Hedge Coin M - Statistical Support and ResistanceHedge Coin M - Statistical Support and Resistance
Introduction
"Hedge Coin M - Statistical Support and Resistance" is a sophisticated, statistically-driven indicator designed specifically for traders in the COIN-M market on Binance. It offers a nuanced approach to identifying key market levels, focusing on the dynamics of support and resistance through advanced volatility analysis.
Foundation and Credits:
This script is an advanced adaptation of TradingView's standard code for the Bollinger Bands indicator. It extends the foundational concept of Bollinger Bands by integrating additional volatility metrics.
Calculation Method
This indicator employs Volume Weighted Moving Averages (VWMA) to create two distinct sets of Bollinger Bands, named BB-a and BB-b.
BB-a is derived from the VWMA of high prices, targeting potential resistance levels.
BB-b is based on the VWMA of low prices, aimed at identifying critical support levels.
Users can independently adjust the standard deviation (SD) multipliers for the upper and lower bands of both BB-a and BB-b, accommodating different market conditions.
Enhanced Volatility Analysis
The indicator calculates additional standard deviation lines for the upper band of BB-a and the lower band of BB-b. These lines provide deeper insights into market volatility.
Plotted Graphs
The primary plots include the upper and lower bands of BB-a and BB-b, marked in distinct colors for clarity.
Additional SD lines are plotted to indicate potential extended levels of support and resistance, offering traders a broader view of possible market movements.
Purpose and Usage
"Hedge Coin M - Statistical Support and Resistance" is designed to provide traders with a consistent, statistical method for identifying significant price levels.
It aids in scaling entry into positions, helping traders to navigate the COIN-M market with more informed decision-making.
This tool is especially useful for traders who combine long-term holding with swing trading strategies, offering a balanced approach to market engagement.
Integration and Adaptation
Easily integrate this indicator into your TradingView chart for the COIN-M market.
Use the insights provided to complement your overall trading strategy, particularly in identifying and reacting to significant market movements.
Disclaimer
Important Note: This indicator is provided for informational purposes only. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. Trading decisions should be made based on your own analysis, prudence, and judgment. Please be aware of the risks involved in trading and consult a financial advisor if necessary.
Pesquisar nos scripts por "swing trading"
Minervini Stage 2 AnalysisHandbook for Minervini Stage 2 Analysis Indicator
Introduction
This handbook provides detailed instructions and guidelines for using the Minervini Stage 2 Analysis Indicator based on Mark Minervini's swing trading methodology. This indicator is designed for traders focusing on US stocks, aiming to capture gains in medium to short-term uptrends (swing trading).
Understanding Stage 2
Stage 2 represents a bullish uptrend in a stock's price. Mark Minervini emphasizes entering long positions during this phase. The stage is identified using four key criteria related to moving averages (MAs).
Indicator Criteria
Stock Price Above MA 150 and 200: Indicates an overall uptrend.
MA 150 Above MA 200: Signals a stronger medium-term trend compared to the long-term trend.
MA 200 Trending Up for At Least 1 Month (22 Days): Confirms a stable uptrend.
MA 50 Above Both MA 150 and 200: Shows short-term strength and momentum.
Using the Indicator
Entering Trades: Consider long positions when all four criteria are met. This signifies that the stock is in a Stage 2 uptrend.
Monitoring Trades: Regularly check if the stock continues to meet these criteria. The indicator provides a clear visual and textual representation for ease of monitoring.
Alarm Signals and Exit Strategy
One Criterion Not Met: This serves as an alarm signal. Increased vigilance is required, and traders should prepare for a potential exit.
Two Criteria Not Met: Strong indication to close the trade. This suggests the stock may be transitioning out of Stage 2, increasing the risk of holding the position.
Risk Management
Stop-Loss Orders: Consider setting a trailing stop-loss to protect profits and minimize losses.
Position Sizing: Adjust position sizes according to your risk tolerance and portfolio strategy.
Volume and Relative Strength Analysis
Volume Analysis: Look for increased trading volume as confirmation when the stock price moves above key MAs.
Relative Strength (RS) Rating: Compare the stock's performance to the broader market to gauge its strength.
Limitations and Considerations
Market Conditions: The indicator's effectiveness may vary with market conditions. It is more reliable in a bullish market environment.
Supplementary Analysis: Combine this indicator with other analysis methods (fundamental, technical) for a holistic approach.
Continuous Learning: Stay updated with market trends and adjust your strategy accordingly.
Conclusion
The Minervini Stage 2 Analysis Indicator is a powerful tool for identifying potential long positions in uptrending stocks. Its reliance on specific criteria aligns with Mark Minervini's proven swing trading strategy. However, always exercise due diligence and risk management in your trading decisions.
SwingConfidence ScoreSwingConfidence is a scoring system that helps us quantitatively manage risk & position size in swing trading.
SwingConfidence uses T3 moving average to determine the swing state in which the instrument is in. So, this is supposed to be used with my previously posted Simple Swing with T3MA indicator . The T3MA ribbon consists of a fast and a slow moving average (MA). The ribbon is green when the fast MA is above the slow MA. This green ribbon represents the upswing. Similarly, the red ribbon represents the downswing.
The score takes into account the swing state of 2 chosen benchmark indices (by default, these are NIFTY & CNXSMALLCAP). It has 2 components:
- Weekly Swing
- Daily Swing
Weekly Swing
The script uses the Simple Swing indicator on weekly charts of of 2 benchmark indices to determine whether the index is in a weekly upswing or downswing.
- If the color of the weekly ribbon is green, we are in a weekly Upswing.
- If the color of the weekly ribbon is red, we are in a weekly Downswing.
Daily Swing
The script uses the Simple Swing indicator on daily charts of 2 benchmark indices to determine the daily swing state. There can be any one of total 6 swing states on a daily chart:
- Early Upswing (close above red ribbon)
- Confirmed upswing (green ribbon)
- Upswing under strain (close inside green ribbon)
- Early Downswing (close below green ribbon)
- Confirmed downswing (red ribbon)
- Downswing under strain (close inside red ribbon)
SwingConfidence Scoring
The script prints the Weekly & Daily Swing states, & assigns a score to each index from 0 to 50, where 0 is the most bearish score, & 50 is the most bullish score. The sum of the scores is the final SwingConfidence score. e.g. If both indices are in a confirmed upswing, then the score reads 50 + 50 = 100.
How to use the SwingConfidence score?
There are multiple ways by which we can use the SwingConfidence score:
- If the SwingConfidence value is 100%, then we can go in with the maximum open risk our strategy allows. As the score starts decreasing, we keep on closing/modifying our positions, so as to keep the open risk proportionately down. Once the score reaches to zero, we must not be having any open risk. We can achieve this by either going in all-cash, or bringing the stop losses to breakeven.
- Another way is to use this is via a progressive exposure method. If the SwingConfidence value is 100%, then we go with full position size (e.g. 1% capital-at-risk). If the value is 0%, we sit out in cash. Between these 2 extremes, we reduce/increase our position size accordingly.
Please note that this script will display only on the daily timeframe.
ATR Range Accumulation by Standard Deviation and Volume [SS]So, this is an indicator/premise I have been experimenting with, which mixes ATR with Z-Score and Volume metrics.
What does the indicator do?
The indicator, on the lower timeframes, uses an ATR approach to determine short-term ranges. It takes the average ATR range over a designated lookback period and plots out the levels like so:
It then calculates the Z-Score for these ATR targets (shown in the chart above) and calculates, over the designated lookback period, how often price accumulates at that standard deviation level.
The indicator is essentially a hybrid of my Z-Score Support and Resistance indicator and my frequency distribution indicator. It combines both concepts into one.
You also have the option of sorting by volume accumulation. This will display the accumulation of the ranges by volume accumulation, like so:
Larger Timeframes:
If you want to see the accumulation by volume or standard deviation on the larger timeframes, you can. Simply toggle on your preferred setting:
Show Total Accumulation Breakdown:
This will break down the levels, over the lookback period, by standard deviation. This is similar to the Z-Score support and resistance indicator. It will then show you how often price accumulates at these various standard deviation levels. Here is an example on the daily timeframe using the 1D chart settings:
Inversely, you can repeat this, with the Z-Score levels, but show accumulation by volume. This will print 5 boxes, which are between +3 Standard Deviations and -3 Standard Deviations, like so:
Here we can see that 61% of volume accumulation is between -1 and 1 standard deviation.
Using it to Trade:
For swing trading, I suggest using the larger timeframe information. However, for both swing and day traders, it is also helpful to use the ATR display. You can modify the ATR display to show the levels on any timeframe by selecting which timeframe you would like to see ATR ranges for. If you are trading on the 1 or 5-minute chart, I suggest leaving the levels at no shorter than a 60-minute timeframe.
You can also use these levels on the daily for the weekly levels, etc.
The accumulation being shown will be based on the current chart timeframe. This is a function of Pinescript, but in this case, it's actually advantageous because if you are trading on the shorter timeframe, and a level has 0% recent accumulation, it's unlikely we will see that level soon or overly quickly. Intraday retracements will generally happen to areas of high accumulation.
How this indicator is different:
The difference in this indicator comes from its focus on accumulation in relation to Standard Deviation. There is one thing that is consistent among retail traders, algorithms, market makers, and funds, and that is looking at the market in terms of standard deviation. Each person, market maker, and algorithm may be slightly nuanced in how it conceptualizes standard deviation (whether it be since the inception of the ticker (or IPO), or the previous 500 days, or the previous 100 days, etc.), but the premise remains consistent. Standard Deviation is a really important, if not the most important, metric to pay attention to. Another important metric is volume. Thus, the premise is that combining volume accumulation with standard deviation should, theoretically, be telling. We can see the extent of buying at various standard deviations and whether a stock is really a buy or not.
And that's the indicator! Hope you enjoy it. Leave your comments and questions below.
Safe trades!
Momentum Candle
bar’s open price (open) from its close price (close). That gives the size of the bar’s body.
The difference between the open and closed is the candle’s body range.
The colour of a candle’s body shows the direction of prices.
if Close > Open then it's Bullish Body Candle & if close < open then it's Bearish Body Candle.
Stronger the interest of buyers or sellers is reflected in the formation of the Body of Candle.
When the body is indeed more than 50% bigger than the average size of a candle
then it will show Momentum on the chart.
we can see the Colour of the candle Changes When it is Stronger than the Average candle & Body size is Bigger than the Average Candle size.
Depending upon Bullish or Bearish the candle Colour Changes to Indicate the Strong Presence of the Buyer or Seller
The Candle which strong but not solid and above Average then it will show Normal Colour Of Candle and the Candle which is Below Average will have no colour on Volume Like Bars on the Chart & chart no effect on the candle colour.
Buyer or Seller's Activity is always reflected in Candle. This helps us to make Trade Decisions.
If Solid Candle at Support or Resistance give or add more Conviction. If Found At Support or resistance will act as Reversal. If found at Swing Low or Retracement, it will help to take trade accordingly with the main trend.
Solid Candle Helps in Good Risk to Reward. Mark the High and Low Of the Strong Candle and observe the Price Action.
as long as the candle is trading below average helps us to take action for Range Breakout & saves us from Taking Entry in Range.
The Distribution at the Top and consolidation at the Bottom can be Observed by the Behaviour of Candles on the Chart.
The candle is always a little first step of price action, Whatever Happens in the market is always first printed in a candle,
The Leader Candle or Momentum Candle with Follow always Decides the Trend.
It's Simple But useful in Day Trading as well as in Swing Trading or Positional Trading too
MTF Market Structure - SMC IndicatorsThe Multi Timeframe Market Structure helps understand and identify bullish or bearish Market Structure by highlighting “KEY” Highs and Lows. It also identifies changes in market direction by identifying a “Shift in Market Structure” (See Point 2 below) or “Break in Market Structure” (See Point 3 Below).
What are Key Highs and Lows?
Not every high or low is a “Key” high or low. “Key” highs and lows are specific highs and lows that form the structure of the market and have significance in understanding the current trend in the market (see point 1 below).
The indicator identifies these “Key” highs and lows on multiple time frames, allowing the trader to keep a perspective of the Market Structure with multiple timeframes simultaneously (see point 5 below).
The key highs and lows identified by the indicator are as follows:
Key Lows : Identify significant Swing Lows, Short-term lows “STL”, Intermediate-Term Lows “ITL”, and Long-Term Lows “LTL”.
Key Highs : Identify significant Swing Highs, Short-term highs “STH”, Intermediate-Term Highs “ITH”, and Long-Term Highs “LTH”.
Significant Swing High : This is a price swing with one lower candle to the right and one lower candle to the left of it.
Significant Swing Low : This is a price swing with one higher candle to the right and one higher candle to the left of it.
Short-Term High “STH” is a price swing with one lower Significant Swing High to the right and one lower Significant Swing High to the left of it.
Short-Term Low “STL” is a price swing with one higher Significant Swing Low to the right and one higher Significant Swing Low to the left of it.
Intermediate-Term High “ITH” is a price swing with one lower STH to the right and one lower STH to the left of it.
Intermediate-Term Low “ITL” is a price swing with one higher STL to the right and one higher STL to the left of it.
Long-Term High “LTH” is a price swing with one lower ITH to the right and one lower ITH to the left of it.
Long-Term Low “ITL” is a price swing with one higher ITL to the right and one higher ITL to the left of it.
By identifying key highs and lows using the Market Structure Indicator, it can be used in multiple ways by using those reference points as follows:
1. Identifying Market Trends by Connecting Key Highs and Lows.
Bullish trend identification is when the indicator is making higher ITLs and ITHs.
Bearish Trend identification when the indicator is making lower ITLs and ITHs.
PS: it’s essential to understand the underlying market trend on multiple timeframes to use the next features correctly. Always use the Shifts and Breaks in Market Structures in line with the 1H or higher timeframes Market Trend for higher probability trade opportunities. This is because, generally, higher timeframes have more importance than lower timeframes.
2. Shift In Market Structure - SMS for Entries
A Shift in Market Structure “SMS” identifies potential reversal in short-term market trend relative to the timeframe where the SMS is identified.
This occurs after a run of any Significant Swing High or Low and then reversing, creating a Fair Value Gap “FVG”.
There can be Bullish and Bearish Market Structure Shifts.
When a Bullish Shift in Market Structure occurs, the indicator identifies an opportunity for the price to change from Bearish to Bullish, as seen in the image below.
When a Bearish Shift in Market Structure occurs, the indicator identifies an opportunity for the price to change from Bullish to Bearish.
3. Break In Market Structure - BMS for Entries
A Break in Market Structure “BMS” has a similar function to the Shift in Market Structure “SMS”; however, when it occurs, it identifies a potential longer-term trend reversal (compared to the SMS) relative to the timeframe where the BMS is identified.
Unlike “SMS”, the BMS occurs after a run only after a run on Key Highs or Lows.
Similar to the SMS, there can be Bullish and Bearish Breaks in Market Structure.
When a Bullish Break in Market Structure occurs, the indicator identifies an opportunity for a longer-term trend change from Bearish to Bullish, as seen in the image below.
The FVG must occur in the lower 50% of the impulse price leg (at Discount).
When a Bearish Break in Market Structure occurs, the indicator identifies an opportunity for a longer-term trend change from Bullish to Bearish.
The FVG must occur in the upper 50% of the impulse price leg (at Premium).
4. Inversion Break and Shift in Market Structure for Early Entries
Inversion “BMS” and “SMS” are similar to the normal SMS and BMS, but they occur:
Bullish: When the FVG of the Bearish BMS/SMS forms in the lower 50% of the impulse price leg (at Discount).
We use the FVG that forms from the Bearish SMS/BMS as an inversion FVG for potential entry after market trend change from Bearish to Bullish.
Bearish: When the FVG of the Bullish BMS/SMS forms in the upper 50% of the impulse price leg (at Premium).
We use the FVG that forms from the Bullish SMS/BMS as an inversion FVG for potential entry after market trend change from Bullish to Bearish.
5. Multi Time Frame analysis
The indicator allows multiple timeframe perspectives to be considered when using it.
The key Highs and Lows have significance not only on the current timeframe they are identified but also on lower or higher timeframes simultaneously.
This is because a ITL/ITH on the 1H means
It’s a LTL/LTH on one or more timeframes lower (15Min, 5M, and 1Min).
And at the same time, it’s a STL/STH on one timeframe higher (4H)
Also, it’s a Significant Low/High (marked with a dot) on two timeframes higher (Daily).
The same logic applies to all other Key Highs and Lows.
Another example is a Significant Low/High (swing marked with a dot below or above it) on the current timeframe (1D) means it’s a STL/STH on one timeframe lower (4H) and an ITL/ITH on two timeframes lower (1H) and a LTH/LTH on three timeframes lower or more (15M, 5M, 1Min, 30 Seconds, etc…).
This Multi-time frame analysis is a great way to help traders understand Market Structure and Market trend on multiple timeframes simultaneously, and it also assists in Top-down analysis.
PS: Note that this multi-timeframe analysis approach and logic can be applied to any timeframe and for any type of trading (swing trading, day trading, scalping, or short-term trading) because the price is fractal.
For example, if a trader is a swing trader, then it’s best to identify trader opportunities on the 1H or higher; however, lower timeframes Market Structure can still be used to help the traders refine their entries and target key highs and lows in the opposite direction.
If a trader is a day trader or a scalper, the trader could use Market Structure on 15M or lower to identify trader opportunities and target key highs and lows in the opposite direction.
6. Setting Targets
The indicator can also be used to identify potential targets after the SMS or BMS occurs. Targets can be chosen above Key Highs or Lows depending on the trade objective and timeframe where the trade idea is identified.
Bonus Features
Highlight Market Structure Trend
This feature is an excellent backtesting visual tool to look at changes in market trends highlighted in colours. These changes are based on the Shift or Break in of Market Structure depending on the selection option.
When "Shift/Break" in Market Structure" is selected, a Bullish trend is highlighted in blue when a Bullish Shift/Break in Market Structure Occurs and in Red when a Bearish Shift/Break in Market Structure Occurs.
Notifications
Sends notifications when there is a Shift or Break in Market Structure on the current timeframe of choice.
Peak & Valley Levels [AlgoAlpha]The Peak & Valley Levels indicator is a sophisticated script designed to pinpoint key support and resistance levels in the market. By utilizing candle length and direction, it accurately identifies potential reversal points, offering traders valuable insights for their strategies.
Core Components:
Peak and Valley Detection: The script recognizes peaks and valleys in price action. Peaks (potential resistance levels) are identified when a candle is longer than the previous one, changes direction, and closes lower, especially on lower volume. Valleys (potential support levels) are detected under similar conditions but with the candle closing higher.
Color-Coded Visualization:
Red lines mark resistance levels, signifying peaks in the price action.
Green lines indicate support levels, representing valleys.
Dynamic Level Adjustment: The script adapts these levels based on ongoing market movements, enhancing their relevance and accuracy.
Rejection Functions:
Bullish Rejection: Determines if a candlestick pattern rejects a level as potential support.
Bearish Rejection: Identifies if a pattern rejects a level as possible resistance.
Usage and Strategy Integration:
Visual Aid for Support and Resistance: The indicator is invaluable for visualizing key market levels where price reversals may occur.
Entry and Exit Points: Traders can use the identified support and resistance levels to fine-tune entry and exit points in their trading strategies.
Trend Reversal Signals: The detection of peaks and valleys serves as an early indicator of potential trend reversals.
Application in Trading:
Versatile for Various Trading Styles: This indicator can be applied across different trading styles, including swing trading, scalping, or trend-following approaches.
Complementary Tool: For best results, it should be used alongside other technical analysis tools to confirm trading signals and strategies.
Customization and Adaptability: Traders are encouraged to experiment with different settings and timeframes to tailor the indicator to their specific trading needs and market conditions.
In summary, the Peak & Valley Levels by AlgoAlpha is a dynamic and adaptable tool that enhances a trader’s ability to identify crucial market levels. Its integration of candlestick analysis with dynamic level adjustment offers a robust method for spotting potential reversal points, making it a valuable addition to any trader's toolkit.
Dynamic Trend Fusion (DTF)The "Dynamic Trend Fusion" (DTF) indicator is a powerful technical analysis tool for traders. It stands out from other indicators due to its adaptability and ability to provide insights into different trading styles. Users can choose from various trading options such as "Short-term Trading," "Long-term Trading," "Aggressive Short-term," "Conservative Long-term," "Balanced Approach," "High Sensitivity," "Low Sensitivity," "Day Trading," and "Swing Trading." These options allow traders to customize the indicator to suit their specific trading strategies.
DTF combines the Moving Average Convergence Divergence (MACD) and Relative Strength Index (RSI) indicators, normalizing them to a similar scale for a comprehensive view of market conditions. It then calculates a combined value and smoothes it using a moving average.
One of its standout features is the ability to identify bullish and bearish states, which is represented visually on the chart. When the indicator detects a transition from a bullish to a bearish state or vice versa, the color of the line changes.
Additionally, DTF offers alert conditions, notifying users when the market shifts into a bullish or bearish state, allowing for timely decision-making.
In summary, the DTF indicator sets itself apart by providing traders with a versatile tool that can be tailored to various trading styles and offers clear visual signals for trend changes, enhancing trading precision and efficiency.
ESZ2023 M1 SR v231019E-mini S&P 500 Futures ESZ2023 Contract Gann Support & Resistance
Description:
Support and resistance angles based on starting date and time stamp and ending date and time stamp, extended to the right in time to show interaction with price. The method of drawing these Gann angles is different than other previously published “Gann angles” and uses an esoteric WD Gann time & price squaring calculation method that he never explicitly published but hid in plain sight in his book " Tunnel Thru the Air ". In the spirit of preserving the originality of Gann’s work, the underlying logic is not being explicitly disclosed here, only an expression of the logic derived from a ‘key’ he left us in his book.
Gann's methods were originally meant for position trading and swing trading larger timeframes. Here these Gann support and resistance levels have been adapted for intraday on the 1-minute chart.
While Gann’s method of calculating support and resistance levels works on any timeframe and instrument, these specific levels published have been calculated for the E-mini S&P 500 Futures ESZ2023 Contract.
What the script does, how it does it and how to use it:
This script draws angles on a chart that represent likely areas where price will encounter support or resistance according to what Gann called the “law of vibration”, suggesting that every instrument moved within its own vibrational frequency.
Gann’s law of vibration can be expressed on a chart as ripples created in still water are expressed by applying surface tension on the water to create the ripples. Similarly, to ripples in water, Gann’s price impulse waves cause price oscillation or ‘ripples’ that resonate through time. These support and resistance levels were calculated based on a single impulse wave in time. The angles represent where time and price square out relative to the impedance of the originating impulse wave.
To use the script, simply apply it to an ES chart on the 1-minute time frame. For improved readability, you should apply a dark theme to your chart. To troubleshoot instances where the lines won’t show for whatever reason, try refreshing the browser or re-applying the script. Panning backwards on the chart to where the line angles start will also get the angle lines to reappear.
What the Different Lines Mean:
Red – These are called ‘axis’ lines and represent very critical support and resistance levels that can signal major trend changes. The axis lines stem from a single impedance point of origin.
Yellow – These are called ‘node’ lines and represent minor support and resistance levels that can signal where price will target or retrace to as it moves towards a higher timeframe price objective. Nodal lines stem from an upper and lower node relative to the wave’s impedance center.
Preserving the Originality of the Script and Usefulness of the Lines Code:
The script dates and timestamps are being protected to deter the proliferation of tampered versions of these Gann calculations which will detract from their usefulness and make it harder for other TradingView users to find the original publisher source.
Quantum Market Strength Indicator (MSI)The Market Strength Indicator (MSI) is yet another in our stable of volume-based indicators, and as such, is a must-have tool for trading virtually any type of market and across a myriad of applications from trend trading to swing trading, scalping, and much more. While its sister indicator, the Currency Strength Indicator (CSI), helps you analyze which currencies are oversold, overbought, correlating, and trending, the MSI or Market Strength Indicator does this also, but in this case, for all markets, including stocks, ETFs, futures, and cryptocurrencies, but with one key difference – VOLUME.
As with our core methodology of volume price analysis, volume adds an entirely new dimension to trading analysis as it reveals the driving pressure behind the price action, be it strong or weak, which are all factored into the algorithm that drives the Market Strength Indicator. But with the MSI indicator, its use and application is only limited by your imagination.
For example, we can use it to see which markets are correlating and which are not so that we might use it as an intraday tool for index futures. And, of course, with knowledge gained from the stock trading and investing program, we could then further validate any analysis by setting each against the top five market cap stocks, for confirmation of strength and to give us more confidence in trading an index future.
And not just index futures, but any futures you care to consider, such as energy, metals, softs, currencies or anything else.
For day traders of stocks, you might wish to see which are correlating with one another and which are not, for example, if you are pairs trading, and also whether a particular stock is moving with the primary futures index. If not, this may be a warning sign. And of course, for ETF traders, we have the SPY, a host of ETFs, and alongside them, the sectors, such as the XLK, the XLE, and more, giving you an instant and powerful insight into sentiment across the entire market complex.
The Market Strength Indicator has much to offer; whether you are a stock investor or day trading scalper, index or ETF trader, swing trader or trend trader, it is all here as the indicator signals in a clear and intuitive way when a stock, future or ETF is overbought or oversold in all timeframes, giving you that potent insight into potential reversals from strong to weak and back again. If you enjoy getting into a trend early and trading reversals, then this is the indicator for you, but if you prefer trading trends – no problem, just jump aboard once the move has some momentum and is underway as displayed by the steepness of the line on the indicator.
It’s all here and so much more, from market correlations to market strength and weakness and in all the timeframes from seconds to months.
And just like its sister indicator, the CSI, the MSI is an oscillator that moves seamlessly from overbought to oversold and back again between a value of 100 at the top and zero at the bottom, with each instrument or market represented with a single-colored line. To help further, we’ve included two regions on the indicator to represent these states at 70 and 30, respectively, but you can change these accordingly and perhaps extend them further to 80 and 20. These levels are purely intended as guides to help provide additional information as to the market state and a potential reversal in due course.
Now, in a single indicator, you have the opportunity to gauge sentiment across multiple markets, whether these are correlating or not, and from there develop a myriad of trading opportunities, or alternatively give you that all-important confidence to dive in, or maintain an existing position. Through its unique algorithm based on volume, it is another indicator only limited by your imagination, and like all our other indicators, one we urge you to use in multiple timeframes.
Nitin Swing TradingThis is a CPR which indicates pivot points based on monthly price action.
The Orange line acts as a resistance area, blue lines act as pivot point/CPR and green one is support.
One can study retrospective chart to analyse how market has respected these Support and Resistance levels.
A guide on how to trade using this indicator?
1. If you see the resistance is broken after multiple attempt - We can Go Long
2.If you see price going down below CPR, We can Go Short
3.If you see price taking support at support level - We can Go Long.
Risk reward should always be 1:1 then gradually increase it to 1:2 & 1:3
It is advised to consult with your financial advisor before taking any trade just based on any indicator. You have to manage risk before entering any trade.
Heuristic Bg Color Hodl/swing/scalp [Ox_kali]The "Heuristic BG Color Hodl/Swing/Scalp " is a multi-faceted technical indicator designed to aid traders across varying investment strategies such as long-term holding (Hodl), swing trading, and scalping. Optimized to run on a range of timeframes from seconds to months. Built upon an intricate layering of moving averages, market oscillators. The indicator displays a color range from light green to deep red, based on market conditions. This tool aims to provide an analytical edge by visualizing market conditions in a straightforward manner. Incorporating both trend-following and oscillatory components both trend-following and oscillating components to furnish a more rounded view of the market. Note that this indicator is best used in conjunction with other forms of market analysis and should not be solely relied upon for making trading decisions.
Key Features:
Multiple Moving Averages: Utilizes Fast and Slow MAs to identify trend momentum.
Modified RSI and MFI: Incorporates RSI and MFI to gauge overbought and oversold conditions.
Stoch RSI Indicator: Used to provide additional confirmation for trading signals.
Dynamic Background Color: Highlights potential Buy and Sell zones using background color for easier visual interpretation.
Alert Conditions: Trigger customizable alerts for Buy and Sell zones.
Functionality Analysis:
The script allows you to select the type and period for Fast and Slow moving averages. It uses these MAs to calculate an underlying trend momentum, further refined by a user-defined MA.
The RSI and MFI are used to identify overbought and oversold conditions calculated and smoothed over a user-defined period. The Stoch RSI gives an additional layer of confirmation, allowing traders to identify more reliable trading signals.
The script's main visual feature is the background color, which changes based on potential Buy and Sell zones. It provides two layers for each, enabling traders to understand the strength of the signal. Notably, the indicator is particularly optimized for identifying Buy Zones and is more functional for detecting Sell Zones when applied to larger timeframes.
Trading Application:
The "Heuristic BG Color Hodl/Swing/Scalp" indicator can adapt to various trading styles, from long-term investment to short-term trading. When the background turns green, it signifies a potential Buy Zone, ideal for entering long positions. Conversely, a red background indicates a Sell Zone, suggesting it may be a good time to exit positions or go short.
Traders can also utilize the alert conditions set within the script to receive real-time notifications, making it easier to capitalize on potential market opportunities.
Please note that the "Heuristic BG Color Hodl/Swing/Scalp" by Ox_kali is intended for educational purposes only and does not constitute financial advice. This indicator is not a guarantee of future market performance and should be used alongside proper risk management strategies. Ensure you fully understand the methodology and limitations of this indicator before making any trading decisions. Past performance is not indicative of future results.
Momentum EruptionIndicator: Momentum Eruption , using momentum to capture swing trading.
⏩Principle overview:
The core of Momentum Eruption is divided into two parts. One is to identify the trend direction. This is relatively clear. It is usually more effective to identify the direction through moving averages such as SMA or EMA. The second is to identify trading opportunities and use the idea of following the trend in large cycle and reversing the trend in small cycle. For example, when the large cycle is bullish and the small cycle is callback, if there are oversold conditions, a rebound from the previous low support, a long downward pin-bar, and an increase in trading volume at the same time, the extreme value of the price rebound or correction can be calculated. When following the trend, go long at the extreme value of the callback and go short at the extreme value of the rebound.
⏩Usage：
Signal: "B" stands for long buy signal. "S" stands for short sell signal.
Support and resistance: "Purple areas" represent support areas and "yellow areas" represent resistance areas.
🧿Tip I：
Adaptive signal. Take long buying as an example. When the purple area representing the support range appears, the market is bullish. If a "B" signal appears at this time, it means that you can consider buying and do a wave of short-term trading.
Usually there will be many short-term trading opportunities in a wave of rising trend.
🧿Tip II：
Since the market is reciprocating, the indicator will prompt many signals when it is trending. Each signal is observed and used independently, and it does not prompt the closing and profit taking points. Take profit and stop loss can be set according to your own trading cycle and style.
Regardless of whether it rises or falls, there will always be many swings that can be captured in the trend.
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
[blackcat] L5 Dragon-Void-Dragon for Spot TradingLevel: 5
Background
First of all, this L5 technical indicator is only suitable for spot trading. Because its algorithm is only designed for one-way long, and there is no algorithm for short-selling mechanism.
This technical indicator is the main chart indicator of the integrated trend line, channel technology and moving average technology. Trendlines are straight lines connecting at least two significant highs or lows on a price chart, indicating the direction and strength of a trend. Channels are parallel lines that contain price action within a trend, showing the range and potential reversal points.
Function
Trend lines, channel indicators, and moving averages are all very good subjective technical indicators. However, I have found that if one of the three is used mechanically, or a combination of the three often does not achieve good trading results.Therefore, through continuous practice and summary, I implemented some subjective ideas through algorithms, which improved the winning rate after the integration of the three. Buy and sell points are also more accurate.This involves automatic drawing of trend lines and channel indicators. It is conceivable that if you want to draw relatively stable trend lines and channel indicators, you have to wait until the price trend is relatively stable to obtain stable trend lines and channel lines. The advantage of this is that the subsequent price may rely on this inertia to move up and down the trend line or in the channel, which can be the basis for trend reversal. On the other hand, the formation of trendlines and channel indicators requires price movements and time as prerequisites. This means that the process of waiting for the formation of the trend must also sacrifice part of the profit. This is a trade-off between corresponding characteristics and stable characteristics. What we need to do is to find a perfect balance between the two, and expand profits while keeping risks within a controllable range. Ultimately realize big wins and small losses, long-term compound interest accumulation.
The technical elements reflected in this indicator are: channel line, color of trend strength, double moving average. And through the calculation of the background algorithm, some labels for buying and selling are obtained as alarm signals.
Key Signal
Overall this indicator is quite intuitive and does not require a lot of intellect to understand how to use it. It can be summarized as:
1. If the channel is in a warm color and the direction points to the upper right corner, then go long; if the channel is in a cool color and the direction points to the lower right corner, then go short or close the position.
2. The color of the channel is changed from cool to warm. The extreme value of the cool color is dark blue, which means that it is extremely oversold; the extreme value of the warm color is purple, which means that it is extremely overbought; therefore, when you see channels in different directions, you should also pay attention to their colors, which means that the current channel is in the market Where, and if you need to be careful about price reversals.
3. Because this technical indicator is specially developed for spot trading. Therefore, if you want to enter the market, it is generally better to have the color of the channel and the candle be yellow and orange. Otherwise, it is just a rebound, and the price will repeat more later, and it is more necessary to continue to fall.
4. The double moving average system is also specially customized, mainly combined with Zen Theory's Kiss Saying. This double moving average system is a pressure and support system other than the channel. When an uptrend is relayed and continues to rise after a retracement, the Kiss, Wet-Kiss, and Fly-Kiss triggered by the double moving average will generate yellow and orange buy signal labels.
5. This system needs to wait for the price trend to stabilize before generating a buying and selling point, so there are not many buying and selling signals, and of course some entry opportunities will be missed. Of course, this is the result of sacrificing timeliness for transaction stability. So, be flexible. If your trading style is more aggressive, you can only use the buy and sell labels as auxiliary signals.
Remarks
1. It need time to stablize trendlines and channels, so "B"/"S" labels may not be so in time.
2. Closed-source, Invite-only, NOT free.
3. Highl recommended to use this indicator for >= 30min timeframe, which means this is powerful for swing trading.
4. If you are trading crypto, highly recommend use " L3 RS MSFIELD Crypto" indicator as a screener to find target is stronger than Bitcoin.
5. If you are trading CN A Share, highly recommend use " L3 RS MSFIELD CN A Share" indicator as a screener to find target is stronger than SSE Index.
Subscription
L4/L5 are not free indicators. Trail permissions can be given. Monthly and annual subscriptions are acceptable.
Supply And DemandThis supply and demand indicator uses sessions, volume spikes, higher timeframe price action and other volume calculations to spot areas on the chart where price will likely react. From the 1 minute and below charts to the daily and up charts, you can get excellent levels for any timeframe.
Why Use Supply And Demand?
One of the safest ways to trade is to wait for price to enter an area of interest where price should react. When we play reversals off of these areas, you increase the likelihood that your trade will be profitable because there was previous price action that told you that the current level is one where price will react. So we look for reversals at or very near these levels to enter into scalp or swing trade positions and look to exit that position when price is at or near the next major supply and demand level.
How To Use
The strategy with this indicator is to wait for price action to reach the levels shown by this supply and demand indicator and then enter trades at these levels, looking for a reversal. The thicker lines and the lines that are from the highest timeframes will be the most important levels on the chart. There is a table on the chart that will help you identify what timeframe the levels are using, with the color of that line next to it for easy identification.
The default settings are designed for scalping the 1-5 minute charts, so there are more levels turned on than necessary if you are using higher timeframes than 5 minutes. If you are using higher timeframes, make sure to turn off some of the lower timeframe levels so that it doesn’t clog up your charts. On the daily timeframe and above, many of the levels are coded to not turn on so that you don’t have to turn them off manually, but be aware that you will need to adjust your charts to suit your preferences, especially if you are on anything above the 5 minute chart.
For scalping, wait for price to react from the supply and demand levels by showing wicks, struggling to break through or getting reversal candles at those levels. Ride those moves to the next major supply and demand area before taking profit. You may want to turn on sessions and some of the lower timeframe levels as well if there are big gaps on the chart that are not suitable for scalping.
For swing trading, you will want to turn some of the lower timeframe and session levels off. Leave it to only higher timeframe OHLC lines and volume spike levels. Then you can swing moves that reverse off of the supply and demand lines.
Customization
This indicator is fully customizable. You can turn on or off any of the levels as well as increase the number specific levels so your charts suit your preferences.
All of the levels used are color coded individually so you can easily tell which type of level it is and these colors can be changed within the settings to suit your preferences. These colors are also reflected in the line identification table that show you exactly which color each type of level is.
There are toggles for the line identification table and session identification table as well if you don’t want them on your chart.
Types Of Levels Used
This indicator uses 4 different types of levels that I have found to be extremely influential on the price action. They are: volume spikes, higher timeframe price action, country based trading sessions and the VWAP. All of these levels have proven to be very important levels in my testing and are very helpful in spotting reversal areas.
Volume Spikes
This indicator is looking for the largest volume spikes and plotting the levels where that volume came in. It checks for the highest volume spikes across multiple different lengths of candles so that you get recent levels as well as the most important levels in the past. There are volume spike calculations for your current chart timeframe, 1 hour charts, 4 hour charts, daily charts, weekly charts, and monthly charts. Each of these looks for volume spikes across various lengths of candles for each timeframe and is color coded so you can identify which levels are which easily. The weekly and monthly volume spike levels are fatter than the normal volume spike levels with a line width of 2 to signify their importance.
OHLC Higher Timeframe Candles
This script plots levels of higher timeframe candles since price usually reacts very strongly to these levels. The levels it will produce are the high, low, open and close of the most recent closed candle of each higher timeframe. You can adjust these to show as many or as few previous HTF candles as you would like. The higher timeframe candles available to use are as follows: 1 hour, 4 hour, daily, 3 day, weekly, monthly, quarterly and yearly. The monthly, quarterly and yearly levels are fatter than the normal levels with a line width of 2 to signify their importance.
Trading Sessions
Trading sessions are very important levels because the market makers of different parts of the world are typically positioning themselves at these specific times. The number of each trading session line can be adjusted to show more or less levels depending on your preference. When you adjust the number, it will affect all lines that are enabled for that specific session. The levels available for each Tokyo, London & New York session are as follows: session premarket open, regular session open, session close, and session high & low. The session close boxes are fatter than the others with a line width of 2 to signify its importance.
VWAP & Previous Close
We all know that the VWAP aka Volume Weighted Average Price is a very important level on any chart, so we included this level as a default. However, we decided to take this a step further and include the previous daily session’s VWAP closing price and plot those levels. These are extremely important levels that you should pay very close attention to, along with the other levels mentioned above. The market makers are hedging their positions based on these levels and you will typically see very strong reactions to these levels, especially in the first hour when the markets open up. The VWAP and previous session VWAP close levels can be turned on or off and the default for the number of previous VWAP session close prices is set to 5. These levels are fatter lines because they are extremely important, so make sure to pay attention to them!
Line & Session Identification Tables
There are two tables to help you identify what is on the chart. The first is a large table in the top right that shows you the color and type of each line that is turned on so you can easily identify which lines are which. The second table is a small one at the bottom center of the chart that tells you which trading session we are currently in and what color that session is on the chart. These tables can be turned on or off and you can also change where they are on the chart by adjusting them at the bottom of the settings page.
Markets
This Supply And Demand indicator can be used on any market with price data such as stocks, crypto, forex and futures.
Timeframes
This Supply And Demand indicator can be used on any timeframe, from the second charts all the way up to the yearly charts.
TradeMaster ProTrading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. To address this, we present a powerful indicator package designed to assist traders on their journey to success.
The TradeMaster indicator package encompasses a variety of trading strategies, including the SMC (Supply, Demand, and Price Action) approach, along with many other techniques. By leveraging concepts such as price action trading, support and resistance analysis, supply and demand dynamics, these indicators can empower traders to analyze entry and exit positions with precision. Unlike other forms of technical analysis that produce values or plots based on historical price data, Price Action brings you the facts straight from the source - the current price movements.
The indicator package consists of three powerful indicators that can be used individually or together to maximize trading effectiveness.
⭐ About the Pro Indicator
The Pro indicator is the cornerstone of the package, offering a comprehensive range of functions. It's strength lies in our unique structure calculation, which is based on real price action data, capturing every ticks from small intraday fluctuations to the significant high timeframe movements. The Pro Indicator reflects our personal use and deep comprehension of Smart Money Concepts. It provides streamlined tools for tracking algorithmic trends with modern visualizations, without unnecessary clutter.
In the ever-evolving trading landscape, mainstream methods and strategies can quickly become outdated as they are widely adopted. Liquidity is constantly sought after, and the best source for this is exploring and exploiting trading strategies that are widely accepted and applied. Currently, one of these strategies is the SMC (Supply, Demand, and Price Action).
It's no coincidence that our educational materials incorporate concepts such as liquidity grabs (LG) and Smart Money Traps (SMT). As the application of SMC gains popularity among retail traders, trading with this approach becomes more challenging. Therefore, the recent focus has been on reforming the SMC methodology, as it is the only method that relies on real price movements and will always work when applied correctly.
▸ What does proper application of SMC entail?
Many SMC traders associate their key areas of interest with the market structure, which is generally considered acceptable. However, depending solely on a single foundation can lead to significant deviations, which may cause notable impacts on trading results. Moreover, if the basis for the market structure calculation is inaccurate, the consequences can be even more severe. It's akin to risking money on a lottery ticket, believing it will be a winner.
Our methodology is different, and it may ensure longevity in the financial markets. The structure remains crucial, but it is not the sole foundation of everything; instead, it serves as a validation tool. Each calculation, such as order blocks (OB), Fair Value Gaps (FVG), liquidity grabs (LG), range analysis, and more, is independent and unique, separate from the structure. However, validation must ultimately come from the structure itself.
We employ individual and high-quality filters: before a function calculation is validated by the structure, it must undergo rigorous testing based on its own set of validation conditions. This approach aims to enhance robustness and accuracy, providing traders with a reliable framework for making informed trading decisions.
▸ An example for structure validation: Order Block with "Swing Sensitivity"
These order blocks will only be displayed and utilized by the script if there is a swing structure validation with a valid break. In other words, the presence of a confirmed swing Change of Character (ChoCh) or Break of Structure (BoS) is essential for the Order Block to be considered valid and relevant.
This approach ensures that the order blocks are aligned with the overall market structure and are not based on isolated or unreliable price movements. Whether it's Fair Value Gaps (FVG), Liquidity Grabs (LG), Range calculations, or other functionalities, the same underlying principle holds true. The background structure calculation serves as a validation mechanism for the data and insights generated by these functions, ensuring they adhere to the specific criteria and rules established within our methodology. By incorporating this robust validation process, traders can have confidence in the reliability and accuracy of the information provided by the indicator, allowing them to make informed trading decisions based on validated data and analysis.
👉 Usage - the general approach:
Determine your trading style using the Pro Indicator and build your basic strategy. This indicator helps you understand your trading style, whether it's swing trading, scalping or another approach. By analyzing the Pro Indicator, you gain valuable information about potential market trends, entry and exit points, and overall market sentiment.
👉 Example of usage:
In the following chart, you'll notice how we've utilized the indicator to formulate a strategic trading approach. We've employed Order Blocks equipped with volume parameters to identify crucial market zones. Simultaneously, we've leveraged swing/internal market structures to gain insights into potential long and short-term market turnarounds. Lastly, we've examined trend line liquidity zones to pinpoint probable impulses and breakouts within ongoing trends.
Now we can see how the price descended to the order block with the highest volume, which we had previously marked as our point of interest for an entry. As the price closed below the median Order Block, we noted its mitigation. After an internal CHoCH, it's directing us towards the main Order Block as a target.
👉 Smart Money Concepts Functions
Market Structure: identifies and marks key structural changes in the market, in order to visually highlight shifts in market trends and patterns. This feature is designed to alert you of significant changes in the market's behavior, signaling a potential shift from accumulation to distribution phase, or vice versa. It helps traders adapt their strategies based on evolving market dynamics.
Order Blocks: pinpoints crucial zones where large institutional investors ("smart money") have shown strong buying or selling interest recently. Order blocks can serve as a tool for identifying key levels for potential trade entries or exits.
FVGs (Fair Value Gaps): detects discrepancies between the perceived market value and actual market price, revealing potential areas for price correction. With its mitigation settings, you can fine-tune the FVG detection according to the magnitude of value misalignment you consider significant.
Liquidity Grabs: helps track "smart money" footprints by identifying levels where large institutional traders may have induced liquidity traps. Understanding these traps can aid in avoiding false market moves and optimizing trade entries.
Automatic Fibonacci Tool: Simplifying the task of identifying key Fibonacci retracement and extension levels, this tool ties Fibonacci levels to the structure for you. It aids in recognizing significant support and resistance levels, providing a clearer understanding of potential price movements.
The Smart Money Concepts trading strategy - combined with these dynamic features - becomes a powerful analytical asset for any trader, providing in-depth insights into market dynamics, trends, and potential opportunities.
👉 Algorithmic trend and dynamic support and resistance
Trend Rainbow: This proprietary feature uses our unique TRMA** method to define short-term, medium-term, and long-term market trends. It incorporates state-of-the-art visualization techniques to render the trend information in an intuitive, easily interpretable manner. It's a 21st-century tool designed for the modern trader who values both precision and simplicity.
Multi-Timeframe Moving Averages: This feature allows traders to simultaneously monitor moving averages across multiple timeframes, providing a comprehensive perspective on market trends. It helps identify dynamic support and resistance zones, key levels where price movements are likely to slow down or reverse. This function not only aids in planning potential trade entries and exits, but also calculates the precise percentage distance to these levels. Can be as well crucial for risk management, enabling traders to set stop losses and profit targets based on solid, data-driven analysis. The Multi-Timeframe Moving Averages function is a versatile tool that combines strategic planning and risk control into a single, easy-to-use feature.
👉 Unlock the Hidden Market Dynamics
Market Sessions: This feature - by default - provides a clear representation of the four major global trading sessions. Each session is distinctly marked on your trading chart, helping you visualize the specific time periods when these markets are most active. Recognizing these sessions is critical for understanding market dynamics, as the opening and closing of major markets can lead to significant price movements. Whether you're a day trader looking to exploit intra-day volatility or a long-term investor wanting to understand broader market trends, the Market Sessions feature can be a useful tool in your trading toolkit.
Divergence Functions: allow the use of unique indicators along with our proprietary ones to detect potential price reversals. As each asset has a different market maker, divergences can vary greatly across different charts and timeframes. With our Divergence Ranking Table, you can quickly determine which divergences have the highest success rates and which are the least successful on a given chart. This feature allows you to adapt your strategies to the most effective signals, enhancing your trading decisions and boosting your potential profits.
Volume Profile with delta: This feature may give traders an edge by providing an in-depth view of market activity. It illustrates the amount of trading volume at different price levels, combined with the 'delta', which is the difference between buying and selling volume. This information allows you to see areas of high trading activity and understand whether the volume is pushing the price up or down. This real-time insight into the market's supply and demand can be instrumental in identifying key support and resistance levels, predicting potential reversals, and recognizing where the market is likely to move. Similarly to Fibonacci tool, Volume Profile can be tied to the current market structure.
👉 Improve Trading Decisions
Range: This innovative feature assists traders in determining discount, premium, and equilibrium zones. It provides a unique way of visualizing price areas where a security could be overbought or oversold (premium or discount zones), and where the price is expected to be fair and balanced (equilibrium zone). Distance from current price is displayed in percentage terms, which can assist traders with crucial data for risk management and strategic planning. The Range function helps you identify the most favorable price zones for entries and set your stop-loss and take-profit levels more accurately.
Previous OHLC: This functionality offers the capability to display the previous Open, High, Low, Close values. It is primarily set on the daily timeframe and serves as an important reference for traders. Having an overview of these key levels from the previous day gives you a solid foundation on which to base today's trading decisions. Recognizing these levels can help you predict potential turning points in the market, providing an advantage in your trading strategy.
Smart Money Zones: our secret weapon for swing traders. Similarly to order blocks, these zones can accurately identify crucial areas of strong buying or selling interest by large institutional investors. However while Order Blocks focus on recent price action, Smart Money Zones take the whole chart into consideration, resulting in more established support and demand zones.
The summary graph combines six unique indicators (Momentum, Trend Strength, Volume, Volatility, Asset Strength, and Sentiment) along with Structure and Sessions. These indicators use our TRMA** method to provide a comprehensive overview of market dynamics. By consolidating these indicators into a single graph, traders can gain valuable insights into the overall market landscape.
** TRMA (Trend Rainbow Moving Averages) is a complex but customizable moving average matrix calculation that is designed to measure market trend direction, strength and shifting.
⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. Our aim is to offer useful features that meet the needs of the 21st century and that we actually use.
🛑 Risk Notice:
Everything provided by trademasterindicator – from scripts, tools, and articles to educational materials – is intended solely for educational and informational purposes. Past performance does not assure future returns.
FalconRed 5 EMA Indicator (Powerofstocks)Improved version:
This indicator is based on Subhashish Pani's "Power of Stocks" 5 EMA Strategy, which aims to identify potential buying and selling opportunities in the market. The indicator plots the 5 EMA (Exponential Moving Average) and generates Buy/Sell signals with corresponding Target and Stoploss levels.
Subhashish Pani's 5 EMA Strategy is a straightforward approach. For intraday trading, a 5-minute timeframe is recommended for selling. In this strategy, you can choose to sell futures, sell calls, or buy puts as part of your selling strategy. The goal is to capture market tops by selling at the peak, anticipating a reversal for profitable trades. Although this strategy may result in frequent stop losses, they are typically small, while the minimum target should be at least three times the risk taken. By staying aligned with the trend, significant profits can be achieved. Subhashish Pani claims that this strategy has a 60% success rate.
Strategy for Selling (Short Future/Call/Stock or Buy Put):
1. When a candle completely closes above the 5 EMA (with no part of the candle touching the 5 EMA), it is considered an Alert Candle.
2. If the next candle is also entirely above the 5 EMA and does not break the low of the previous Alert Candle, ignore the previous Alert Candle and consider the new candle as the new Alert Candle.
3. Continue shifting the Alert Candle in this manner. However, when the next candle breaks the low of the Alert Candle, take a short trade (e.g., short futures, calls, stocks, or buy puts).
4. Set the stop loss above the high of the Alert Candle, and the minimum target should be 1:3 (at least three times the stop loss).
Strategy for Buying (Buy Future/Call/Stock or Sell Put):
1. When a candle completely closes below the 5 EMA (with no part of the candle touching the 5 EMA), it is considered an Alert Candle.
2. If the next candle is also entirely below the 5 EMA and does not break the high of the previous Alert Candle, ignore the previous Alert Candle and consider the new candle as the new Alert Candle.
3. Continue shifting the Alert Candle in this manner. However, when the next candle breaks the high of the Alert Candle, take a long trade (e.g., buy futures, calls, stocks, or sell puts).
4. Set the stop loss below the low of the Alert Candle, and the minimum target should be 1:3 (at least three times the stop loss).
Buy/Sell with Additional Conditions:
An additional condition is added to the buying/selling strategy:
1. Check if the closing price of the current candle is lower than the closing price of the Alert Candle for selling, or higher than the closing price of the Alert Candle for buying.
- This condition aims to filter out false moves, potentially preventing entering trades based on temporary fluctuations. However, it may cause you to miss out on significant moves, as you will enter trades after the candle closes, rather than at the breakout point.
Note: According to Subhashish Pani, the recommended timeframe for intraday buying is 15 minutes. However, this strategy can also be applied to positional/swing trading. If used on a monthly timeframe, it can be beneficial for long-term investing as well. The rules remain the same for all types of trades and timeframes.
If you need a deeper understanding of this strategy, you can search for "Subhashish Pani's (Power of Stocks) 5 EMA Strategy" on YouTube for further explanations.
Note: This strategy is not limited to intraday trading and can be applied to positional/swing
Probability Box Rule of Thirds [PPI]█ Probability Box Rule of Thirds
The Probability Box Rule of Thirds , is a visual indicator that helps traders identify possible overbought and oversold conditions. It does this by dividing the price range – highest high minus the lowest low of a given lookback period or date range – into thirds. Each third has distinct probability characteristics and when combined represent a probability box.
We have spent years refining the probability box concept, and have previously published a How To on Trading View – "How to Trade Probability Ranges – The Critical Rule of 1/3" which can be found here:
To quickly summarize the How To – when using the Rule of Thirds , you are using a combination of statistics, probabilities of success, and prior price action to determine when to enter a trade. The visual range division helps remove subjectivity and clearly shows when the trading odds are stacked in your favor. By identifying and taking higher probability trades, you have a higher chance of success as trading is all about probability and risk management.
Implementing the Rule of Thirds starts with finding an instrument that is consolidating and identifying the nearest important support and resistance levels based on your targeted trading timeframe or lookback period.
The range between the support and resistance levels is divided into thirds to form three zones within the consolidation range.
When going LONG , you want to BUY in the bottom third of the range. Once you buy, your objective is to hold during the middle third and sell when the price enters the top third.
When you buy in the lower third, there's a 66.6% probability of success. If you buy in the middle third, you only have a 50% / 50% chance of success. Going long in the top third of the range gives you a 33.3% chance of success as you are already close to the identified resistance level.
When going SHORT , the sequence and odds are reversed. You want to SELL in the top third of the range, hold the middle third and exit in the bottom third of the range. This gives you a 66.6% chance of success when entering in the top third, a 50% / 50% chance when entering in the middle third, and a 33.3% chance in the bottom third given you are already close to the identified support level.
When the price lies in the middle third, the even 50% / 50% odds provide no probability edge and a trader is better off waiting until the price reaches the upper or lower thirds of the price range.
The Rule of Thirds allows us to quickly visually evaluate trades based on probabilities, selectively enter trades that have the highest odds of success, and avoid likely losing trades. The Rule of Thirds gives you confidence to hold trades based on prior trading ranges and provides clear levels where the prices are likely to either reverse or start trending.
The Probability Box Rule of Thirds automatically implements the first two steps of the Rule of Thirds by using the highest high and lowest low of a given lookback period to identify the support and resistance levels, and automatically divides the range into thirds. The rest of the Rule of Thirds rules remain the same.
Just having the price within the bottom thirds or top thirds, however, does not mean the price will immediately reverse. The GE chart below is an example of a stock that remained 'stuck' in the upper thirds of the price range for an extended amount of time:
And the CVS chart below is an example where the price is 'stuck' in the lower thirds of the price range:
While the price is in the upper or lower thirds, it is very important that the trader should use other indicators to identify when a significant trend reversal occurs. Once a trend reversal event happens, the trader either enters a trade AND/OR exits a trade if already in one.
When the price exceeds the bounds of the probability box, there are three possible outcomes – a strong continuation trend, the price consolidates around the probability box edge, or a trend reversal. Your favorite indicators will help determine which event is happening.
The CVS chart above is a good example of the probability box being exceeded with the last bar. The price exceeding the price range is temporary event as the price range will expand to encompass the revised price range on the next trading day.
█ Indicator Features
Each supported timeframe – Monthly, Weekly, and Daily – allows the selection of an appropriate lookback period for your trading style. The defaults are a good starting point for swing trading and long-term investing. You many need to experiment to find the optimal lookback period for your trading style.
Even if you only day trade, the Probability Box Rule of Thirds with the appropriate lookback periods can help you visualize the bigger picture of where the instrument is heading.
When viewing the charts, you can find the currently selected lookback period above the upper edge of the price range.
The indicator will display a dotted yellow line at 50% of the price range and show the line's value when requested.
The visibility of the actual thirds and border price values are controlled by the " Show Probability Box Values " checkbox. You may need to expand the chart's right margin to see the values.
The " Show Internal Labels " checkbox controls the display of the internal ⅓ Division labels and the percentage odds, along with the 50% label. This option by default is set to off.
The " Show Error Messages " checkbox controls the display of error messages and by default is turned on. Turn off to prevent error messages from being shown on intraday timeframes. Save as indicator default to prevent having to turn off this setting each time added to chart.
The color and transparency controls allow the user to modify the colors used for each third. The default settings are optimized for use with a DARK background.
█ Implementation Notes
IMPORTANT - the Probability Box Rule of Thirds is set up to only handle Monthly, Weekly and Daily charts. This is intentional as the indicator is designed to be used for safer multiple day and longer swing trades. When viewed on intraday charts, the indicator will be hidden.
The Probability Box Rule of Thirds uses a rolling window of the equivalent number of bars for the lookback period rather than relying on the bar starting and ending dates. This allows the use of a standard number of days in the selected lookback window across various instruments and ensures fast, efficient calculations.
The lookback periods are adjusted when non-standard timeframe multipliers are used – e.g., a 12M chart timeframe and a 3-year lookback period will result in a 3 bar lookback. Fractional bars in this calculation are rounded up and any incompatible lookback period and chart timeframe combination will generate a runtime error.
In summary, the Probability Box Rule of Thirds automates and visually identifies overbought and oversold areas, which combined with the Rule of Thirds probability risk profiles, increases your odds of success through better trade selections and higher confidence in your trades.
█ Disclaimer
There is substantial risk in trading. Losses incurred in trading can be significant. Only trade with money you can afford to lose. We make no claims whatsoever regarding the impact of past or future performance on your trading results.
FCPO - NSawit Swing StrategyThis Indicator implements a custom strategy function in an indicator script. It works on a 4-hour time frame and exclusively for the FCPO futures market only.
The NSawit Swing Strategy consists of three main features:
Feature 1: Trade Summary
This feature utilizes the table function to summarize all completed trades within the current active month. The indicator generates a table that displays relevant trade information like total ticks and profit/loss. For example: table.new(position.top_right, 1, 4, border_width=0)
Feature 2: Active Month Highlight
The purpose of this feature is to visually mark the beginning and end of the current active month on the chart. It achieves this by dynamically changing the background color within the current active month. For example: bgcolor(Highlight ? ColorBG : na)
Feature 3: Swing Reversal Points
This feature identifies swing reversal points on the chart by analyzing candlestick patterns and applying a custom matching algorithm.
If a candlestick pattern matches the specified criteria, the indicator generates a retest box area.
When the price touches this box, it triggers long or short orders. The relevant data, including entry and exit points, are stored in sets of arrays. These data are then utilized by the Trade Summary table to provide a comprehensive overview of the swing trading activity.
Take profit and cut loss value can be set in setting.
To view past contracts kindly add this watchlist.
www.tradingview.com
Anchored VWAP (Auto High & Low)OVERVIEW
This script plots, and auto-updates, 3 separate VWAPs: a traditional VWAP, a VWAP anchored to a trends high, and another anchored to a trends low.
VWAP and Anchored VWAPs are commonly used by institutions responsible for the majority of market volume on a given day. Citadel Trading, for example, accounts for approximately 35% of all U.S. listed retail volume , largely executed through program trades over the course of a day, week, or month.
Because VWAP is a prominent market maker tool for executing large trades, day traders can use it to better anticipate trends, mean reversion, and breakouts.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (1 hour or greater) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
The size, color, and visibility of 6 different plots (VWAP, High Anchor, Low Anchor, Average of Anchors, Quarter Values, Interim Bands)
How smooth the average displays
INSPIRATION
1. "How To Measure Anything" by Douglas W. Hubbard
2. "Maximum Trading Gains With Anchored VWAP" by Brian Shannon
Better understanding probability and how to analyze risk (first book), as well as the tools market makers use (second book), has completely reframed how I approach day trading.
Oscillator Toolkit (Expo)█ Overview
The Oscillators Toolkit stands at the forefront of technical trading tools, offering a comprehensive suite of sophisticated, adaptive, and unique oscillators. This toolkit has been thoughtfully designed to cater to all trading styles, ensuring versatility and utility for every trader. The toolkit features our flagship oscillators, including the WaveTrend Momentum, Leading RSI, Momentum Oscillator, and Bellcurves. Furthermore, it offers many great features such as trend recognition, market impulses, and trend changes; all consolidated into a single, easy-to-use indicator.
Access to these high-quality oscillators and tools can elevate your trading strategy, providing you with insightful market analysis and potential trading opportunities. In addition, these tools help traders and investors to identify and interpret various market trends, momentum, and volatility patterns more efficiently.
The Oscillator toolkit works in any market and timeframe for discretionary analysis and includes many oscillators and features:
█ Oscillators
WaveTrend Momentum
The WaveTrend Momentum oscillator is a significant component of the toolkit. It factors in both the direction and the momentum of market trends. The waves within this system are both quick and responsive, operating independently to offer the most pertinent insights at the most opportune moments. Their rapid response time ensures that traders receive timely information, which is essential in the fast-paced, dynamic world of trading.
Example of how to use the WaveTrend Momentum Oscialltor
The WaveTrend Momentum is proficient at identifying trend reversals and pullbacks, allowing traders to enter or exit trades at optimal moments.
Leading RSI
The Leading Relative Strength Index (RSI) is a type of momentum oscillator that is commonly used in technical analysis to predict price movements. As the name suggests, it is an advanced form of the traditional Relative Strength Index (RSI), and it provides traders with more timely signals for market entries and exits.
The Leading RSI works on similar principles but is designed to provide signals ahead of the traditional RSI. This is achieved through more advanced mathematical modeling and calculations, which aim to identify shifts in market momentum before they happen. It takes into account not only the current price action but also considers historical data in a way that can foresee changes in trend directions.
Example of how to use the Leading RSI
The Leading RSI is an enhanced version of the traditional Relative Strength Index, offering more timely indications of divergences and overbought or oversold market conditions.
Momentum Oscillator
This oscillator measures the amount that a security's price has changed over a given time span. It is an excellent tool for understanding the strength of a trend and its potential endurance. When the momentum oscillator rises, it suggests that the price is moving upwards and vice versa.
The Momentum Oscillator is an advanced technical analysis tool that helps traders identify the rate of change or the momentum of the market. It is typically used to determine the strength or speed at which the price of an asset increases or decreases for a set of returns. This oscillator is considered 'fast-moving' and 'sensitive' because it responds quickly to changes in price momentum. The fast-moving nature of this oscillator helps traders to get early signals for potential market entry or exit points.
The Momentum Oscillator analyzes the current price compared to the previous price and adds two additional layers of analysis: 'Buy & Sell moves' and 'Extremes.'
Buy & Sell Moves: This layer of the oscillator helps identify the buying and selling pressure in the market. This can provide traders with valuable information about the possible direction of future price moves. When there is high buying pressure (demand), the price tends to rise, and when there is high selling pressure (supply), the price tends to fall.
Extremes: This layer helps to identify extreme overbought or oversold conditions. When the oscillator enters the overbought territory, it could indicate that the price is at a high and could potentially reverse. Conversely, if the oscillator enters the oversold territory, it could suggest that the price is at a low and could potentially rebound.
Example of how to use the Momentum Oscillator
The Momentum Oscillator is a sensitive and fast-moving oscillator that adapts quickly to price changes while keeping track of the long-term momentum, making it easier to spot buying or selling opportunities in trends.
Bellcurves
The Bellcurves indicator is a powerful tool for traders that uses statistical analysis to help identify potential market reversals and key support and resistance levels by leveraging the principles of statistical analysis to measure market impulses. The concept behind this tool is the normal distribution, also known as the bell curve, which is a fundamental statistical concept signifying that data tends to cluster around the average or mean value. The "impulses" in the market context refer to significant price movements driven by a high volume of trading activity. These are typically sharp and swift moves either upwards (bullish impulse) or downwards (bearish impulse). These impulses often signify a strong sentiment in the market and can result at the beginning of a new trend or the continuation of an existing one.
In effect, the Bellcurve indicator is designed to filter out minor price fluctuations or 'noise,' allowing traders to focus solely on significant market impulses. This makes it easier for traders to identify key market movements.
Example of how to use the Bellcurve
The Bellcurves uses the principles of statistical analysis to identify significant market impulses and potential market reversals.
█ Why is this Oscillator Toolkit Needed?
The Oscillator Toolkit is a vital asset for traders for several reasons:
Insight into Market Trends: The Oscillator Toolkit provides valuable insight into current market trends. This includes understanding whether the market is bullish (rising) or bearish (falling), as well as identifying potential future price movements.
Identification of Overbought or Oversold Conditions: Oscillators like those in the toolkit can help traders identify when an asset is overbought (potentially overvalued) or oversold (potentially undervalued). This can signal potential market reversals.
Confirmation of Price Patterns: The oscillators in the toolkit can confirm price patterns and trends. For example, if a price pattern suggests a bullish trend, an oscillator can help confirm this by showing rising momentum.
Versatility Across Markets and Timeframes: The Oscillator Toolkit is designed to work across a variety of markets, including stocks, forex, commodities, and cryptocurrencies. It's also effective across different timeframes, from short-term day trading to longer-term investment strategies.
Timely Trade Signals: By providing real-time insights into market conditions and price momentum, the Oscillator Toolkit offers timely signals for trade entries and exits.
Enhancing Trading Strategy: Every trader has a unique approach to the market. The Oscillator Toolkit, with its suite of different oscillators, provides a robust set of tools that can be customized to enhance any trading strategy, whether it's a trend following, swing trading, scalping, or any other approach.
█ Any Alert Function Call
This function allows traders to combine any feature and create customized alerts. These alerts can be set for various conditions and customized according to the trader's strategy or preferences.
█ How are the Oscillators calculated? - Overview
The Toolkit combines many of our existing premium indicators and new technical analysis algorithms to analyze the market. This overview covers how the main features are calculated.
WaveTrend Momentum
The WaveTrend Momentum oscillator operates at its core by comparing the current price to previous prices. If the current price is higher than the previous price, the oscillator value will rise, indicating an uptrend. Conversely, if the current price is lower than the previous price, the oscillator value will fall, indicating a downtrend. To make it unique and useful normalized weighting functions are added.
Leading RSI
The Leading RSI is based on the traditional Relative Strength Index, with an added exploration function that takes into account historical price movements.
Momentum Oscillator
The Momentum oscillator measures how quickly the price is changing, on average, over a certain period, relative to the variability of the price over that same period. It gives higher values when the price is changing rapidly in one direction and lower values when the price is fluctuating or changing more slowly. In addition, other functions, such as market extremes and buying/selling pressure, are factored in.
Bellcurves
The Bellcurves assume that some common historical price data is normally distributed, and once these patterns or moves are found the in the price data, a Bellcurve is formed.
█ In conclusion , the Oscillator Toolkit is an advanced, versatile, and indispensable asset for traders across various markets and timeframes. This innovative collection includes different oscillators, including the WaveTrend Momentum, Leading RSI, Momentum Oscillator, and the Bellcurves Indicator, each serving a unique function in providing valuable insights into the market's behavior.
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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!
Key Levels (Open, Premarket, & Yesterday)OVERVIEW
This indicator automatically identifies and draws recent high-probability support and resistance levels (recent key levels). Specifically, yesterdays highs / lows, premarket highs / lows, as well as yesterdays end of day Volume Weighted Average Price and trader specified Moving Average.
This is most useful on charts with intraday time frames (1 minute, 5 minute etc.) commonly used for day trading. This is not ideal for larger time frames (greater than 1 hour) commonly used for swing trading or identifying larger trends.
INPUTS
You can configure:
Line size, style, and colors
Label colors
Which key levels you want to see
Moving Average Parameters
Market Hours and Time Zone
DEV NOTES
This script illustrates:
A method for iterative management of more complex data objects (not just discrete values) with loops and arrays.
VIX HeatmapVIX HeatMap
Instructions:
- To be used with the S&P500 index (ES, SPX, SPY, any S&P ETF) as that's the input from where the CBOE calculates and measures the VIX. Can also be used with the Dow Jones, Nasdaq, & Nasdaq100.
Description:
- Expected Implied Volatility regime simplified & visualized. Know if we are in a high, medium, or low volatility regime, instantly.
- Ranges from Hot to Cold: The hotter the heat-map, the higher the implied volatility and fear & vice versa.
- The VIX HeatMap, color-maps important VIX levels (7 in this case) in measuring volatility for day trading & swing trading.
Using the VIX HeatMap:
- A LOW level volatility environment: Represented by "cooler" colors (Blue & White) depicts that the level of volatility and fear is low. Percentage moves on the index level are going to be tame and less volatile more often than not. Low fear = low perceived risk.
- A MEDIUM level volatility environment: Represented by "warmer" colors (Green & Yellow) depicts that the markets are transitioning from a calmer period or from a more fearful period. Market volatility here will be higher and provide more volatile swings in price.
- A HIGH level volatility environment: Represented by "hotter" colors (Orange, Red, & Purple) depicts that the markets are very fearful at the moment and will have big swings in both directions. Historically, extreme VIX levels tend to coincide with bottoms but are in no way predictive of the exact timing as the volatile moves can continue for an extended period of time.
- Transitioning between the 7 VIX Zones: Each and every one of these specific VIX zone levels is important.
1. Extreme low: <16
2. Low: 16 to 20
3. Normal: 20 to 24
4. Medium: 24 to 28
5. Med-High: 28 to 32
6. High: 32 to 36
7. Extreme high: >36
- These VIX levels in particular measure volatility changes that have a major impact on switching between smaller time frames and measuring depths of a sell move and vice versa. Each level also behaves as its own support & resistance level in terms of taking a bit of effort to switch regimes, and aids in identifying and measuring the potential depth of pullbacks in bull markets and bounces in bear markets to reveal reversal points.
- Examples of VIX level supports depicted on the chart marked with arrows. From left to right:
1. March 10th: Markets jumped 2 volatility levels in 2 days. The fluctuations from blue to yellow to green where a sign that price action would reverse from the selloff.
2. March 28th: As soon as we move from green to the blue VIX level (<20), markets began to rally and only ended when the volatility level moved sub VIX 16 (white).
3. May 4th & 24th: Next we see the 2 dips where volatility levels went from blue to green (VIX > 20), marked bottoms and reversed higher.
4. June 1st: We see a change in VIX regime yet again into lower VIX level and markets rocket higher.
Knowing the current VIX regime is a very important tool and aid in trading, now easily visualized.
GKD-B Multi-Ticker Baseline [Loxx]Giga Kaleidoscope GKD-B Multi-Ticker Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
This is a special implementation of GKD-B Baseline that allows the trader to input multiple tickers to be passed onto a GKD-BT Multi-Ticker Backtest. This baseline can only be used with the GKD-BT Multi-Ticker Backtests.
GKD-B Multi-Ticker Baseline includes 64 different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types.
█ Volatility Types included
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. You can change the values of the multipliers in the settings as well.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker SCC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Fisher Trasnform
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest
GKD-BT Giga Stacks Backtest
GKD-BT Full Giga Kaleidoscope Backtest
GKD-BT Solo Confirmation Super Complex Backtest
GKD-BT Solo Confirmation Complex Backtest
GKD-BT Solo Confirmation Simple Backtest
GKD-M Baseline Optimizer
GKD-M Accuracy Alchemist
