint high-demand zones, revealing internal market sentiment and predicting potential reversals. This analysis utilizes bid/ask zones to provide supply/demand insights, empowering informed trading decisions.
Imbalance Concepts (FVG and Breakers) allows traders to identify potential market weaknesses and areas where price might be attracted to fill the gap, creating opportunities for entry and exit.
Swing failure patterns help traders identify potential entry points and rejection zones based on price swings.
Liquidity Concepts, our advanced liquidity algorithm, pinpoints high-impact events, allowing you to predict market shifts, strong price reactions, and potential stop-loss hunting zones. This gives traders an edge to make informed trading decisions based on liquidity dynamics.
🔵 FEATURES
The indicator has quite a lot of features that are provided below:
Swing market structure
Internal market structure
Mapping structure
Adjustable market structure
Strong/Weak H&L
Sweep
Volumetric Order block / Breakers
Fair Value Gaps / Breakers (multi-timeframe)
Swing Failure Patterns (multi-timeframe)
Deviation area
Equal H&L
Liquidity Prints
Buyside & Sellside
Sweep Area
Highs and Lows (multi-timeframe)
🔵 BASIC DEMONSTRATION OF ALL FEATURES
1. MARKET STRUCTURE
The preceding image illustrates the market structure functionality within the Smart Money Concepts indicator.
➤ Solid lines: These represent the core indicator's internal structure, forming the foundation for most other components. They visually depict the overall market direction and identify major reversal points marked by significant price movements (denoted as 'x').
➤ Internal Structure: These represent an alternative internal structure with the potential to drive more rapid market shifts. This is particularly relevant when a significant gap exists in the established swing structure, specifically between the Break of Structure (BOS) and the most recent Change of High/Low (CHoCH). Identifying these formations can offer opportunities for quicker entries and potential short-term reversals.
➤ Sweeps (x): These signify potential turning points in the market where liquidity is removed from the structure. This suggests a possible trend reversal and presents crucial entry opportunities. Sweeps are identified within both swing and internal structures, providing valuable insights for informed trading decisions.
➤ Mapping structure: A tool that automatically identifies and connects significant price highs and lows, creating a zig-zag pattern. It visualizes market structure, highlights trends, support/resistance levels, and potential breakouts. Helps traders quickly grasp price action patterns and make informed decisions.
➤ Color-coded candles based on market structure: These colors visually represent the underlying market structure, making it easier for traders to quickly identify trends.
➤ Extreme H&L: It visualizes market structure with extreme high and lows, which gives perspective for macro Market Structure.
2. VOLUMETRIC ORDER BLOCKS
Order blocks are specific areas on a financial chart where significant buying or selling activity has occurred. These are not just simple zones; they contain valuable information about market dynamics. Within each of these order blocks, volume bars represent the actual buying and selling activity that took place. These volume bars offer deeper insights into the strength of the order block by showing how much buying or selling power is concentrated in that specific zone.
Additionally, these order blocks can be transformed into Breaker Blocks. When an order block fails—meaning the price breaks through this zone without reversing—it becomes a breaker block. Breaker blocks are particularly useful for trading breakouts, as they signal that the market has shifted beyond a previously established zone, offering opportunities for traders to enter in the direction of the breakout.
Here's a breakdown:
➤ Bear Order Blocks (Red): These are zones where a lot of selling happened. Traders see these areas as places where sellers were strong, pushing the price down. When the price returns to these zones, it might face resistance and drop again.
➤ Bull Order Blocks (Green): These are zones where a lot of buying happened. Traders see these areas as places where buyers were strong, pushing the price up. When the price returns to these zones, it might find support and rise again.
These Order Blocks help traders identify potential areas for entering or exiting trades based on past market activity. The volume bars inside blocks show the amount of trading activity that occurred in these blocks, giving an idea of the strength of buying or selling pressure.
➤ Breaker Block: When an order block fails, meaning the price breaks through this zone without reversing, it becomes a breaker block. This indicates a significant shift in market liquidity and structure.
➤ A bearish breaker block occurs after a bullish order block fails. This typically happens when there's an upward trend, and a certain level that was expected to support the market's rise instead gives way, leading to a sharp decline. This decline indicates that sellers have overcome the buyers, absorbing liquidity and shifting the sentiment from bullish to bearish.
Conversely, a bullish breaker block is formed from the failure of a bearish order block. In a downtrend, when a level that was expected to act as resistance is breached, and the price shoots up, it signifies that buyers have taken control, overpowering the sellers.
3. FAIR VALUE GAPS:
A fair value gap (FVG), also referred to as an imbalance, is an essential concept in Smart Money trading. It highlights the supply and demand dynamics. This gap arises when there's a notable difference between the volume of buy and sell orders. FVGs can be found across various asset classes, including forex, commodities, stocks, and cryptocurrencies.
FVGs in this toolkit have the ability to detect raids of FVG which helps to identify potential price reversals.
Mitigation option helps to change from what source FVGs will be identified: Close, Wicks or AVG.
4. SWING FAILURE PATTERN (SFP):
The Swing Failure Pattern is a liquidity engineering pattern, generally used to fill large orders. This means, the SFP generally occurs when larger players push the price into liquidity pockets with the sole objective of filling their own positions.
SFP is a technical analysis tool designed to identify potential market reversals. It works by detecting instances where the price briefly breaks a previous high or low but fails to maintain that breakout, quickly reversing direction.
How it works:
Pattern Detection: The indicator scans for price movements that breach recent highs or lows.
Reversal Confirmation: If the price quickly reverses after breaching these levels, it's identified as an SFP.
➤ SFP Display:
Bullish SFP: Marked with a green symbol when price drops below a recent low before reversing upwards.
Bearish SFP: Marked with a red symbol when price rises above a recent high before reversing downwards.
➤ Deviation Levels: After detecting an SFP, the indicator projects white lines showing potential price deviation:
For bullish SFPs, the deviation line appears above the current price.
For bearish SFPs, the deviation line appears below the current price.
These deviation levels can serve as a potential trading opportunity or areas where the reversal might lose momentum.
With Volume Threshold and Filtering of SFP traders can adjust their trading style:
Volume Threshold: This setting allows traders to filter SFPs based on the volume of the reversal candle. By setting a higher volume threshold, traders can focus on potentially more significant reversals that are backed by higher trading activity.
SFP Filtering: This feature enables traders to filter SFP detection. It includes parameters such as:
5. LIQUIDITY CONCEPTS:
➤ Equal Lows (EQL) and Equal Highs (EQH) are important concepts in liquidity-based trading.
EQL: A series of two or more swing lows that occur at approximately the same price level.
EQH: A series of two or more swing highs that occur at approximately the same price level.
EQLs and EQHs are seen as potential liquidity pools where a large number of stop loss orders or limit orders may be clustered. They can be used as potential reverse points for trades.
This multi-period feature allows traders to select less and more significant EQL and EQH:
➤ Liquidity wicks:
Liquidity wicks are a minor representation of a stop-loss hunt during the retracement of a pivot point:
➤ Buy and Sell side liquidity:
The buy side liquidity represents a concentration of potential buy orders below the current price level. When price moves into this area, it can lead to increased buying pressure due to the execution of these orders.
The sell side liquidity indicates a pool of potential sell orders below the current price level. Price movement into this area can result in increased selling pressure as these orders are executed.
➤ Sweep Liquidation Zones:
Sweep Liquidation Zones are crucial for understanding market structure and potential future price movements. They provide insights into areas where significant market participants have been forced out of their positions, potentially setting up new trading opportunities.
🔵 USAGE & EXAMPLES
The core principle behind the success of this toolkit lies in identifying "confluence." This refers to the convergence of multiple trading indicators all signaling the same information at a specific point or area. By seeking such alignment, traders can significantly enhance the likelihood of successful trades.
MS + OBs
The chart illustrates a highly bullish setup where the price is rejecting from a bullish order block (POC), while simultaneously forming a bullish Swing Failure Pattern (SFP). This occurs after an internal structure change, marked by a bullish Change of Character (CHoCH). The price broke through a bearish order block, transforming it into a breaker block, further confirming the bullish momentum.
The combination of these elements—bullish order blocks, SFP, and CHoCH—creates a powerful bullish signal, reinforcing the potential for upward movement in the market.
SFP + Bear OB
This chart above displays a bearish setup with a high probability of a price move lower. The price is currently rejecting from a bear order block, which represents a key resistance area where significant selling pressure has previously occurred. A Swing Failure Pattern (SFP) has also formed near this bear order block, indicating that the price briefly attempted to break above a recent high but failed to sustain that upward movement. This failure suggests that buyers are losing momentum, and the market could be preparing for a move to the downside.
Additionally, we can toggle on the Deviation Area in the SFP section to highlight potential levels where price deviation might occur. These deviation areas represent zones where the price is likely to react after the Swing Failure Pattern:
BUY – SELL sides + EQL
The chart showcases a bullish setup with a high probability of price breaking out of the current sell-side resistance level. The market structure indicates a formation of Equal Lows (EQL), which often suggests a build-up of liquidity that could drive the price higher.
The presence of strong buy-side pressure (69%), indicated by the green zone at the bottom, reinforces this bullish outlook. This area represents a key support zone where buyers are outpacing sellers, providing the foundation for a potential upward breakout.
EQL + Bull ChoCh
This chart illustrates a potential bullish setup, driven by the formation of Equal Lows (EQL) followed by a bullish Change of Character (CHoCH). The presence of Equal Lows often signals a liquidity build-up, which can lead to a reversal when combined with additional bullish signals.
Liquidity grab + Bull ChoCh + FVGs
This chart demonstrates a strong bullish scenario, where several important market dynamics are at play. The price begins its upward momentum from Liquidity grab following a bullish Change of Character (CHoCH), signaling the transition from a bearish phase to a bullish one.
As the price progresses, it performs liquidity grabs, which serve to gather the necessary fuel for further movement. These liquidity grabs often occur before significant price surges, as large market participants exploit these areas to accumulate positions before pushing the price higher.
The chart also highlights a market imbalance area, showing strong momentum as the price moves swiftly through this zone.
In this examples, we see how the combination of multiple “smart money” tools helps identify a potential trade opportunities. This is just one of the many scenarios that traders can spot using this toolkit. Other combinations—such as order blocks, liquidity grabs, fair value gaps, and Swing Failure Patterns (SFPs)—can also be layered on top of these concepts to further refine your trading strategy.
🔵 SETTINGS
Window: limit calculation period
Swing: limit drawing function
Mapping structure: show structural points
Algorithmic Logic: (Extreme-Adjusted) Use max high/low or pivot point calculation
Algorithmic loopback: pivot point look back
Show Last: Amount of Order block to display
Hide Overlap: hide overlapping order blocks
Construction: Size of the order blocks
Fair value gaps: Choose between normal FVG or Breaker FVG
Mitigation: (close - wick - avg) point to mitigate the order block/imbalance
SFP lookback: find a higher / lower point to improve accuracy
Threshold: remove less relevant SFP
Equal H&L: (short-mid-long term) display longer term
Liquidity Prints: Shows wicks of candles where liquidity was grabbed
Sweep Area: Identify Sweep Liquidation areas
By combining these indicators in one toolkit, traders are equipped with a comprehensive suite of tools that address every angle of the Smart Money Concept. Instead of relying on disparate tools spread across various platforms, having them integrated into a single, cohesive system allows traders to easily see confluence and make more informed trading decisions.
Pesquisar nos scripts por "ha溢价率"
ADR Study [TFO]This indicator is focused on the Average Daily Range (ADR), with the goal of collecting data to show how often price reaches/closes through these levels, as well as a look at historical moves that reached ADR and at similar times of day to study how price moved for the remainder of the session.
The ADR here (blue line) is calculated using the difference between a day's highest and lowest points. If our ADR length is 5, then we are taking this difference from the last 5 days and averaging them together. At the following day's open, we take half of this average and plot it above and below the daily opening price to place theoretical limits on how far price may move according to the lookback period. The triangles indicate when price has reached ADR (either +ADR or -ADR), and alerts can be created for these events.
The Scale Factor is an optional parameter to scale the ADR by a certain amount. If set to 2 for example, then the ADR would be 2x the average daily range. This value will be reflected in the statistics options so that users can see how different values affect the outcomes.
Show Table will display data collected on how often price reaches these levels, and how often price closes through them, for each day of the week. By default, these are colored as blue and red, respectively. From the following chart of NQ1!, we can see for example that on Mondays, price reached +ADR 38% of the time and closed through it 23% of the time. Note that the statistics for closing through the ADR levels are derived from all instances, not just those that reached ADR.
Show Sample Sizes will display how many instances were collected for all given sets of data. Referring to the same example of NQ1!, we can see that this particular chart has collected data from 109 Mondays. From those Mondays, 41 reached +ADR (38%, verifying our initial claim) and 25 closed through it (23%). This is important to understand the scope of the data that we're working with, as percentages can be misleading for smaller sample sizes.
Show Histogram will plot the same exact data as the table, just in a histogram form to visually emphasize the differences on a day-by-day basis. On this chart of RTY1!, we can see for example from the top histogram that on Wednesdays, 40% reached +ADR and only 22% closed through it. Similarly if we look at the bottom histogram, we can see that Wednesdays reached -ADR 46% of the time and closed through it only 28% of the time.
We can also use Show Sample Sizes to display the same information that would be in the table, showing how many instances were collected for each event. In this case we can see that we observed 175 Fridays, where 76 reached +ADR (43%) and 44 closed above it (25%).
Show Historical Moves is an interesting feature of this script. When enabled, if price has reached +/- ADR in the current session, the indicator will plot the evolution of the close prices from all past sessions that reached +/- ADR to see how they traded for the remainder of the session. These calculations are made with respect to the ADR range at the time that price traded through these levels.
Historical Proximity (Bars) allows the user to observe historical moves where price reached ADR within this many bars of the current session (assuming price has reached an ADR level in the current session). In the above chart, this is set to 1000 so that we can observe each and every instance where price reached an ADR level. However, we can refine this a bit more.
By limiting the Historical Proximity to something like 20, we are only considering historical moves that reached ADR within 20 bars of todays +ADR reach (9:50 am EST, noted by the blue triangle up). We can enable Show Average Move to display the average move by the filtered dataset, and Match +/-ADR to only observe moves inline with the current day's price action (in this case, only moves that reached +ADR, since price has not reached -ADR).
We can add one more filter to this data with the setting Only Show Days That: closed through ADR; closed within ADR; or either. The option either is what you see above, as we are considering both days that closed through ADR and days that closed within it (note that in this case, closing within ADR simply means that price reached +ADR and closed the day below it, and vice versa for -ADR; this does not mean that price must have closed in between +ADR and -ADR). If we set this to only show instances that closed within ADR, we see the following data.
Alternatively, we can choose to Only Show Days That closed through ADR, where we would see the following data. In this case, the average move very much resembles the price action that occurred on this particular day. This is in no way guaranteed, but it makes an interesting case for how we could use this data in our analysis by observing similar, historical price action.
Please note that this data will change over time on a rolling basis due to TradingView's bar lookback, and that for this same reason, lower timeframes will yield less data than larger timeframes.
Intellect_city - World Cycle - Ath - Timeframe 1D and 1WIndicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA, not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. However, in this instance, it does so with a high degree of accuracy over Bitcoin's adoption phase of growth.
Bitcoin Price Prediction Using This Tool
The Pi Cycle Top Indicator forecasts the cycle top of Bitcoin’s market cycles. It attempts to predict the point where Bitcoin price will peak before pulling back. It does this on major high time frames and has picked the absolute tops of Bitcoin’s major price moves throughout most of its history.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter-term moving average, which is the 111-day moving average, has reached an x2 multiple of the 350-day moving average. Historically, it has proved advantageous to sell Bitcoin around this time in Bitcoin's price cycles.
It is also worth noting that this indicator has worked during Bitcoin's adoption growth phase, the first 15 years or so of Bitcoin's life. With the launch of Bitcoin ETF's and Bitcoin's increased integration into the global financial system, this indicator may cease to be relevant at some point in this new market structure.
Momentum Alligator 4h Bitcoin StrategyOverview
The Momentum Alligator 4h Bitcoin Strategy is a trend-following trading system that operates on dual time frames. It utilizes the 1D Williams Alligator indicator to identify the prevailing major price trend and seeks trading opportunities on the 4-hour (4h) time frame when the momentum is turning up. The strategy is designed to close trades if the trend fails to develop or holding position if price continues increasing without any significant correction. Note that this strategy is specifically tailored for the 4-hour time frame.
Unique Features
2-layers market noise filtering system: Trades are only initiated in the direction of the 1D trend, determined by the Williams Alligator indicator. This higher time frame confirmation filters out minor trade signals, focusing on more substantial opportunities. At the same time, strategy has additional filter on 4h time frame with Awesome Oscillator which is showing the current price momentum.
Flexible Risk Management: The strategy exclusively opens long positions, resulting in fewer trades during bear markets. It incorporates a dynamic stop-loss mechanism, which can either follow the jaw line of the 4h Alligator or a user-defined fixed stop-loss. This flexibility helps manage risk and avoid non-trending markets.
Methodology
The strategy initiates a long position when the d-line of Stochastic RSI crosses up it's k-line. It means that there is a high probability that price momentum reversed from down to up. To avoid overtrading in potentially choppy markets, it skips the next two trades following a winning trade, anticipating sideways movement after a significant price surge.
This strategy has two layers trades filtering system: 4h and 1D time frames. The first one is awesome oscillator. It shall be increasing and value has to be higher than it's 5-period SMA. This is an additional confirmation that long trade is opened in the direction of the current momentum. As it was mentioned above, all entry signals are validated against the 1D Williams Alligator indicator. A trade is only opened if the price is above all three lines of the 1D Alligator, ensuring alignment with the major trend.
A trade is closed if the price hits the 4h jaw line of the Alligator or reaches the user-defined stop-loss level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 2% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Stochastic RSI on 4h time frame to open long trade when momentum started reversing to the upside. On the one hand, Stochastic RSI is one of the most sensitive indicator, which allows to react fast on the potential trend reversal. On the other hand, this indicator can be too sensitive and provide a lot of false trend changing signals. To eliminate this weakness we use two-layers trades filtering system.
The first layer is the 4h Awesome oscillator. This is less sensitive momentum indicator. Usually it starts increasing when price has already passed significant distance from the actual reversal point. The strategy opens long trade only is Awesome oscillator is increasing and above it's 5-period SMA. This approach increases the probability to filter the false signals during the choppy market or if the reversal is false.
The second layer filter is the Williams Alligator indicator on 1D time frame. The 1D Alligator serves as a filter for identifying the primary trend and increases probability to avoid the trades with low potential because trading against major trend usually is more risky. It's much better to catch the trend continuation than local bounce.
Last but not least feature of this strategy is close trades condition. It uses the flexible approach. First of all, user can set up the fixed stop-loss according to his own risk-tolerance, by default this value is 2% of price movement. It restricts the potential loss at the moment when trade has just been opened. Moreover strategy utilizes the 4h Williams Alligator's jaw line to exit the trade. If price fell below it trade is closed. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results:
Operating window: Date range of backtests is 2021.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -3.04%
Maximum Single Profit: +29.67%
Net Profit: +6228.01 USDT (+62.28%)
Total Trades: 118 (24.58% win rate)
Profit Factor: 1.71
Maximum Accumulated Loss: 1527.69 USDT (-11.52%)
Average Profit per Trade: 52.78 USDT (+0.89%)
Average Trade Duration: 60 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use:
Add the script to favorites for easy access.
Apply to the 4h timeframe desired chart (optimal performance observed on the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
Support and Resistance ZoneSupport and Resistance Zone Indicator :
Introduction :
The purpose of this indicator is to identify the chart symbol's main supports and resistances. It displays these key zones, which are very important psychological points for traders. Since support and resistance are not very precise levels, the indicator displays them as zones.
Pivots :
Pivots are a key concept in identifying support and resistance. The indicator uses two types of pivot:
Pivot high : This is a high point that has not been reached by a user-defined number of candles on either the left and right of this candle. The " left pivot leg " is the number of candles before this pivot point that have not reached the realized high, and the " right pivot leg " is the number of candles after this pivot point that have not reached this high. If these two conditions are met, the pivot point is considered a turning point, and resistance is probably the cause.
Pivot low : This is a low point that has not been reached by a user-defined number of candles on either the left or right. The " left pivot leg " is the number of candles before this pivot point that have not reached the candle low, and the " right pivot leg " is the number of candles after this pivot point that have not reached this low. If these two conditions are met, the pivot point is considered a turning point, and support is probably the cause.
Support/Resistance area :
If a pivot point has been identified, the indicator considers it a resistance if it's a pivot high, or a support if it's a pivot low. To define the support or resistance zone, we'll use the ATR (Average True Range), an indicator that measures asset volatility. We'll take the ATR of the candle for which the pivot was spotted, and use it as the width of the support or resistance zone. Thus the upper line of support/resistance is at pivot+atr/2 and the lower line is at pivot-atr/2 . The greater the volatility, the larger the zone.
New Support/Resistance :
If a new pivot has been identified, but the level of this pivot lies between the lower line and the upper line of the previous support or resistance, the indicator considers this to be the same support or resistance as before. In this case, no new support or resistance is created. The pivot must be outside the area of the previous support or resistance to be validated.
Anticipated Support/Resistance :
This indicator also allows early detection of support or resistance. To do this, the value of the right pivot legs will be shortened in order to find these areas more quickly. The support or resistance will then be considered anticipated and may disappear at any time if the high/low is reached. On the other hand, if the high/low is not reached, and a number of candles equal to the " Right Pivot Legs" parameter has elapsed since the detection of this anticipated support/resistance, it will be considered validated and will integrate the other supports/resistances of the chart.
Extended supports/resistances :
For a more optimal view, the indicator allows the user to choose the number of last support or resistance levels to be extended to the last candle. This must be specified in the indicator parameters.
Parameters :
Pivot Legs : Determine the left and right legs of the pivot i.e the number of candle before and after the pivot that doesn’t reach pivot point. The pivot is validated only if this two conditions are verified.
Extend Last Supports : Number of supports to extend to the last bar
Extend Last Resistances : Number of resistances to extend to the last bar
Show Support/Resistance Anticipated : If yes, will find anticipated support and resistance
Right Pivot Legs for Anticipation : Determine the right legs of pivots to find faster a support or a resistance.
Conclusion :
This indicator plot support and resistance zones based on pivot. The width of support and resistance zones are calculated with ATR. Possibility to find anticipated support and resistance in order to have more timeliness informations.
Enjoy the indicator and don’t forget to take the trade ;)
Relative Strength Scoring SystemRelative Strength Scoring System :
Important prerequisite :
This indicator can be loaded on any forex chart, i.e. a currency pair, but must not be loaded on any other asset due to certain market closures.
The chart timeframe must be less than or equal to the trading timeframe, which is the indicator's first parameter. A timeframe equal to that of the "Trading Timeframe" parameter is preferable.
Introduction :
This indicator measures the relative strength of a currency against all other currencies using spread formulas. It gives an indication of which currencies are bullish, neutral or bearish. The ultimate aim of this indicator is to find out which pair will generate a higher probability of gain than the others by pairing the most bullish pair with the most bearish pair.
Spread formulas :
To find the relative strength of a currency compared with others, we use the following spreads formulas :
USD = (FX:USDJPY/100+SAXO:USDEUR+FX:USDCHF+SAXO:USDGBP+FX:USDCAD+SAXO:USDAUD+FX_IDC:USDNZD)/7
JPY = (SAXO:JPYUSD/100+FX_IDC:JPYAUD/100+FX_IDC:JPYCAD/100+FX_IDC:JPYNZD/100+FX_IDC:JPYCHF/100+SAXO:JPYEUR/100+FX_IDC:JPYGBP/100)/7
CHF = (FX:CHFJPY/100+SAXO:CHFUSD+SAXO:CHFEUR+FX_IDC:CHFGBP+FX_IDC:CHFCAD+SAXO:CHFAUD+FX_IDC:CHFNZD)/7
EUR = (FX:EURJPY/100+FX:EURUSD+FX:EURCHF+FX:EURGBP+FX:EURCAD+FX:EURAUD+FX:EURNZD)/7
GBP = (FX:GBPJPY/100+FX:GBPUSD+FX:GBPCHF+SAXO:GBPEUR+FX:GBPCAD+FX:GBPAUD+FX:GBPNZD)/7
CAD = (FX:CADJPY/100+SAXO:CADUSD+FX:CADCHF+FX_IDC:CADGBP+SAXO:CADEUR+FX_IDC:CADAUD+FX_IDC:CADNZD)/7
AUD = (FX:AUDJPY/100+FX:AUDUSD+FX:AUDCHF+SAXO:AUDGBP+FX:AUDCAD+SAXO:AUDEUR+FX:AUDNZD)/7
NZD = (FX:NZDJPY/100+FX:NZDUSD+FX:NZDCHF+SAXO:NZDGBP+FX:NZDCAD+SAXO:NZDAUD+SAXO:NZDEUR)/7
CRYPTO = (BITSTAMP:BTCUSD+BITSTAMP:ETHUSD+BITSTAMP:LTCUSD+BITSTAMP:BCHUSD)/4
Timeframes :
As mentioned in the prerequisites, the chart timeframe must not be greater than the trading timeframe. The latter corresponds to the timeframe chosen by the trader to enter a position, and is the indicator's first parameter. Once this has been chosen, the algorithm selects the timeframes of the "Trend" and "Velocity" charts. Here's how it allocates them :
Trading TF => ("Velocity TF", "Trend TF")
"5min" => ("15min ", "60min")
"15min" => ("60min ", "4h")
"30min" => ("2h ", "8h")
"60min" => ("4h ", "12h")
"4h" => ("12h", "1D")
"6h" => ("1D", "3D")
"8h" => ("1D", "4D")
"12h" => ("2D", "1W")
"1D" => ("3D", "1W")
Trend Scoring System :
When the timeframe of the trend graph has been allocated, the algorithm will establish this graph's score using three criteria :
Trend chart pivot points: if the last two pivots, high and low, are increasing, the score is 1; if they are decreasing, the score is -1; else the score is 0.
SMA: if its slope is increasing with a candle strictly above the SMA value, the score is 1; if its slope is decreasing with a candle strictly below it, the score is -1; otherwise, it is 0.
MACD: if the MACD is positive, the score is 1, if it is negative, the score is -1; else it's 0.
We then sum the scores of these three criteria to find the trend score.
Velocity Scoring System :
In the same way, we analyze the score of the "velocity" graph with its corresponding timeframe using three criteria :
The EMA: if its slope is increasing with a candle strictly above the EMA value, the score is 1; if its slope is decreasing with a candle strictly below it, the score is -1; otherwise, it is 0.
The RSI: if the RSI's EMA has an increasing slope with an RSI strictly greater than the value of this EMA, the score is 1; and if the RSI's EMA has a decreasing slope with an RSI strictly less than this EMA, the score is -1; otherwise it is 0.
SAR parabolic: if the SAR is below the price, the score is 1; if it is above the price, the score is -1.
We then sum the scores of these three criteria to find the velocity score.
Relative Strength Scoring System :
Once the trend score and velocity score have been calculated, we determine the relative strength score of each currency using the following algorithm :
If trend score >=2 and velocity score >=2, the currency is bullish.
If trend score <=2 and velocity score <=2, currency is bearish
If (trendScore>=2 or velocityScore>=2) and (trendScore=1 or velocityScore=1) the currency is not yet bullish
If (trendScore<=2 or velocityScore<=2) and (trendScore=-1 or velocityScore=-1) the currency is not yet bearish.
Otherwise the currency is neutral
Parameters :
Trading Timeframe: the trading timeframe chosen by the trader for which he makes his position entry and exit decisions. Default is 1h
Pivot Legs: Parameter used for the chart "Trend" setting the pivot strength to the right and left of high/low. Default is 2
SMA Length: SMA length of the chart "Trend". Default is 20
MACD Fast Length: Length of the MACD fast SMA calculated on the chart "Trend". Default is 12
MACD Slow Length: Length of the MACD slow SMA calculated on the chart "Trend". Default is 26
MACD Signal Length: Length of the MACD signal SMA calculated on the chart "Trend". Default is 9
EMA Length: EMA length of the "Velocity" graph. Default is 13
RSI Length: RSI length of the "Velocity" graph. Default is 14
RSI EMA Length: Length of the RSI EMA. Default is 9
Parabolic SAR Start: Start of the SAR parabola in the "Velocity" graph. Default is 0.02
Parabolic SAR Increment: Increment of the SAR parabola in the "Velocity" graph. Default is 0.02
Parabolic SAR Max: Maximum of the SAR parabola in the "Velocity" graph. Default is 0.2
Conclusion :
This indicator has been designed to determine the relative strength of the major currencies against each other. The aim is to know which pair to trade at the right time in order to maximize the probability of a successful trade. For example, if the USD is bullish and the NZD bearish, we'll short the NZDUSD pair.
Enjoy this indicator and don't forget to take the trade ;)
MACD_RSI_trend_followingINFO:
This indicator can be used to build-up a strategy for trading of assets which are currently in trending phase.
My preference is to use it on slowly moving assets like GOLD and on higher timeframes, but practice may show that we find more usefull cases.
This script uses two indicators - MACD and RSI, as the timeframe that those are extracted for is configurable (defaults with the Chart TF, but can be any other selected by the user).
The strategy has the following simple idea - buy if any if the conditions below is true:
The selected TF MACD line crosses above the signal line and the TF RSI is above the user selected trigger value
The selected TF MACD line is above the signal line and the TF RSI crosses above the user selected trigger value
Once we're in position we wait for the selected TF MACD line to cross below the signal line, and then we set a SL at the low of that bar
DETAILS and USAGE:
In the current implementation I find two possible use cases for the indicator:
as a stand-alone indicator on the chart which can also fire alerts that can help to determine if we want to manually enter/exit trades based on them
can be used to connect to the Signal input of the TTS (TempalteTradingStrategy) by jason5480 in order to backtest it, thus effectively turning it into a strategy (instructions below in TTS CONNECTIVITY section)
In the example below we see a position opened at the bar after the buy indicator from the script has been triggered, and then later after the SL indicator from the script has been triggered a SL has been set on the lower wick of the closing candle, and the position eventually got closed once the price hit that level. Note that most of the drawing on the example snapshot below are from the TTS indicator following the buy/sell/SL conditions themseves:
Trading period can be selected from the indicator itself to limit to more interesting periods.
Arrow indications are drawn on the chart to indicate the trading conditions met in the script - green arrow for a buy signal indication and orange for LTF crossunder to indicate setting of SL.
SETTINGS:
Leaving all of the settings as in vanilla use case, as both the MACD and RSI indicator's settings follow the default ones for the stand-alone indicators themselves.
The start-end date is a time filter that can be extermely usefull when backtesting different time periods.
Pesonal preference is using the script on a D/W timeframe, while the indicator is configured to use Monthly chart.
The default value of the RSI filter is left to 50, which can be changed. I.e. if the RSI is above 50 we have a regime filter based on the MACD criteria.
EXTERNAL LIBRARIES:
The script uses a couple of external libraries:
HeWhoMustNotBeNamed/enhanced_ta/14 - collection of TA indicators
jason5480/tts_convention/3 - more details about the Template Trading Strategy below
I would like to highly appreciate and credit the work of both HeWhoMustNotBeNamed and jason5480 for providing them to the community.
TTS SETTINGS (NEEDED IF USED TO BACKTEST WITH TTS):
The TempalteTradingStrategy is a strategy script developed in Pine by jason5480, which I recommend for quick turn-around of testing different ideas on a proven and tested framework
I cannot give enough credit to the developer for the efforts put in building of the infrastructure, so I advice everyone that wants to use it first to get familiar with the concept and by checking
by checking jason5480's profile www.tradingview.com
The TTS itself is extremely functional and have a lot of properties, so its functionality is beyond the scope of the current script -
Again, I strongly recommend to be thoroughly epxlored by everyone that plans on using it.
In the nutshell it is a script that can be feed with buy/sell signals from an external indicator script and based on many configuration options it can determine how to execute the trades.
The TTS has many settings that can be applied, so below I will cover only the ones that differ from the default ones, at least according to my testing - do your own research, you may find something even better :)
The current/latest version that I've been using as of writing and testing this script is TTSv48
Settings which differ from the default ones:
from - False (time filter is from the indicator script itself)
Deal Conditions Mode - External (take enter/exit conditions from an external script)
🔌Signal 🛈➡ - MACD_RSI_trend_following: 🔌Signal to TTSv48 (this is the output from the indicator script, according to the TTS convention)
Sat/Sun - true (for crypto, in order to trade 24/7)
Order Type - STOP (perform stop order)
Distance Method - HHLL (HigherHighLowerLow - in order to set the SL according to the strategy definition from above)
The next are just personal preferenes, you can feel free to experiment according to your trading style
Take Profit Targets - 0 (either 100% in or out, no incremental stepping in or out of positions)
Dist Mul|Len Long/Short- 10 (make sure that we don't close on profitable trades by any reason)
Quantity Method - EQUITY (personal backtesting preference is to consider each backtest as a separate portfolio, so determine the position size by 100% of the allocated equity size)
Equity % - 100 (note above)
The Ultimate Buy and Sell IndicatorThis indicator should be used in conjunction with a solid risk management strategy that does not over-leverage positions and uses stop-losses. You can not rely 100% on the signals provided by this indicator (or any other for that matter).
With that said, this indicator can provide some excellent signals.
It has been designed with a large number of customization options intended for advanced traders, but you do not HAVE to be an advanced user to simply use the indicator. I have tried to make it easy to understand, and this section will provide you with a better understanding of how to use it.
NOTE:
While NOT REQUIRED, I would recommend also finding my indicator called, "Ultimate RSI", which is designed to work together with this indicator (visually). They both contain the same settings and allow you to visualize changes made in this indicator that can not be displayed on the main chart.
This indicator creates it's own candles(bars), so you have to go into your main settings and turn off the "body, border and wick" color settings. Using a dark background is also recommended.
How does it work?
The indicator mainly relies on the RSI indicator with Bollinger Bands for signals. (Though not entirely)
First, there are something that I call "Watch Signals", which are various Bollinger Band crossing events. This could be the price crossing Bollinger Bands or the RSI crossing Bollinger Bands.
There are separate watch signals for buys and sells. Buy watch signals are colored orange to match the BUY signal candle color and Fuchsia (kind of a bright purple) to match SELL signal candles.
In order for most buy or sell signals to be created, there must first be a watch signal. There is a lookback period (or length) for watch signals to be used, and after that many candles (bars) have passed, they will be ignored. You can set a length to look back as well as a time to wait before creating any.
What this means is that if there has previously been (for instance) a sell signal. You can tell it to wait 10 bars before creating any buy watch signals. You can then also tell it that it should look back 10 bars from the current one in order to find any buy watch signals. This means that if you had it set up that way 10 to wait and 10 to validate, it would start allowing buy watch signals 11 bars after a sell, and then once you hit 20 bars, it will start leaving a gap (invisible to you) as the 10 bar lookback period starts moving forward with each new bar. This is useful in order to keep signals more spaced apart as some bad signals come quickly after another one.
Example: You may get a sell signal where the Bollinger bands are tight, then the price easily drops down into the lower band creating a buy watch signal, then you get a "fake" or short pump up and it says buy, but then drops dramatically afterwards. The wait period can ensure that the sell stays in effect longer before a buy is considered by blocking any buy watch signals for a period of time.
After you get a watch signal, the system then looks for various other things to happen to create buy or sell signals. This could be the RSI crossing the (slow) RSI Basis line (from its Bollinger bands), it could be the price crossing its basis line, it could be MACD crosses, it could even be RSI crossing certain levels. All of these are options. If you like the MACD strategy and want it to give you buy and sell signals from just MACD crosses, simply select that option for signals.
It is also able to use the first of any of the options that takes place.
I included an option to force alternating buy and sell signals, rather than showing groups of, or subsequent buy, buy, buy signals, for instance.
Moving on....
You can change the moving average that is used to calculate the RSI. The standard moving average for RSI is the RMA (aka SWMA). Changes to this can dramatically change your signals. You also have the option to change the moving average type used in the Bollinger bands calculation. You can change the length of these as well. The same goes for the Bollinger bands over the Price chart. I added an ATR option for the RSI Bollinger bands to play with, as well. You are able to adjust the standard deviation (multiplier) of the bands as well, which will of course affect the signals.
The ways you can play with signals are nearly infinite, so have fun figuring it out.
The indicator allows for moving averages to be shown as well, with a variety of types to choose from. The standard numbers are 5, 10, 20, 50, 100 and 200, with the addition of a custom moving average of your choice. You can also change the color of this one. You can choose to show them all or any of them you want to show, in any combination, although the TYPE of moving average (SMA, EMA, WMA, etc.) will apply to all of them.
You may also notice the Bollinger Bands over the Price are colored, and become more or less transparent.
The color is derived from the trend of the RSI or the RSI basis (your choice). It looks back at the value however many bars you want and compares the values and that's how it determines if it is trending up or down. Since RSI is a directional momentum indicator, this can be quite useful. If you see the bands are getting darker, this will explain why.
The indicator has a lookback period for determining the widest the bands (which measure volatility) have been over that period of time. This is the baseline. It then will make the bands disappear (by making them more transparent) if the volatility is low. This indicates that a change in volatility is coming and that price isn't really changing much compared to the past (default 500) bars. If they become bright, this is because price has started trending in a direction and volatility is increasing.
I should also note that the candles are colored based on RSI levels.
If you use the Ultimate Companion indicator, you will be able to see the RSI levels (zones) that the colors are based on. As RSI moves into a new range, the candle color will change.
I have created a yellow zone where the candles turn yellow. This is when RSI is between (default) 45 and 55, indicating there is basically no momentum and price is going sideways. This is a good place to get trapped in bad trades, and there is a Yellow RSI Filter to block signals in this area to keep you from entering bad trades.
Green candles indicate values over 55 (getting brighter as RSI rises) and red candles are RSI values under 45 (getting brighter as RSI values get lower). If you see white, this means RSI is either over 80 or under 20. A sharp reversal is almost always imminent at this stage.
When we talk about Buy and Sell Signals, they draw a green or red triangle and it literally says BUY or SELL. There is an option to color the background for added visibility. These signals do not "repaint", what this means is that they can be late. To account for this, I have included a background color that will flash as a warning that a buy or sell could be imminent, although it may fail to break through and set a buy or sell signal. This is simply an advanced warning. The reason is that sometimes a candle may be very large and you won't be told to buy or sell during the candle until the move is completely over and now you're getting in on the next one. That's not a great feeling, so I made it repaint the background color and not repaint the completed signal. You get the best of both worlds.
This indicator also uses complex logic to handle things.
When there is a buy signal, it enters into a state of having been bought, or a "bought state". The same for sells. If Force alternating signals is off, you could have more than one buy in a bought state, or more than one sell in a sell state. There is an option to color the background green during the full duration of a bought state, or red during the full duration of a sold state.
I have added divergence.
This shows that the lows or highs of RSI and PRICE are different. If RSI is making higher highs but the price is not, then the price is likely to follow this bullish divergence, if the opposite happens, it's bearish. It will draw a line on the chart connecting the highs and lows and call it bearish or bullish. You can adjust this as well.
I have an RSI High/Low filter. If the RSI basis (or average) is very high or low, you can block signal from this area since the price is likely to continue in that direction before actually reversing.
You can change the settings of the MACD if you choose to use it for signals, and if you want to see it, you'll have to run that indicator below the chart and match the settings to see what is going on, just like the RSI.
Going back to Watch Signals. You can also choose to require more than one watch signal if you choose. You can skip watch signals, so it will ignore the first or second one, whatever you want to do. You can color the background to show you where watch signals have been skipped.
Regarding the wait period for creating watch signals after a sell or after a buy, you can also color the background to see where these were blocked by the wait period.
Lastly you can choose which type of watch signals to use, or keep them from being shown on the chart. This allows you to study the history of how the asset you are trading behaves and customize the behavior of signals based on your study of it.
Everything in the settings area has tooltips, which will explain what that thing does to help you along this journey.
I hope this indicator (and perhaps Ultimate RSI alongside this) will help you take your trading to the next level.
Renko StrategyRENKO STRATEGY
CAUTION : This strategy must be applied to a candlestick chart (not a Renko chart).
INTRODUCTION :
The Traditional Renko chart has been reproduced and is plotted according to the evolution of the price. It will enable us to receive buy or sell signals and follow major trends. This is a medium/long term strategy and depends a lot on the box size chosen in the parameters. There's also a money management method allowing us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RENKO CHART :
Renko chart construction methodology :
The user must first choose the box size. The minimum is 0.00001 and there is no maximum. The default is 10. The user must then choose the source that will define the data on which the calculations will be based (high, low, open, close). By default, close is selected. The first candle on the chart is used to draw the first box with its high and low.
Each time the price changes by the amount of the box size relative to the high or low of the last box, a new box is added above or below the previous one. If price variations are less than the box size, the same box is added next to the previous one. If price variations are N (integer number) times greater than box size, N boxes are added above or below the previous one. Each box added above the previous one is a green box, while each box added below the previous one is a red box.
Conditions for drawing a green box above the previous one :
(source - high_of_the_last_box) / box_size > 1
Condition for drawing a red box below the previous one :
(low_of_the_last_box - source) / box_size > 1
If neither condition is triggered, the same box is drawn next to the previous one.
Example :
The last candle has drawn a box with low 12 and high 14. The box size is therefore 2. The strategy will look at the value of the close each time a candle ends. The current candle closes with a close equal to 15.5. As the variation from the previous high is only 1.5 (which is less than the box size), the same box is added next to the previous one. The next candle closes at 16.2. The price variation is therefore 2.2 compared with the previous high. We can now add a new green box just above the previous one, with a low of 14 and a high of 16. The same process applies if the candle's close is at least one box size below the low of the last box. In this case, a new red box is placed below the previous one.
PARAMETERS :
Source : Allows you to specify which data will be taken into account by the strategy when performing calculations. The default is close.
Box size : Size of Renko graph boxes. This is a very important parameter to choose carefully, as it has a strong impact on the strategy's performance. Defaults to 10.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. The default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test all possible box sizes to find out which one generates the highest return on BITSTAMP:LTCUSD while limiting the drawdown. This strategy is the most optimal with a box size equal to 5.08 in 8h timeframe.
BUY AND SHORT SIGNALS :
As the aim of this strategy is to follow major trends based on price movements, we need to be on the right side of price fluctuation. We trade every box reversal, i.e. we are LONG when the boxes are green indicating an uptrend and SHORT when they are red indicating a downtrend.
RISK MANAGEMENT :
This strategy can incur losses. The size of the box is decisive, as it is used to plot the RENKO chart and thus trigger buy or sell signals. It's also what allows us to manage risk. For every trade, we risk a maximum amount equal to 2 times the size of the box, i.e. :(5.08*2*nb_contract)/trade_value.
MONEY MANAGEMENT :
The fixed ratio method has been used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy not only increases our performance, but also our drawdown.
Enjoy the strategy and don't forget to take the trade :)
Statistical Package for the Trading Sciences [SS]
This is SPTS.
It stands for Statistical Package for the Trading Sciences.
Its a play on SPSS (Statistical Package for the Social Sciences) by IBM (software that, prior to Pinescript, I would use on a daily basis for trading).
Let's preface this indicator first:
This isn't so much an indicator as it is a project. A passion project really.
This has been in the works for months and I still feel like its incomplete. But the plan here is to continue to add functionality to it and actually have the Pinecoding and Tradingview community contribute to it.
As a math based trader, I relied on Excel, SPSS and R constantly to plan my trades. Since learning a functional amount of Pinescript and coding a lot of what I do and what I relied on SPSS, Excel and R for, I use it perhaps maybe a few times a week.
This indicator, or package, has some of the key things I used Excel and SPSS for on a daily and weekly basis. This also adds a lot of, I would say, fairly complex math functionality to Pinescript. Because this is adding functionality not necessarily native to Pinescript, I have placed most, if not all, of the functionality into actual exportable functions. I have also set it up as a kind of library, with explanations and tips on how other coders can take these functions and implement them into other scripts.
The hope here is that other coders will take it, build upon it, improve it and hopefully share additional functionality that can be added into this package. Hence why I call it a project. Okay, let's get into an overview:
Current Functions of SPTS:
SPTS currently has the following functionality (further explanations will be offered below):
Ability to Perform a One-Tailed, Two-Tailed and Paired Sample T-Test, with corresponding P value.
Standard Pearson Correlation (with functionality to be able to calculate the Pearson Correlation between 2 arrays).
Quadratic (or Curvlinear) correlation assessments.
R squared Assessments.
Standard Linear Regression.
Multiple Regression of 2 independent variables.
Tests of Normality (with Kurtosis and Skewness) and recognition of up to 7 Different Distributions.
ARIMA Modeller (Sort of, more details below)
Okay, so let's go over each of them!
T-Tests
So traditionally, most correlation assessments on Pinescript are done with a generic Pearson Correlation using the "ta.correlation" argument. However, this is not always the best test to be used for correlations and determine effects. One approach to correlation assessments used frequently in economics is the T-Test assessment.
The t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It assesses whether the sample means are likely to have come from populations with the same mean. The test produces a t-statistic, which is then compared to a critical value from the t-distribution to determine statistical significance. Lower p-values indicate stronger evidence against the null hypothesis of equal means.
A significant t-test result, indicating the rejection of the null hypothesis, suggests that there is statistical evidence to support that there is a significant difference between the means of the two groups being compared. In practical terms, it means that the observed difference in sample means is unlikely to have occurred by random chance alone. Researchers typically interpret this as evidence that there is a real, meaningful difference between the groups being studied.
Some uses of the T-Test in finance include:
Risk Assessment: The t-test can be used to compare the risk profiles of different financial assets or portfolios. It helps investors assess whether the differences in returns or volatility are statistically significant.
Pairs Trading: Traders often apply the t-test when engaging in pairs trading, a strategy that involves trading two correlated securities. It helps determine when the price spread between the two assets is statistically significant and may revert to the mean.
Volatility Analysis: Traders and risk managers use t-tests to compare the volatility of different assets or portfolios, assessing whether one is significantly more or less volatile than another.
Market Efficiency Tests: Financial researchers use t-tests to test the Efficient Market Hypothesis by assessing whether stock price movements follow a random walk or if there are statistically significant deviations from it.
Value at Risk (VaR) Calculation: Risk managers use t-tests to calculate VaR, a measure of potential losses in a portfolio. It helps assess whether a portfolio's value is likely to fall below a certain threshold.
There are many other applications, but these are a few of the highlights. SPTS permits 3 different types of T-Test analyses, these being the One Tailed T-Test (if you want to test a single direction), two tailed T-Test (if you are unsure of which direction is significant) and a paired sample t-test.
Which T is the Right T?
Generally, a one-tailed t-test is used to determine if a sample mean is significantly greater than or less than a specified population mean, whereas a two-tailed t-test assesses if the sample mean is significantly different (either greater or less) from the population mean. In contrast, a paired sample t-test compares two sets of paired observations (e.g., before and after treatment) to assess if there's a significant difference in their means, typically used when the data points in each pair are related or dependent.
So which do you use? Well, it depends on what you want to know. As a general rule a one tailed t-test is sufficient and will help you pinpoint directionality of the relationship (that one ticker or economic indicator has a significant affect on another in a linear way).
A two tailed is more broad and looks for significance in either direction.
A paired sample t-test usually looks at identical groups to see if one group has a statistically different outcome. This is usually used in clinical trials to compare treatment interventions in identical groups. It's use in finance is somewhat limited, but it is invaluable when you want to compare equities that track the same thing (for example SPX vs SPY vs ES1!) or you want to test a hypothesis about an index and a leveraged share (for example, the relationship between FNGU and, say, MSFT or NVDA).
Statistical Significance
In general, with a t-test you would need to reference a T-Table to determine the statistical significance of the degree of Freedom and the T-Statistic.
However, because I wanted Pinescript to full fledge replace SPSS and Excel, I went ahead and threw the T-Table into an array, so that Pinescript can make the determination itself of the actual P value for a t-test, no cross referencing required :-).
Left tail (Significant):
Both tails (Significant):
Distributed throughout (insignificant):
As you can see in the images above, the t-test will also display a bell-curve analysis of where the significance falls (left tail, both tails or insignificant, distributed throughout).
That said, I have not included this function for the paired sample t-test because that is a bit more nuanced. But for the one and two tailed assessments, the indicator will provide you the P value.
Pearson Correlation Assessment
I don't think I need to go into too much detail on this one.
I have put in functionality to quickly calculate the Pearson Correlation of two array's, which is not currently possible with the "ta.correlation" function.
Quadratic (Curvlinear) Correlation
Not everything in life is linear, sometimes things are curved!
The Pearson Correlation is great for linear assessments, but tends to under-estimate the degree of the relationship in curved relationships. There currently is no native function to t-test for quadratic/curvlinear relationships, so I went ahead and created one.
You can see an example of how Quadratic and Pearson Correlations vary when you look at CME_MINI:ES1! against AMEX:DIA for the past 10 ish months:
Pearson Correlation:
Quadratic Correlation:
One or the other is not always the best, so it is important to check both!
R-Squared Assessments:
The R-squared value, or the square of the Pearson correlation coefficient (r), is used to measure the proportion of variance in one variable that can be explained by the linear relationship with another variable. It represents the goodness-of-fit of a linear regression model with a single predictor variable.
R-Squared is offered in 3 separate forms within this indicator. First, there is the generic R squared which is taking the square root of a Pearson Correlation assessment to assess the variance.
The next is the R-Squared which is calculated from an actual linear regression model done within the indicator.
The first is the R-Squared which is calculated from a multiple regression model done within the indicator.
Regardless of which R-Squared value you are using, the meaning is the same. R-Square assesses the variance between the variables under assessment and can offer an insight into the goodness of fit and the ability of the model to account for the degree of variance.
Here is the R Squared assessment of the SPX against the US Money Supply:
Standard Linear Regression
The indicator contains the ability to do a standard linear regression model. You can convert one ticker or economic indicator into a stock, ticker or other economic indicator. The indicator will provide you with all of the expected information from a linear regression model, including the coefficients, intercept, error assessments, correlation and R2 value.
Here is AAPL and MSFT as an example:
Multiple Regression
Oh man, this was something I really wanted in Pinescript, and now we have it!
I have created a function for multiple regression, which, if you export the function, will permit you to perform multiple regression on any variables available in Pinescript!
Using this functionality in the indicator, you will need to select 2, dependent variables and a single independent variable.
Here is an example of multiple regression for NASDAQ:AAPL using NASDAQ:MSFT and NASDAQ:NVDA :
And an example of SPX using the US Money Supply (M2) and AMEX:GLD :
Tests of Normality:
Many indicators perform a lot of functions on the assumption of normality, yet there are no indicators that actually test that assumption!
So, I have inputted a function to assess for normality. It uses the Kurtosis and Skewness to determine up to 7 different distribution types and it will explain the implication of the distribution. Here is an example of SP:SPX on the Monthly Perspective since 2010:
And NYSE:BA since the 60s:
And NVDA since 2015:
ARIMA Modeller
Okay, so let me disclose, this isn't a full fledge ARIMA modeller. I took some shortcuts.
True ARIMA modelling would involve decomposing the seasonality from the trend. I omitted this step for simplicity sake. Instead, you can select between using an EMA or SMA based approach, and it will perform an autogressive type analysis on the EMA or SMA.
I have tested it on lookback with results provided by SPSS and this actually works better than SPSS' ARIMA function. So I am actually kind of impressed.
You will need to input your parameters for the ARIMA model, I usually would do a 14, 21 and 50 day EMA of the close price, and it will forecast out that range over the length of the EMA.
So for example, if you select the EMA 50 on the daily, it will plot out the forecast for the next 50 days based on an autoregressive model created on the EMA 50. Here is how it looks on AMEX:SPY :
You can also elect to plot the upper and lower confidence bands:
Closing Remarks
So that is the indicator/package.
I do hope to continue expanding its functionality, but as of now, it does already have quite a lot of functionality.
I really hope you enjoy it and find it helpful. This. Has. Taken. AGES! No joke. Between referencing my old statistics textbooks, trying to remember how to calculate some of these things, and wanting to throw my computer against the wall because of errors in the code, this was a task, that's for sure. So I really hope you find some usefulness in it all and enjoy the ability to be able to do functions that previously could really only be done in external software.
As always, leave your comments, suggestions and feedback below!
Take care!
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
MVRV Z ScoreIndicator Overview
MVRV Z-Score is a bitcoin chart that uses blockchain analysis to identify periods where Bitcoin is extremely over or undervalued relative to its 'fair value'.
It uses three metrics:
1. Market Value: The current price of Bitcoin multiplied by the number of coins in circulation. This is like market cap in traditional markets i.e. share price multiplied by number of shares.
2. Realised Value: Rather than taking the current price of Bitcoin, Realised Value takes the price of each Bitcoin when it was last moved i.e. the last time it was sent from one wallet to another wallet. It then adds up all those individual prices and takes an average of them. It then multiplies that average price by the total number of coins in circulation.
In doing so, it strips out the short term market sentiment that we have within the Market Value metric. It can therefore be seen as a more 'true' long term measure of Bitcoin value which Market Value moves above and below depending on the market sentiment at the time.
3. Z-score (Orange): A standard deviation test that pulls out the extremes in the data between market value and realised value.
How It Can Be Used
The MVRV Z-score has historically been very effective in identifying periods where market value is moving unusually high above realised value. These periods are highlighted by the z-score (red line) entering the pink box and indicates the top of market cycles. It has been able to pick the market high of each cycle to within two weeks.
It also shows when market value is far below realised value, highlighted by z-score entering the green box. Buying Bitcoin during these periods has historically produced outsized returns.
(Bar colors shows when market is trending down or a top - strong red or trending up and bottom - strong green. Added allerts for values)
Bitcoin Price Prediction Using This Tool
MVRV Z-Score bitcoin chart is useful for predicting Bitcoin price at the extremes of market conditions. It is able to forecast where Bitcoin price may need to pull back when MVRV Z-score enters the upper red band, and also when CRYPTOCAP:BTC price may rally after spending time in the lower green band.
Historically it has picked major Bitcoin price highs to within 2 weeks.
Created By
@aweandwonder who has unfortunately since deleted the original article and his online profile.
He built on the initial work to create MVRV by Murad Mahmudov and David Puell
Relative VolumeHello traders,
"There's nothing new on Wall Street" is an age-old saying that still shows its relevance in modern day financial markets; volume still serves as a valuable tool for any trader just as it did for those that came and succeeded before us; in order to succeed in modern day markets one has to take it up a notch and dabble in complicated topics, like math. Now I dunno about you reader but I’m not keen on sitting around all day just to watch numbers on a screen; it’s pretty important to add some color into your life before it becomes dull but how can someone add colors into their trading toolkit as an aid rather than bother? With a bit of help from 3 other amazing open-source indicators you too can become a statistics enjoyer by combining math and colors to make pattern recognition much more intuitive and offering more peace of mind when trading. “Sir but how?”, glad you didn’t ask, it helps with simplifying statistics, in this case a Gaussian bellcurve
“HUH?”, you say? Alright class, Gaussian bellcurves for math dislikers 101 is in session
- Imagine that we have a bunch of numbers that we want to graph. We could just draw a line and plot the numbers on it, but that might not be very interesting.
- Instead, we can use the shape of a bell to show how many of each number we have.
- Let's say we have a lot of people and we want to graph how tall they are. We would start by making a line from the shortest person to the tallest person, and then we would draw the bell shape around the line.
- The bell shape is called a "Gaussian Bell Curve," and it shows us how many people are a certain height.
- In the middle of the bell, where it's the widest, we have the most people who are about average height. As we move to the sides of the bell, the curve gets lower because there are fewer people who are really tall or really short.
The bell curve discussed is the main idea for the candle coloring component of this indicator as being able to analyze the distribution of an entire dataset, in this case volume, can alert us when volume/participation in the market is away from its average using color, and therefore an opportunity could be present. Fair warning, it’s important to not strictly focus on volume as volume is meant to be confluence to the current structure of the market rather than causing tunnel vision.
Why 3 indicators to combine?
It starts with the RVOL by Mik3Christ3ns3n indicator as the backbone by calculating the average volume over a specified period of time, and then compares each new volume value to this average to determine whether it is above or below the average. The indicator then normalizes the volume data and calculates the z-score/standard deviation to determine whether the volume is within normal range or is an anomaly beyond a specified threshold which can also be set into an alert to aid in eyeing possible opportunities.
The code also includes Candle Coloring by Morty as it calculates a function to get the z-score for the size of the candle's body, and then compares it to the z-score for volume to determine whether the body size is a factor in the price action.
Finally, the code plots the anomalies and the normalized volume data on the chart using the first RVOL indicator mentioned, and colors the bars of the chart based on whether they are within normal range or are anomalies which comes from using code from veryfid's relative volume indicator.
Overall, this custom technical indicator is best used to identify unusual changes in trading volume, which may indicate potential price movements in the underlying.
How about some examples?
This first example is for my scalpers wanting to get in and out but not having much of an idea where or let alone how; using a tool like VWAP can be great for determining the area value to execute mean reversion trades once a speculator spots a colored candle anomaly at standard deviation band. Works best when VWAP is flat as it signals lack of conviction from both bulls and bears
This second example is for my fire and forget intraweek swing traders who want to execute a higher timeframe trend-following bias. A speculator starting 2023 off notices that the negative sentiment around Binance from late last year has quieted down and has conviction in upside after BTC began an uptrend as monthly VWAP (right chart) has began sloping up as well as a rally with momentum shown with the blue colored candle so the trader waits wait for a pullback for entry. On the chart to the left of the 4H the speculator notices a pullback into the area of interest to do business so a limit bid is left to enter for continued upside in Bitcoin through January 2023 just by keeping things simple
That’s really the main purpose of this indicator: simplicity of statistics for confluence using volume
Volume precedes price and price moves only for narrative to follow- why wait for your subjective Twitter timeline to give you a biased narrative to trade when you can use objective analysis by combining statistics and colors to allow for a cleaner execution process
“But what about risk management?” Glad you didn’t ask reader!
One last example then, we meet our trend following trader again feeling euphoric so they know profit taking season is coming soon but wants to leave emotion out of it. How to go about it? Same idea as our last trend following example: we see on the 4h chart to the right side shows Bitcoin lose and trade back within the 2nd standard deviation of quarterly VWAP which is telling our speculator that the uptrend has broken on top of which notices on the 30 minute chart on the left that aggressive market buyers have been steadily absorbed by limit sellers on multiple occasions of retesting 30,500 shown with the green colored candles and volume bars below, time to sell.
Turns out that selling was proactive risk management because price dumped thereafter
Hope this explanation gave you some useful insights on using statistics as colors from cherrypicked examples, remember that just because my examples are cherrypicked doesn’t invalidate these concepts at all as the market only does two things, initiate aggressive auctions and respond passively to auctions. This tool makes for seeing where that initiative aggressive activity is happening much simpler to deduce if others will respond to an anomaly of initiative aggressive activity or if the aggression will continue.
If there’s just one thing you take from this- simplicity above all, cheers and good luck
ICT Concepts [LuxAlgo]The ICT Concepts indicator regroups core concepts highlighted by trader and educator "The Inner Circle Trader" (ICT) into an all-in-one toolkit. Features include Market Structure (MSS & BOS), Order Blocks, Imbalances, Buyside/Sellside Liquidity, Displacements, ICT Killzones, and New Week/Day Opening Gaps.
🔶 SETTINGS
🔹 Mode
When Present is selected, only data of the latest 500 bars are used/visualized, except for NWOG/NDOG
🔹 Market Structure
Enable/disable Market Structure.
Length: will set the lookback period/sensitivity.
In Present Mode only the latest Market Structure trend will be shown, while in Historical Mode, previous trends will be shown as well:
You can toggle MSS/BOS separately and change the colors:
🔹 Displacement
Enable/disable Displacement.
🔹 Volume Imbalance
Enable/disable Volume Imbalance.
# Visible VI's: sets the amount of visible Volume Imbalances (max 100), color setting is placed at the side.
🔹 Order Blocks
Enable/disable Order Blocks.
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Color settings.
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
Change in Order Blocks style:
🔹 Liquidity
Enable/disable Liquidity.
Margin: sets the sensitivity, 2 points are fairly equal when:
'point 1' < 'point 2' + (10 bar Average True Range / (10 / margin)) and
'point 1' > 'point 2' - (10 bar Average True Range / (10 / margin))
# Visible Liq. boxes: sets the amount of visible Liquidity boxes (max 50), this amount is for Sellside and Buyside boxes separately.
Colour settings.
Change in Liquidity style:
🔹 Fair Value Gaps
Enable/disable FVG's.
Balance Price Range: this is the overlap of latest bullish and bearish Fair Value Gaps.
By disabling Balance Price Range only FVGs will be shown.
Options: Choose whether you wish to see FVG or Implied Fair Value Gaps (this will impact Balance Price Range as well)
# Visible FVG's: sets the amount of visible FVG's (max 20, in the same direction).
Color settings.
Change in FVG style:
🔹 NWOG/NDOG
Enable/disable NWOG; color settings; amount of NWOG shown (max 50).
Enable/disable NDOG ; color settings; amount of NDOG shown (max 50).
🔹 Fibonacci
This tool connects the 2 most recent bullish/bearish (if applicable) features of your choice, provided they are enabled.
3 examples (FVG, BPR, OB):
Extend lines -> Enabled (example OB):
🔹 Killzones
Enable/disable all or the ones you need.
Time settings are coded in the corresponding time zones.
🔶 USAGE
By default, the indicator displays each feature relevant to the most recent price variations in order to avoid clutter on the chart & to provide a very similar experience to how a user would contruct ICT Concepts by hand.
Users can use the historical mode in the settings to see historical market structure/imbalances. The ICT Concepts indicator has various use cases, below we outline many examples of how a trader could find usage of the features together.
In the above image we can see price took out Sellside liquidity, filled two bearish FVGs, a market structure shift, which then led to a clean retest of a bullish FVG as a clean setup to target the order block above.
Price then fills the OB which creates a breaker level as seen in yellow.
Broken OBs can be useful for a trader using the ICT Concepts indicator as it marks a level where orders have now been filled, indicating a solidified level that has proved itself as an area of liquidity. In the image above we can see a trade setup using a broken bearish OB as a potential entry level.
We can see the New Week Opening Gap (NWOG) above was an optimal level to target considering price may tend to fill / react off of these levels according to ICT.
In the next image above, we have another example of various use cases where the ICT Concepts indicator hypothetically allow traders to find key levels & find optimal entry points using market structure.
In the image above we can see a bearish Market Structure Shift (MSS) is confirmed, indicating a potential trade setup for targeting the Balanced Price Range imbalance (BPR) below with a stop loss above the buyside liquidity.
Although what we are demonstrating here is a hindsight example, it shows the potential usage this toolkit gives you for creating trading plans based on ICT Concepts.
Same chart but playing out the history further we can see directly after price came down to the Sellside liquidity & swept below it...
Then by enabling IFVGs in the settings, we can see the IFVG retests alongside the Sellside & Buyside liquidity acting in confluence.
Which allows us to see a great bullish structure in the market with various key levels for potential entries.
Here we can see a potential bullish setup as price has taken out a previous Sellside liquidity zone and is now retesting a NWOG + Volume Imbalance.
Users also have the option to display Fibonacci retracements based on market structure, order blocks, and imbalance areas, which can help place limit/stop orders more effectively as well as finding optimal points of interest beyond what the primary ICT Concepts features can generate for a trader.
In the above image we can see the Fibonacci extension was selected to be based on the NWOG giving us some upside levels above the buyside liquidity.
🔶 DETAILS
Each feature within the ICT Concepts indicator is described in the sub sections below.
🔹 Market Structure
Market structure labels are constructed from price breaking a prior swing point. This allows a user to determine the current market trend based on the price action.
There are two types of Market Structure labels included:
Market Structure Shift (MSS)
Break Of Structure (BOS)
A MSS occurs when price breaks a swing low in an uptrend or a swing high in a downtrend, highlighting a potential reversal. This is often labeled as "CHoCH", but ICT specifies it as MSS.
On the other hand, BOS labels occur when price breaks a swing high in an uptrend or a swing low in a downtrend. The occurrence of these particular swing points is caused by retracements (inducements) that highlights liquidity hunting in lower timeframes.
🔹 Order Blocks
More significant market participants (institutions) with the ability of placing large orders in the market will generally place a sequence of individual trades spread out in time. This is referred as executing what is called a "meta-order".
Order blocks highlight the area where potential meta-orders are executed. Bullish order blocks are located near local bottoms in an uptrend while bearish order blocks are located near local tops in a downtrend.
When price mitigates (breaks out) an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
🔹 Buyside & Sellside Liquidity
Buyside / Sellside liquidity levels highlight price levels where market participants might place limit/stop orders.
Buyside liquidity levels will regroup the stoploss orders of short traders as well as limit orders of long traders, while Sellside liquidity levels will regroup the stoploss orders of long traders as well as limit orders of short traders.
These levels can play different roles. More informed market participants might view these levels as source of liquidity, and once liquidity over a specific level is reduced it will be found in another area.
🔹 Imbalances
Imbalances highlight disparities between the bid/ask, these can also be defined as inefficiencies, which would suggest that not all available information is reflected by the price and would as such provide potential trading opportunities.
It is common for price to "rebalance" and seek to come back to a previous imbalance area.
ICT highlights multiple imbalance formations:
Fair Value Gaps: A three candle formation where the candle shadows adjacent to the central candle do not overlap, this highlights a gap area.
Implied Fair Value Gaps: Unlike the fair value gap the implied fair value gap has candle shadows adjacent to the central candle overlapping. The gap area is constructed from the average between the respective shadow and the nearest extremity of their candle body.
Balanced Price Range: Balanced price ranges occur when a fair value gap overlaps a previous fair value gap, with the overlapping area resulting in the imbalance area.
Volume Imbalance: Volume imbalances highlight gaps between the opening price and closing price with existing trading activity (the low/high overlap the previous high/low).
Opening Gap: Unlike volume imbalances opening gaps highlight areas with no trading activity. The low/high does not reach previous high/low, highlighting a "void" area.
🔹 Displacement
Displacements are scenarios where price forms successive candles of the same sentiment (bullish/bearish) with large bodies and short shadows.
These can more technically be identified by positive auto correlation (a close to open change is more likely to be followed by a change of the same sign) as well as volatility clustering (large changes are followed by large changes).
Displacements can be the cause for the formation of imbalances as well as market structure, these can be caused by the full execution of a meta order.
🔹 Kill Zones
Killzones represent different time intervals that aims at offering optimal trade entries. Killzones include:
- New York Killzone (7:9 ET)
- London Open Killzone (2:5 ET)
- London Close Killzone (10:12 ET)
- Asian Killzone (20:00 ET)
🔶 Conclusion & Supplementary Material
This script aims to emulate how a trader would draw each of the covered features on their chart in the most precise representation to how it's actually taught by ICT directly.
There are many parallels between ICT Concepts and Smart Money Concepts that we released in 2022 which has a more general & simpler usage:
ICT Concepts, however, is more specifically aligned toward the community's interpretation of how to analyze price 'based on ICT', rather than displaying features to have a more classic interpretation for a technical analyst.
Weis V5 zigzag jayySomehow, I deleted version 5 of the zigzag script. Same name. I have added some older notes describing how the Weis Wave works.
I have also changed the date restriction that stopped the script from working after Dec 31, 2022.
What you see here is the Weis zigzag wave plotted directly on the price chart. This script is the companion to the Weis cumulative wave volume script.
What is a Weis wave? David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now-popular Weis wave. The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength. Chief among the characteristics of strength is the cumulative volume of the wave. There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish. Weis also uses time, particularly when using a Renko chart
David Weis did a futures io video which is a popular source of information about his method. (Search David Weis and futures.io. I strongly suggest you also read “Trades About to Happen” by David Weis.
This will get you up and running more quickly when studying charts. However, you should choose the Traditional method to be true to David Weis technique as described in his book "Trades About to Happen" and in the Futures IO Webcast featuring David Weis
. The Weis pip zigzag wave shows how far in terms of bar close price a Weis wave has traveled through the duration of a Weis wave. The Weis zigzag wave is used in combination with the Weis cumulative volume wave. The two waves should be set to the same "wave size".
To use this script, you must set the wave size: Using the traditional Weis method simply enter the desired wave size in the box "How should wave size be calculated", in this example I am using a traditional wave size of .25. Each wave for each security and each timeframe requires its own wave size. Although not the traditional method devised by David Weis a more automatic way to set wave size would be to use Average True Range (ATR). Using ATR is not the true Weis method but it does give you similar waves and, importantly, without the hassle described above. Once the Weis wave size is set then the zigzag wave will be shown with volume. Because Weis used the closing price of a wave to define waves a line Bar highs and bar lows are not captured by the Weis Wave. The default script setting is now cumulative volume waves using an ATR of 7 and a multiplication factor of .5.
To display volume in a way that does not crowd out neighbouring volumes Weis displayed volume as a maximum of 3 digits (usually). Consider two Weis Wave volumes 176,895,570 and 2,654,763,889. To display wave volume as three digits it is necessary to take a number such as 176,895,570 and truncate it. 176,895,570 can be represented as 177 X 10 to the power of 6. The number displayed must also be relative to other numbers in the field. If the highest volume on the page is: 2,654,763,889 and with only three numbers available to display the result the value shown must be 265 (265 X 10 to the power of 7). Since 176,895,570 is an order of magnitude smaller than 2,654,763,889 therefore 175,895,570 must be shown as 18 instead of 177. In this way, the relative magnitudes of the two volumes can be understood. All numbers in the field of view must be truncated by the same order of magnitude to make the relative volumes understandable. The script attempts to calculate the order of magnitude value automatically. If you see a red number in the field of view it means the script has failed to do the calculation automatically and you should use the manual method – use the dialogue box “Calculate truncated wave value automatically or manually”. Scroll down from the automatic method and select manual. Once "manual" is selected the values displayed become the power values or multipliers for each wave.
Using the manual method you will select a “Multiplier” in the next dialogue box. Scan the field and select the largest value in the field of view (visible chart) is the multiplier of interest. If you select a lower number than the maximum value will see at least one red “up”. If you are too high you will see at least one red “down”. Scroll in the direction recommended or the values on the screen will be totally incorrect. With volume truncated to the highest order values, the eye can quickly get a feel for relative volumes. It also reduces the crowding and overlapping of values on the screen. You can opt to show the full volume to help get a sense of the magnitude of the true volumes.
How does the script determine if a Weis wave is continuing to grow or not?
The script evaluates the closing price of each new bar relative to the "Weis wave size". Suppose the current bar closes at a new low close, within the current down wave, at $30.00. If the Weis wave size is $0.10 then the algorithm will remember the $30.00 close and compare it to the close of the next bar. If the bar close price does not close equal to or lower than $30.00 or close equal to or higher than $30.10 then the wave is still a down wave with a current low of $30.00. This is true even if the bar low is less than $30.00 or the bar high is greater than 30.10 – only the bar’s closing price matters. If a bar's closing price climbs back up to a close of $30.11 then because the closing price has moved more than $0.10 (the Weis wave size) then that is a wave reversal with a new up-trending wave. In the above example if there was currently a downward trending wave and the bar closes were as follows $30.00, $30.09, $30.01, $30.05, $30.10 The wave direction would continue to stay downward trending until the close of $30.10 was achieved. As such $30.00 would be the low and the following closes $30.09, $30.01, $30.05 would be allocated to the new upward-trending wave. If however There was a series of bar closes like this $30.00, $30.09, $30.01, $30.05, $29.99 since none of the closes was equal to above the 10-cent reversal target of $30.10 but instead, a new Weis wave low was achieved ($29.99). As such the closes of $30.09, $30.01, $30.05 would all be attributed to the continued down-trending wave with a current low of $29.99, even though the closing price for the interim bars was above $30.00. Now that the Weis Wave low is now 429.99 then, in order to reverse this continued downtrend price will need to close at or above $30.09 on subsequent bar closes assuming now new low bar close is achieved. With large wave sizes, wave direction can be in limbo for many bars before a close either renews wave direction or reverses it and confirms wave direction as either a reversal or a continuation. On the zig-zag, a wave line and its volume will not be "printed" until a wave reversal is confirmed.
The wave attribution is similar when using other methods to define wave size. If ATR is used for wave size instead of a traditional wave constant size such as $0.10 or $2 or 2000 pips or ... then the wave size is calculated based on current ATR instead of the Weis wave constant (Traditional selected value).
I have the option to display pseudo-Ord volume. In truth, Ord used more traditional zig-zag pivots of bar highs and lows. Waves using closes as pivots can have some significant differences. This difference can be lessened by using smaller time frames and larger wave sizes.
There are other options such to display the delta price or pip size of a Weis Wave, the number of bars in a wave, and a few other options.
Trail Blaze - (Multi Function Trailing Stop Loss) - [mutantdog]Shorter version:
As the title states, this is a 'Trailing Stop' type indicator, albeit one with a whole bunch of additional functionality, making it far more versatile and customisable than a standard trailing stop.
The main set of features includes:
Three independent trailing types each with their own +/- multipliers:
- Standard % change
- ATR (aka Supertrend)
- IQR (inter-quartile range)
These can be used in isolation or summed together. A subsequent pair of direction specific multipliers are also included.
Two separate custom source inputs are available, both feature the standard options alongside a selection of 'weighted inputs' and the option to use another indicator (selected via 'AUX'):
- 'Centre' determines the value about which the trailing sum will be added to define the stop level.
- 'Trigger' determines the value used for crossing of stops, initiating trend changes and triggering alerts.
A selection of optional filters and moving averages are available for both.
Furthermore there are various useful visualisation options available, including the underlying bands that govern the stop levels. Preset alerts for trend reversals are also included.
This is not really an 'out-of-the-box' indicator. Depending upon the market and timeframe some adjustments will be necessary for it to function in a useful manner, these can be as simple or complex as the feature-set allows. Basic settings are easy to dial in however and the default state is intended as a good starting point. Alternatively with some experimentation, a plethora of unique and creative configurations are possible, making this a great tool for tweaking. Below is a more detailed overview followed by a bunch of simple example settings.
------------------------
Lengthy Version :
DESIGN & CONCEPT
Before we start breaking this down, a little background. This started off as an attempt to improve upon the ever-popular Supertrend indicator. Of course there are many excellent user created variants available utilising some interesting methods to overcome the drawbacks of the basic version. To that end, rather than copying the work of others, the direction here shifted towards a hybrid trailing stop loss with a bunch of additional user customisation options. At some point, a completely different project involving IQR got morphed into this one. After sitting through months of sideways chop (where this proved to be of limited use), at the time of publication the market has began to form some near term trend direction and it appears to be performing well in many different timeframes.
And so with that out of the way...
INPUTS
The standard Supertrend (and most other variants) includes a single source input, as default set to 'hl2' (candle mid-range). This is the centre around which the atr bands are added/subtracted to govern the stop levels. This is not however the value which is used to trigger the trend reversal, that is usually hard-coded to 'close'. For this version both source values are adjustable: labelled 'centre' and 'trigger' respectively.
Each has custom input selectors including the usual options, a selection of 'weighted inputs' and the option to use another indicator (selected from the Aux input). The 'weighted inputs' are those introduced in Weight Gain 4000, for more details please refer to that listing. These should be treated as experimental, however may prove useful in certain configurations. In this case 'hl-oc2' can be considered an estimate of the candle median and may be a good alternative to the default 'centre' setting of 'hl2', in contrast 'cc-ohlc4' can tend to favour the extremes in the trend direction so could be useful as a faster 'trigger' than the default 'close'.
To cap them off both come with a selection of moving average filters (SMA, EMA, WMA, RMA, HMA, VWMA and a simple VWEMA - note: not elastic) aswell as median and mid-range. 'Centre' can also be set to the output of 'trigger' post-filter which can be useful if working with fast/slow crosses as the basis.
DYNAMICS
This is the main section, comprised of three separate factors: 'TSL', 'ATR' and 'IQR'. The first two should be fairly obvious, 'TSL' (trailing stop loss) is simply a percentage of the 'centre' value while 'ATR' (average true range) is the standard RMA-based version as used in Supertrend, Volatility Stop etc.
The third factor is less common however: 'IQR' (inter-quartile range). In case you are unfamiliar the principle here is, for a given dataset, the greatest 25% and smallest 25% of samples are removed. The remainder is then treated as a set and the range is calculated by highest - lowest. This is a commonly used method in statistical analysis, by removing the extremes it is less prone to influence by outliers and gives a good representation of the main dispersion around the median. In practise i have found it can be a good alternative to ATR, translating better across multiple time-frames due to it representing a fraction of the total range rather than an average of per-candle range like ATR. Used in combination with the others it can also add a factor more representative of longer-term/higher-timeframe trend. By discarding outliers it also benefits from not being impacted by brief pumps/volatility, instead responding only to more sustained changes in trend, such as rallies and parabolic moves. In order to give an accurate result the IQR is calculated using a dataset of high, low and hlcc4 values for all bars within the lookback length. Once calculated this value is then halved which, strictly speaking, makes it a semi-interquartile range.
All three of these components can be used individually or summed together to create a hybrid dynamics factor. Furthermore each multiplier can be set to both positive and negative values allowing for some interesting and creative possibilities. An optional smoothing filter can be applied to the sum, this is a basic SWMA-4 which is can reduce the impact of sudden changes but does incur a noticeable lag. Finally, a basic limiter condition has been hard-coded here to prevent the sum total from ever going below zero.
Capping off this section is a pair of direction multipliers. These simply take the prior dynamics sum and allow for further multiplication applied only to one side (uptrend/lo-stop and downtrend/hi-stop). To see why this is useful consider that markets often behave differently in each direction, we've all seen prices steadily climb over several weeks and then abruptly dump in the process of a day or two, shorter time frames are no stranger to this either. A lack of downside liquidity, a panicked market, aggressive shorts. All these things contribute to significant differences in downward price action. This function allows for tighter stops in one direction compared to the other to reflect this imbalance.
VISUALISATIONS
With all of these options and possibilities, some visual aids are useful. Beneath the dynamics' section are several visual options including both sources post-filter and the actual 'bands' created by the dynamics. These are what govern the stop levels and seeing them in full can help to better understand what our various configurations actually do. We can even hide the stop levels altogether and just use the bands, making this a kind of expanded Keltner Channel. Here we can also find colour and opacity settings for everything we've discussed.
EXAMPLES
The obvious first example here is the standard %-change trailing stop loss which, from my experience, tends to be the best suited for lower time frames. Filtering should probably minimal here. In both charts here we use the default config for source inputs, the top is a standard bi-directional setup with 1.5% tsl while the bottom uses a 2.5% tsl with the histop multiplier reduced to 0 resulting in an uptrend only stoploss.
Shown here in grey is the standard Supertrend which uses 'hl2' as centre and 'close' as trigger, ATR(10) multiplied by 3. On top we have the default filtered source config with ATR(8) multiplied by 2 which gives a different yet functionally similar result, below is the same source config instead using IQR(12) multiplied by 2. Notice here the more 'stepped' response from IQR following the central rally, holding back for a while before closing in on price and ultimately initiating reversal much sooner. Unlike ATR, the length parameter for IQR is absolute and can more significantly affect its responsiveness.
Next we focus on the visualisation options, on top we have the default source config with ATR(8) multiplied by 2 and IQR(12) multiplied by 1. Here we have activated the switch to show 'bands', from this we can see the actual summed dynamics and how it influences the stop levels. Below that we have an altogether different config utilising the included filters which are now visible. In this example we have created a basic 8/21 EMA cross and set a 1% TSL, notice the brief fakeout in the middle which ordinarily might indicate a buy signal. Here the TSL functions as an additional requirement which in this case is not met and thus no buy signal is given.
Finally we have a couple of more 'experimental' examples. On top we have Lazybear's 'Variable Moving Average' in white which has been assigned via 'aux' as the centre with no additional filtering, the default config for trigger is used here and a basic TSL of 1.5% added. It's a simple example but it shows how this can be applied to other indicators. At the bottom we return to the default source config, combining a TSL of 8% with IQR(24) multiplied by -2. Note here the negative IQR with greater length which causes the stop to close in on price following significant deviations while otherwise remaining fairly wide. Combining positive and negative multiples of each factor can yield mixed results, some more useful than others depending upon suitable market conditions.
Since this has been quite lengthy, i shall leave it there. Suffice to say that there are plenty more ways to use this besides these examples. Please feel free to share any of your own ideas in the comments below. Enjoy.
ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
Quickfingers Luc base scanner - version 2This is my second implementation of a Pine Script Quickfingers Luc (QFL) base scanner that I have published on Trading View. QFL base scanners seek to provide buy signals according to the QFL trading strategy. To profitably trade using this script you should be familiar with the QFL trading strategy, scaling in and out of positions, and money risk management.
Background
All the QFL base identification Pine Scripts that I have inspected to date use a simple candlestick pattern of two lower lows followed by two higher lows to identify a base. Some scripts may combine this with a volume indicator as well. In practice, I found the results of this approach to be somewhat unreliable. The candlestick pattern may identify some significant bases, may identify minor bases (that should not be traded), but at the same time miss other significant bases entirely!
My first QFL base scanner sought to use Pine Script’s built in ta.lowest and ta.highest functions to identify bases and peaks. This approach depended on the time period selected to find the lowest lows and highest highs. This approach can be problematic because significant bases may be formed outside the nominated time period, leading to the identification of minor bases within the time period. I have left the first version of my QFL base scanning script in the Trading View indicators because it uses a different approach to this script that other people may still find useful.
My second version of the QFL base scanner does not use the Pine Script ta.lowest and ta.highest functions, and therefore does not rely on nominating a time period to look back through data.
User inputs
This script steps through the price data to find the following patterns that are used to confirm bases and peaks.
Base – bounce of x% above previous base confirms that base
Peak – fall of y% below previous peak confirms that peak
Buy signal – fall of z% below the base signals a buy signal.
x%, y% and z% are user configurable through the script settings. Small percentages will provide more, but riskier, buy signals; larger percentages will provide fewer, but safer, buy signals.
The script identifies QFL bases and buy signals and marks them on the price chart. These are able to be turned on and off in the script settings. The settings also allow the user to turn on plots for peaks, lowest lows and highest highs. These are not useful for applying the QFL trading strategy, but are calculations used in finding bases and can be useful for the user to understand what the script is doing in the background.
Troubleshooting
If looking at the past script results, you may think that the script is perfectly timing entry points at the bottom of market dips. This is NOT the case. The script is actually showing buy signals when the price falls z% below the PREVIOUS base. The current base is only retrospectively marked some periods later once the reversal is confirmed – a solid line marks a confirmed base in real time; a dotted line retrospectively repaints the line to the actual base. New bases are not tradeable using this script, but a percentage fall from the previous base is – this is the QFL trading strategy.
Pine Script may flag that this script has a repainting issue. Pine Script defines repainting as, “script behavior causing historical vs realtime calculations or plots to behave differently.” In the case of this script, bases are confirmed once the price has bounced x% off the low. The script then repaints a dotted line from the base that has been identified in real time (with a solid line) back to the point in the price data where the base actually occurs. The dotted line only aids in visual identification of the base, and does not impact on the real time identification of bases. A similar repainting issue occurs for identifying peaks. I have identified the lines in the script that cause this repainting. These lines can be commented out without affecting the buy signals generated by the script, but you will also lose the visual pinpointing of historical bases and peaks.
The user may find price charts where they think that the script has not correctly identified a base or peak. Usually, careful measurement will reveal that the price chart has not confirmed a base or peak by moving x% or y% from the previous base or peak respectively.
And before you ask, yes, Trading View alerts work with this script.
Enjoy.
MarketStructureLibrary "MarketStructure"
This library contains functions for identifying Lows and Highs in a rule-based way, and deriving useful information from them.
f_simpleLowHigh()
This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
It doesn't have to be "the" high, so don't be confused.
By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs.
Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for stops, I want them all, not just the ones that alternate in strict order.
@param - there are no parameters. The function uses the chart OHLC.
@returns boolean values for whether this bar confirms a Simple Low/High, and ints for the bar_index of that Low/High.
f_localLowHigh()
This function finds Local Lows and Highs, in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
By the rules, Local Lows and Highs must alternate, and in this function they do.
@param - there are no parameters. The function uses the chart OHLC.
@returns boolean values for whether this bar confirms a Local Low/High, and ints for the bar_index of that Low/High.
f_enhancedSimpleLowHigh()
This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs.
Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for trailing stops, I want them all, not just the ones that alternate in strict order.
The difference between this function and f_simpleLowHigh() is that it also tracks the lowest/highest recent level. This level can be useful for trailing stops.
In effect, these are like more "normal" highs and lows that you would pick by eye, but confirmed faster in many cases than by waiting for the low/high of that particular candle to be taken out on close,
because they are instead confirmed by ANY subsequent candle having its low/high exceeded. Hence, I call these Enhanced Simple Lows/Highs.
The levels are taken from the extreme highs/lows, but the bar indexes are given for the candles that were actually used to confirm the Low/High.
This is by design, because it might be misleading to label the extreme, since we didn't use that candle to confirm the Low/High..
@param - there are no parameters. The function uses the chart OHLC.
@returns - boolean values for whether this bar confirms an Enhanced Simple Low/High
ints for the bar_index of that Low/High
floats for the values of the recent high/low levels
floats for the trailing high/low levels (for debug/post-processing)
bools for market structure bias
f_trueLowHigh()
This function finds True Lows and Highs.
A True High is the candle with the highest recent high, which then has its low taken out on close by a subsequent candle (and vice-versa for True Lows).
The difference between this and an Enhanced High is that confirmation requires not just any Simple High, but confirmation of the very candle that has the highest high.
Because of this, confirmation is often later, and multiple Simple Highs and Lows can develop within ranges formed by a single big candle without any of them being confirmed. This is by design.
A True High looks like the intuitive "real high" when you look at the chart. True Lows and Highs must alternate.
@param - there are no parameters. The function uses the chart OHLC.
@returns - boolean values for whether this bar confirms an Enhanced Simple Low/High
ints for the bar_index of that Low/High
floats for the values of the recent high/low levels
floats for the trailing high/low levels (for debug/post-processing)
bools for market structure bias
Interactive SAR Stop-Loss [TANHEF]This indicator is "Interactive" which means some inputs can are manually added through the first click after adding the indicator to the chart (SAR Trailing Stop-loss start point).
Unlike the normal Parabolic SAR, this indicator allows for the modification of the start point of the Parabolic SAR’s first bar calculation. Normally, the Parabolic SAR automatically has a start point after the first bar of an asset’s historical price that will then switch between trailing above and below price respectively. It must be noted that due to how the first position of the Parabolic SAR is calculated, on occasion the Parabolic SAR will immediately flip on the next bar to the opposite side relative to price that it was just located. Modifying the setting “⭐Initial Interactive SAR Position Source”, then selecting either 'Clicked' or 'ATR' level as the vertical start position will prevent this. See images below for more explanation.
Why use a trailing stop-loss?
A trailing stop-loss provides an exit when price moves against you but also enables you to move the exit point further into profit when price is moving in the desired direction of a trade. The Parabolic SAR ( stop and reverse ) which is used to determine price direction as well as when price direction is changing, is very effective at functioning as a trailing stop loss.
Indicator Explanation
Initially when this indicator is added to the chart, you will be prompted to select where to begin the SAR Trailing Stop-loss.
For a long stop-loss, select below price.
For a short stop-loss, select above price.
After this indicator is placed, it can be modified via dragging or from within the settings by modifying the time and the price input. Or simply re-add the indicator to the chart. Another option is to have this Parabolic SAR begin directly on the price that was initially ‘Clicked’ or the ‘ATR’ level, which requires selecting the option in settings labeled “⭐Initial Interactive SAR Position Source”
The SAR Stop Loss plotted. Note that the calculation that occurs on this first bar of the ‘Interactive SAR’ is as if the prior bar was the oldest historical bar of the asset. Due to the SAR’s calculations, if the ‘Normal SAR’ were to also flip sides over to the position that has been manually set for the ‘Interactive SAR’, they won’t necessarily have the same result.
An optional fixed profit target can be added within the settings. This profit target will only actively be plotted when the SAR Trailing Stop-loss has not be hit yet or until the profit target has been hit.
Here shows that the profit target was hit, then later on the SAR Trailing Stop-loss was hit.
Note, trailing stop-loss will continue to be plotted until it has been hit regardless of the profit target being hit or not.
Here is an example of when the Parabolic SAR will immediately flip on the next bar to the opposite side relative to price that it was just first located. This is due to how the Parabolic SAR is calculated and will also occur with the traditional Parabolic SAR that is not interactively (manually) given a start location. To prevent this, either relocate this time in which this SAR beings or consider modifying the SAR’s (start, increment, max) settings specifically.
Here instead of using the SAR’s calculation for an initial bar, the ‘ATR’ was selected as the start point within the setting “⭐Initial Interactive SAR Position Source”.
Alerts
1. 'Check' alerts to use within indicator settings (trailing stop hit and/or profit target hit).
2. Select 'Create Alert'
3. Set the condition to 'Interactive SAR''
4. Select create.
MTF CCI + Realtime DivergencesMulti-timeframe Commodity Channel Index (CCI) + Realtime Divergences + Alerts
This version of the CCI includes the following features:
- Optional 2x sets of triple-timeframe overbought and oversold signals with fully configurable timeframes and overbought and oversold thresholds, can indicate where 3 selected timeframes are all overbought or all oversold at the same time, with alert option.
- Optional divergence lines drawn directly onto the oscillator in realtime, with alert options.
- Configurable pivot periods to fine tune the divergences drawn in order to suit different trading styles and timeframes, including the ability to enable automatic adjustment of pivot period per chart timeframe.
- Alternate timeframe feature allows you to configure the oscillator to use data from a different timeframe than the chart it is loaded on.
- 'Hide oscillator' feature allows traders to hide the oscillator itself, leaving only the background colours indicating the overbought and oversold periods and/or MTF overbought and oversold confluences, as seen in the chart image.
- Also includes standard configurable CCI options, including CCI length and source type. Defaults set to length 20, and hlc3 source type.
- Optional Flip oscillator feature, allows users to flip the oscillator upside down, for use with Tradingviews 'Flip chart' feature (Alt+i), for the purpose of manually spotting divergences, where the trader has a strong natural bias in one direction, so that they can flip both the chart and the oscillator.
- Optional 'Fade oscillator' feature, which will fade out all but the most recent period, reducing visual noise on the chart.
While this version of the CCI has the ability to draw divergences in realtime along with related alerts so you can be notified as divergences occur without spending all day watching the charts, the main purpose of this indicator was to provide the triple-timeframe overbought and oversold confluence signals, in an attempt to add more confluence, weight and reliability to the single timeframe overbought and oversold states, commonly used for trade entry confluence. It's primary purpose is intended for scalping reversal trades on lower timeframes, typically between 1-15 minutes, which can be used in conjunction with the regular divergences the indicator can highlight. The triple timeframe overbought can often indicate near term reversals to the downside, with the triple timeframe oversold often indicating neartime reversals to the upside. The default timeframes for this confluence are set to check the 1m, 5m and 15m timeframes together, ideal for scalping the < 15 minute charts. The default settings for the MTF #1 timeframes (1m, 5m and 15m) are best used on a <5 minute chart.
Its design and use case is based upon the original MTF Stoch RSI + Realtime Divergences found here .
Commodity Channel Index (CCI)
Investopedia has described the popular oscillator as follows:
“The Commodity Channel Index (CCI) is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold.
Developed by Donald Lambert, this technical indicator assesses price trend direction and strength, allowing traders to determine if they want to enter or exit a trade, refrain from taking a trade, or add to an existing position. In this way, the indicator can be used to provide trade signals when it acts in a certain way.”
You can read more about the CCI, its use cases and calculations here .
How do traders use overbought and oversold levels in their trading?
The oversold level, that is traditionally when the CCI is above the 100 level is typically interpreted as being 'overbought', and below the -100 level is typically considered 'oversold'. Traders will often use the CCI at an overbought level as a confluence for entry into a short position, and the CCI at an oversold level as a confluence for an entry into a long position. These levels do not mean that price will necessarily reverse at those levels in a reliable way, however. This is why this version of the CCI employs the triple timeframe overbought and oversold confluence, in an attempt to add a more confluence and reliability to this usage of the CCI. While traditionally, the overbought and oversold levels are below -100 for oversold, and above 100 for overbought, he default threshold settings of this indicator have been increased to provide fewer, stronger signals, especially suited to the low timeframes and highly volatile assets.
What are divergences?
Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
There are 4 main types of divergence, which are split into 2 categories;
regular divergences and hidden divergences. Regular divergences indicate possible trend reversals, and hidden divergences indicate possible trend continuation.
Regular bullish divergence: An indication of a potential trend reversal, from the current downtrend, to an uptrend.
Regular bearish divergence: An indication of a potential trend reversal, from the current uptrend, to a downtrend.
Hidden bullish divergence: An indication of a potential uptrend continuation.
Hidden bearish divergence: An indication of a potential downtrend continuation.
How do traders use divergences in their trading?
A divergence is considered a leading indicator in technical analysis , meaning it has the ability to indicate a potential price move in the short term future.
Hidden bullish and hidden bearish divergences, which indicate a potential continuation of the current trend are sometimes considered a good place for traders to begin, since trend continuation occurs more frequently than reversals, or trend changes.
When trading regular bullish divergences and regular bearish divergences, which are indications of a trend reversal, the probability of it doing so may increase when these occur at a strong support or resistance level . A common mistake new traders make is to get into a regular divergence trade too early, assuming it will immediately reverse, but these can continue to form for some time before the trend eventually changes, by using forms of support or resistance as an added confluence, such as when price reaches a moving average, the success rate when trading these patterns may increase.
Typically, traders will manually draw lines across the swing highs and swing lows of both the price chart and the oscillator to see whether they appear to present a divergence, this indicator will draw them for you, quickly and clearly, and can notify you when they occur.
Setting alerts.
With this indicator you can set alerts to notify you when any/all of the above types of divergences occur, on any chart timeframe you choose, and also when the triple timeframe overbought and oversold confluences occur.
Configurable pivot period.
You can adjust the default pivot period values to suit your prefered trading style and timeframe. If you like to trade a shorter time frame, lowering the default lookback values will make the divergences drawn more sensitive to short term price action. By default, this indicator has enabled the automatic adjustment of the pivot periods for 4 configurable timeframes, in a bid to optimise the divergences drawn when the indicator is loaded onto any of the 4 timeframes. These timeframes and the auto adjusted pivot periods on each of them can also be reconfigured within the settings menu.
Disclaimer: This script includes code adapted from the Divergence for Many Indicators v4 by LonesomeTheBlue . With special thanks.
