Hurst Future Lines of Demarcation StrategyJ. M. Hurst introduced a concept in technical analysis known as the Future Line of Demarcation (FLD), which serves as a forward-looking tool by incorporating a simple yet profound line into future projections on a financial chart. Specifically, the FLD is constructed by offsetting the price half a cycle ahead into the future on the time axis, relative to the Hurst Cycle of interest. For instance, in the context of a 40 Day Cycle, the FLD would be represented by shifting the current price data 20 days forward on the chart, offering an idea of future price movement anticipations.
The utility of FLDs extends into three critical areas of insight, which form the backbone of the FLD Trading Strategy:
A price crossing the FLD signifies the confirmation of either a peak or trough formation, indicating pivotal moments in price action.
Such crossings also help determine precise price targets for the upcoming peak or trough, aligned with the cycle of examination.
Additionally, the occurrence of a peak in the FLD itself signals a probable zone where the price might experience a trough, helping to anticipate of future price movements.
These insights by Hurst in his "Cycles Trading Course" during the 1970s, are instrumental for traders aiming to determine entry and exit points, and to forecast potential price movements within the market.
To use the FLD Trading Strategy, for example when focusing on the 40 Day Cycle, a trader should primarily concentrate on the interplay between three Hurst Cycles:
The 20 Day FLD (Signal) - Half the length of the Trade Cycle
The 40 Day FLD (Trade) - The Cycle you want to trade
The 80 Day FLD (Trend) - Twice the length of the Trade Cycle
Traders can gauge trend or consolidation by watching for two critical patterns:
Cascading patterns, characterized by several FLDs running parallel with a consistent separation, typically emerge during pronounced market trends, indicating strong directional momentum.
Consolidation patterns, on the other hand, occur when multiple FLDs intersect and navigate within the same price bandwidth, often reversing direction to traverse this range multiple times. This tangled scenario results in the formation of Pause Zones, areas where price momentum is likely to temporarily stall or where the emergence of a significant trend might be delayed.
This simple FLD indicator provides 3 FLDs with optional source input and smoothing, A-through-H FLD interaction background, adjustable “Close the Trade” triggers, and a simple strategy for backtesting it all.
The A-through-H FLD interactions are a framework designed to classify the different types of price movements as they intersect with or diverge from the Future Line of Demarcation (FLD). Each interaction (designated A through H by color) represents a specific phase or characteristic within the cycle, and understanding these can help traders anticipate future price movements and make informed decisions.
The adjustable “Close the Trade” triggers are for setting the crossover/under that determines the trade exits. The options include: Price, Signal FLD, Trade FLD, or Trend FLD. For example, a trader may want to exit trades only when price finally crosses the Trade FLD line.
Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help:
🏆 @TerryPascoe
🏅 @Hpotter
👏 @parisboy
Ciclos
Yeong RRGThe code outlines a trading strategy that leverages Relative Strength (RS) and Rate of Change (RoC) to make trading decisions. Here's a detailed breakdown of the tactic described by the code:
Ticker and Period Selection: The strategy begins by selecting a stock ticker symbol and defining a period (len) for the calculations, which defaults to 14 but can be adjusted by the user.
Stock and Index Data Retrieval: It fetches the closing price (stock_close) of the chosen stock and calculates its 25-period exponential moving average (stock_ema). Additionally, it retrieves the closing price of the S&P 500 Index (index_close), used as a benchmark for calculating Relative Strength.
Relative Strength Calculation: The Relative Strength (rs) is computed by dividing the stock's closing price by the index's closing price, then multiplying by 100 to scale the result. This metric is used to assess the stock's performance relative to the broader market.
Moving RS Ratio and Rate of Change: The strategy calculates a Simple Moving Average (sma) of the RS over the specified period to get the RS Ratio (rs_ratio). It then computes the Rate of Change (roc) of this RS Ratio over the same period to get the RM Ratio (rm_ratio).
Normalization: The RS Ratio and RM Ratio are normalized using a formula that adjusts their values based on the mean and standard deviation of their respective series over the specified window. This normalization process helps in standardizing the indicators, making them easier to interpret and compare.
Indicator Plotting: The normalized RS Ratio (jdk_rs_ratio) and RM Ratio (jdk_rm_ratio) are plotted on the chart with different colors for visual analysis. A horizontal line (hline) at 100 serves as a reference point, indicating a neutral level for the indicators.
State Color Logic: The script includes a logic to determine the state color (statecolor) based on the previous state color and the current values of jdk_rs_ratio and jdk_rm_ratio. This color coding is intended to visually represent different market states: green for bullish, red for bearish, yellow for hold, and blue for watch conditions.
Signal Generation: The strategy generates buy, sell, hold, and watch signals based on the state color and the indicators' values relative to 100. For example, a buy signal is generated when both jdk_rs_ratio and jdk_rm_ratio are above 100, and the background color is set to green to reflect this bullish condition.
Trade Execution: Finally, the strategy executes trades based on the generated signals. A "BUY" trade is entered when a buy signal is present, and it is closed when a sell signal occurs.
Overall, the strategy uses a combination of RS and RoC indicators, normalized for better comparison, to identify potential buy and sell opportunities based on the stock's performance relative to the market and its momentum.
PS January Barometer BacktesterPS January Barometer Backtester (PS JBB)
The PS January Barometer Backtester (PS JBB) is a simple strategy designed to test the "January Effect" hypothesis in financial markets. This effect theorizes that stock market performance in January can predict the trend for the rest of the year. The script operates on a monthly timeframe, focusing on capturing and analyzing the price movements in January and their subsequent influence on the market until the end of each year.
User Input:
January Trifecta Selectors
These are user-selectable options allowing traders to incorporate additional criteria into their market analysis.
The Santa Claus Rally refers to a stock market increase typically seen in the last week of December through the first two trading days in January.
The First Five Days Indicator assesses market performance during the initial five days of the year.
Script Operation:
The script automatically detects the start of each year, tracks January's high, and signals entry and exit points for trades based on the strategy's logic. It's an excellent tool for traders and investors looking to explore the January Effect's validity and its potential impact on their trading decisions.
In essence, the "PS January Barometer Backtester" is designed to exploit specific seasonal market trends, particularly focusing on the early part of the year, by analyzing and acting upon defined market movements. This strategy is ideal for traders who focus on yearly cyclical patterns and seek to incorporate historical trends into their trading decisions.
Note: This script is intended for educational and research purposes and should not be construed as financial advice. Always conduct your own due diligence before making trading/investment decisions.
Dual Regime Strategy (DRS)/Introduction
The Dual Regime Strategy (DRS) is a composite strategy consisting of two signals, both catering to two different market regimes. The stock market experiences periods of high volatility followed by periods of low volatility, a mean reversion strategy performs well during periods of high volatility while a trend following strategy performs well during periods of low volatility. This is the basis for the mean reversion signal and the momentum signal.
/Signals
1. Mean Reversion Signal
Definition: Mean reversion is a financial theory that suggests that asset prices and financial markets tend to fluctuate around a long-term average or mean value. In other words, when the price of an asset moves significantly away from its historical average, it is likely to revert, or move back, towards that average over time.
Concept: Mean reversion assumes that extreme price movements are temporary and that there is an inherent tendency for prices to return to their historical average or equilibrium level. Traders and investors who follow mean reversion strategies often look for overbought or oversold conditions in the market to identify potential trading opportunities. They believe that when prices deviate too far from their mean, there is a higher probability of a reversal.
DRS strategy: The Keltner Channel is a volatility-based technical indicator that consists of three lines: an upper channel, a lower channel, and a middle channel. It is primarily used for mean reversion strategies. The strategy uses a Keltner channel to trigger the mean reversion signals by identifying potential overbought and oversold conditions.
2. Momentum Signal
Definition: Momentum, in the context of financial markets, refers to the tendency of assets to continue moving in the same direction as their recent past price movements. It is based on the idea that assets that have been performing well recently are more likely to continue performing well, and assets that have been performing poorly are more likely to continue performing poorly.
Concept: Momentum traders and investors seek to identify and ride existing price trends. They believe that there is a persistence in price movements, and they aim to capitalize on this persistence by buying assets that have shown recent strength and selling assets that have shown recent weakness.
DRS strategy: The Exponential Moving Average is used to identify the strength and direction of the existing trend. When the price remains above the moving average, it indicates bullish momentum and vice versa for bearish momentum.
/Results
The backtest results are based on a starting capital of $13,700 (convenient amount for retail traders) with 5% of equity for the position size and pyramiding of 2 to allow one open position at a time for each signal. Commissions vary from broker to broker and they are calculated in different ways so a simple $3 per order is used in backtesting this strategy. Slippage of 3 ticks is used to ensure the results are representative of real world, market order trading. The backtest results are available to view at the bottom of this page.
Note:
Past performance in backtesting does not guarantee future results. Broker execution and market changes can significantly affect strategy performance in live trading.
Originality:
The DRS strategy is unique in its combination of both Momentum Strategy and Mean Reversion Strategy components within a single trading strategy. This dual-regime approach allows the strategy to adapt to different market conditions. Additionally, it incorporates short positions for momentum signals, this ensures that the strategy remains active in bear markets.
1. Mean Reverting Regimes
In mean-reverting regimes, markets exhibit high volatility with prices oscillating around a historical average. The DRS employs the Keltner Channel as a core tool for identifying overbought and oversold conditions, which are prevalent in such regimes.
Detection: The strategy detects mean reverting opportunities when prices deviate significantly from the middle band of the Keltner Channel, signaling an overbought or oversold condition.
Execution: Trades are executed with the expectation that prices will revert to the mean. For example, buying when the price is below the lower band (oversold) and selling when it's above the upper band (overbought).
2. Trending Regimes
In trending regimes, markets move in a persistent direction, either up or down. The DRS utilizes the Exponential Moving Average (EMA) to identify and follow these trends.
Trend Identification: The EMA helps in determining the overall direction of the trend, while the number of days price stays above the moving average indicates the strength of the trend.
Trade Execution: The strategy capitalizes on strong trends by taking positions in the direction of the trend (long positions in uptrends and short positions in downtrends).
/Tickers
This strategy has been backtested primarily on SPY. It also performs well on IWF and QQQ.
Seasonal Market Strategy (SMS)/Introduction
The Seasonal Market Strategy (SMS) is not a technical strategy, it is based on market seasonality and draws heavily from the work of Yale Hirsch, creator of the Stock Trader's Almanac.
/Signals
The strategy is long only. Four different seasonal signals are generated to ensure stock market history, cycles, psychology and patterns are turned into actionable trades. The signals are:
1. Sell in May and Go Away: A strategy suggesting investors sell stocks in May and avoid the market until November, based on historical underperformance during this period.
2. Turn of the Month: Trading tactic that capitalises on the tendency of stock prices to rise at the month's beginning.
3. Santa Claus Rally: Refers to the often-seen increase in stock prices around Christmas and the New Year.
4. Turn Around Tuesday: A pattern where stock markets rebound on Tuesdays following a decline on Mondays.
There is no logic or calculation, just dates for entry and exit. These seasonal patterns are explained in various places online for those who want to understand why they are profitable. Stock Trader's Almanac is a good resource to start with.
/Interpretation
SMS will display an upward blue arrow signifying a buy signal after the candle closes, when entry conditions are met. A label below the arrow will describe which signal was triggered and a number depicting the number of units (they can be deactivated in the style settings). SMS will also display a downwards pink arrow above the candle when the exit conditions are met.
/Strategy Results
The backtest results are based on a starting capital of $13,700 (convenient amount for retail traders) with 5% of equity for the position size and pyramiding of 4 consecutive positions because there are four signals. Because of the large amount of trades, this strategy is suitable with brokers that do not charge commissions, so commissions is set to zero while slippage of 3 ticks is used to ensure the results are representative of real world, market order, end-of-day trading. The backtest results are available to view at the bottom of this page.
NOTE:
Past results are not indicative of future results. The strategy is backtested in ideal conditions, it has no predictive abilities and seasonal trends may breakdown at anytime hence, results from live trading may not achieve the same performance shown here as each trader may introduce subjectivity or interfere with its performance or market conditions might change significantly.
/Tickers
This strategy has been backtested on the Dow Jones Industrial Average ETF with ticker DIA but it also performs well with the SPY ticker which is the ETF for the S&P500.
Martingale + Grid DCA Strategy [YinYangAlgorithms]This Strategy focuses on strategically Martingaling when the price has dropped X% from your current Dollar Cost Average (DCA). When it does Martingale, it will create a Purchase Grid around this location to likewise attempt to get you a better DCA. Likewise following the Martingale strategy, it will sell when your Profit has hit your target of X%.
Martingale may be an effective way to lower your DCA. This is due to the fact that if your initial purchase; or in our case, initial Grid, all went through and the price kept going down afterwards, that you may purchase more to help lower your DCA even more. By doing so, you may bring your DCA down and effectively may make it easier and quicker to reach your target profit %.
Grid trading may be an effective way of reducing risk and lowering your DCA as you are spreading your purchases out over multiple different locations. Likewise we offer the ability to ‘Stack Grids’. What this means, is that if a single bar was to go through 20 grids, the purchase amount would be 20x what each grid is valued at. This may help get you a lower DCA as rather than creating 20 purchase orders at each grid location, we create a single purchase order at the lowest grid location, but for 20x the amount.
By combining both Martingale and Grid DCA techniques we attempt to lower your DCA strategically until you have reached your target profit %.
Before we start, we just want to make it known that first off, this Strategy features 8% Commission Fees, you may change this in the Settings to better reflect the Commission Fees of your exchange. On a similar note, due to Commission Fees being one of the number one profit killers in fast swing trade strategies, this strategy doesn’t focus on low trades, but the ideology of it may result in low amounts of trades. Please keep in mind this is not a bad thing. Since it has the ability to ‘Stack Grid Purchases’ it may purchase more for less and result in more profit, less commission fees, and likewise less # of trades.
Tutorial:
In this example above, we have it set so we Martingale twice, and we use 100 grids between the upper and lower level of each martingale; for a total of 200 Grids. This strategy will take total capital (initial capital + net profit) and divide it by the amount of grids. This will result in the $ amount purchased per grid. For instance, say you started with $10,000 and you’ve made $2000 from this Strategy so far, your total capital is $12,000. If you likewise are implementing 200 grids within your Strategy, this will result in $12,000 / 200 = $60 per grid. However, please note, that the further down the grid / martingale is, the more volume it is able to purchase for $60.
The white line within the Strategy represents your DCA. As the Strategy makes purchases, this will continue to get lower as will your Target Profit price (Blue Line). When the Close goes above your Target Profit price, the Strategy will close all open positions and claim the profit. This profit is then reinvested back into the Strategy, which may exponentially help the Strategy become more profitable the longer it runs for.
In the example above, we’ve zoomed in on the first example. In this we want to focus on how the Strategy got back into the trades shortly after it sold. Currently within the Settings we have it set so our entry is when the Lowest with a length of 3 is less than the previous Lowest with a length of 3. This is 100% customizable and there are multiple different entry options you can choose from and customize such as:
EMA 7 Crossover EMA 21
EMA 7 Crossunder EMA 21
RSI 14 Crossover RSI MA 14
RSI 14 Crossunder RSI MA 14
MFI 14 Crossover MFI MA 14
MFI 14 Crossunder MFI MA 14
Lowest of X Length < Previous Lowest of X Length
Highest of X Length > Previous Highest of X Length
All of these entry options may be tailored to be checked for on a different Time Frame than the one you are currently using the Strategy on. For instance, you may be running the Strategy on the 15 minute Time Frame yet decide you want the RSI to cross over the RSI MA on the 1 Day to be a valid entry location.
Please keep in mind, this Strategy focuses on DCA, this means you may not want the initial purchase to be the best location. You may want to buy when others think it is a good time to sell. This is because there may be strong bearish momentum which drives the price down drastically and potentially getting you a good DCA before it corrects back up.
We will continue to add more Entry options as time goes on, and if you have any in mind please don’t hesitate to let us know.
Now, back to the example above, if we refer to the Yellow circle, you may see that the Lowest of a length of 3 was less than its previous lowest, this triggered the martingales to create their grids. Only a few bars later, the price went into the first grid and went a little lower than its midpoint (Yellow line). This caused about 60% of the first grid to be purchased. Shortly after the price went even lower into this grid and caused the entire first martingale grid to be purchased. However, if you notice, the white line (your DCA) is lower than the midpoint of the first grid. This is due to the fact that we have ‘Stack Grid Purchases’ enabled. This allows the Strategy to purchase more when a single bar crosses through multiple grid locations; and effectively may lower your average more than if it simply executed a purchase order at each grid.
Still looking at the same location within our next example, if we simply increase the Martingale amount from 2 to 3 we can see something strange happens. What happened is our Target Profit price was reached, then our entry condition was met, which caused all of the martingale grids to be formed; however, the price continued to increase afterwards. This may not be a good thing, sure the price could correct back down to these grid locations, but what if it didn’t and it just kept increasing? This would result in this Strategy being stuck and unable to make any trades. For this reason we have implemented a Failsafe in the Settings called ‘Reset Grids if no purchase happens after X bars’.
We have enabled our Failsafe ‘Reset Grids if no purchase happens after X bars’ in this example above. By default it is set to 100 bars, but you can change this to whatever works best for you. If you set it to 0, this Failsafe will be disabled and act like the example prior where it is possible to be stuck with no trades executing.
This Failsafe may be an important way to ensure the Strategy is able to make purchases, however it may also mean the Grids increase in price when it is used, and if a massive correction were to occur afterwards, you may lose out on potential profit.
This Strategy was designed with WebHooks in mind. WebHooks allow you to send signals from the Strategy to your exchange. Simply set up a Custom TradingView Bot within the OKX exchange or 3Commas platform (which has your exchange API), enter the data required from the bot into the settings here, select your bot type in ‘Webhook Alert Type’, and then set up the alert. After that you’re good to go and this Strategy will fully automate all of its trades within your exchange for you. You need to format the Alert a certain way for it to work, which we will go over in the next example.
Add an alert for this Strategy and simply modify the alert message so all it says is:
{{strategy.order.alert_message}}
Likewise change from the Alert ‘Settings’ to Alert ‘Notifications’ at the top of the alert popup. Within the Notifications we will enable ‘Webhook URL’ and then we will pass the URL we are sending the Webhook to. In this example we’ve put OKX exchange Webhook URL, however if you are using 3Commas you’ll need to change this to theirs.
OKX Webhook URL:
www.okx.com
3Commas Webhook URL:
app.3commas.io
Make sure you click ‘Create’ to actually create this alert. After that you’re all set! There are many Tutorials videos you can watch if you are still a little confused as to how Webhook trading works.
Due to the nature of this Strategy and how it is designed to work, it has the ability to never sell unless there it will make profit. However, because of this it also may be stuck waiting in trades for quite a long period of time (usually a few months); especially when your Target Profit % is 15% like in the example above. However, this example above may be a good indication that it may maintain profitability for a long period of time; considering this ‘Deep Backtest’ is from 2017-8-17.
We will conclude the tutorial here. Hopefully you understand how this Strategy has the potential to make calculated and strategic DCA Grid purchases for you and then based on a traditional Martingale fashion, bulk sell at the desired Target Profit Percent.
Settings:
Purchase Settings:
Only Purchase if its lower than DCA: Generally speaking, we want to lower our Average, and therefore it makes sense to only buy when the close is lower than our current DCA and a Purchase Condition is met.
Purchase Condition: When creating the initial buy location you must remember, you want to Buy when others are Fearful and Sell when others are Greedy. Therefore, many of the Buy conditions involve times many would likewise Sell. This is one of the bonuses to using a Strategy like this as it will attempt to get you a good entry location at times people are selling.
Lower / Upper Change Length: This Lower / Upper Length is only used if the Purchase Condition is set to 'Lower Changed' or 'Upper Changed'. This is when the Lowest or Highest of this length changes. Lowest would become lower or Highest would become higher.
Purchase Resolution: Purchase Resolution is the Time Frame that the Purchase Condition is calculated on. For instance, you may only want to start a new Purchase Order when the RSI Crosses RSI MA on the 1 Day, but yet you run this Strategy on the 15 minutes.
Sell Settings:
Trailing Take Profit: Trailing Take Profit is where once your Target Profit Percent has been hit, this will trail up to attempt to claim even more profit.
Target Profit Percent: What is your Target Profit Percent? The Strategy will close all positions when the close price is greater than your DCA * this Target Profit Percent.
Grid Settings:
Stack Grid Purchases: If a close goes through multiple Buy Grids in one bar, should we amplify its purchase amount based on how many grids it went through?
Reset Grids if no purchase happens after X Bars: Set this to 0 if you never want to reset. This is very useful in case the price is very bullish and continues to increase after our Target Profit location is hit. What may happen is, Target Profit location is hit, then the Entry condition is met but the price just keeps increasing afterwards. We may not want to be sitting waiting for the price to drop, which may never happen. This is more of a failsafe if anything. You may set it very large, like 500+ if you only want to use it in extreme situations.
Grid % Less than Initial Purchase Price: How big should our Buy Grid be? For instance if we bought at 0.25 and this value is set to 20%, that means our Buy Grid spans from 0.2 - 0.25.
Grid Amounts: How many Grids should we create within our Buy location?
Martingale Settings:
Amount of Times 'Planned' to Martingale: The more Grids + the More Martingales = the less $ spent per grid, however the less risk. Remember it may be better to be right and take your time than risk too much and be stuck too long.
Martingale Percent: When the current price is this percent less than our DCA, lets create another Buy Grid so we can lower our average more. This will make our profit location less.
Webhook Alerts:
Webhook Alert Type: How should we format this Alert? 3Commas and OKX take their alerts differently, so please select the proper one or your webhooks won't work.
3Commas Webhook Alerts:
3Commas Bot ID: The 3Commas Bot ID is needed so we know which BOT ID we are sending this webhook too.
3Commas Email Token: The 3Commas Email Token is needed for your webhooks to work properly as it is linked to your account.
OKX Webhook Alerts:
OKX Signal Token: This Signal Token is attached to your OKX bot and will be used to access it within OKX.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
SuperTrend Long Strategy +TrendFilterThis strategy aims to identify long (buy) opportunities in the market using the SuperTrend indicator. It utilizes the Average True Range (ATR) and a multiplier to determine the dynamic support levels for entering long positions. This presentation will provide an overview of the strategy's components, explain its usage, and highlight that it focuses on long trades.
Components of the Strategy:
1. ATR Period: This input determines the period used for calculating the Average True Range (ATR). A higher value may result in smoother trend lines but may lag behind recent price changes.
2. Source (src): This input determines the price source used for calculations, with "hl2" (the average of high and low prices) set as the default.
3. ATR Multiplier: This input specifies the multiplier applied to the ATR value to determine the distance of the support levels from the source.
4. Change ATR Calculation Method: This input allows toggling between two methods of ATR calculation: the default method using atr() or a simple moving average (SMA) of ATR values (sma(tr, Periods)).
5. Show Buy/Sell Signals: This input enables or disables the display of buy and sell signals on the chart.
6. Highlighter On/Off: This input controls whether highlighting of up and down trends is displayed on the chart.
7. Bar Coloring On/Off: This input determines whether the bars on the chart are colored based on the trend direction.
8. The "SuperTrend Long STRATEGY" has been enhanced by incorporating a trend filter. A moving average is used as the filter to confirm the prevailing trend before executing trades. This addition effectively reduces false signals and improves the strategy's reliability, all while maintaining its original name.
Strategy Logic:
1. The strategy calculates the upper (up) and lower (dn) trend lines based on the ATR value and the chosen multiplier.
2. The trend variable keeps track of the current trend, with 1 indicating an uptrend and -1 indicating a downtrend.
3. Buy and sell signals are generated based on the change in trend direction.
4. The strategy includes an optional highlighting feature that colors the chart background based on the current trend.
5. Additionally, the bar coloring feature colors the bars based on the direction of the last trend change.
Usage:
1. ATR Period and ATR Multiplier can be adjusted based on the desired sensitivity and risk tolerance.
2. Buy and sell signals can be displayed using the Show Buy/Sell Signals input, providing clear indications of entry and exit points.
3. The Highlighter On/Off input allows users to visually identify the prevailing trend by coloring the chart background.
4. The Bar Coloring On/Off input offers a quick visual reference for the most recent trend change.
Long Strategy:
The SuperTrend Long Strategy is specifically designed to identify long (buy) opportunities. It generates buy signals when the current trend changes from a downtrend to an uptrend, indicating a potential entry point for long positions. The strategy aims to capture upward price movements and maximize profits during bullish market conditions.
The SuperTrend Long Strategy provides traders with a systematic approach to identifying long trade opportunities. By leveraging the SuperTrend indicator and dynamic support levels, this strategy aims to generate buy signals in uptrending markets. Traders can customize the inputs and utilize the visual features to adapt the strategy to their specific trading preferences.
The modification adds a trend filter to the "SuperTrend Long STRATEGY" to improve its effectiveness. The trend filter uses a moving average to confirm the prevailing trend before taking trades. This addition helps filter out false signals and enhances the strategy's reliability without changing its name.
Adaptive Price Channel StrategyThis strategy is an adaptive price channel strategy based on the Average True Range (ATR) indicator and the Average Directional Index (ADX). It aims to identify sideways markets and trends in the price movements and make trades accordingly.
The strategy uses a length parameter for the ATR and ADX indicators, which determines the length of the calculation for these indicators. The strategy also uses an ATR multiplier, which is multiplied by the ATR to determine the upper and lower bounds of the price channel.
The first step of the strategy is to calculate the highest high (HH) and lowest low (LL) over the specified length. The ATR is also calculated over the same length. Then the strategy calculates the positive directional indicator (+DI) and negative directional indicator (-DI) based on the up and down moves in the price, and uses these to calculate the ADX.
If the ADX is less than 25, the market is considered to be in a sideways phase. In this case, if the price closes above the upper bound of the price channel (HH - ATR multiplier * ATR), the strategy enters a long position, and if the price closes below the lower bound of the price channel (LL + ATR multiplier * ATR), the strategy enters a short position.
If the ADX is greater than or equal to 25 and the +DI is greater than the -DI, the market is considered to be in a bullish phase. In this case, if the price closes above the upper bound of the price channel, the strategy enters a long position. If the ADX is greater than or equal to 25 and the +DI is less than the -DI, the market is considered to be in a bearish phase. In this case, if the price closes below the lower bound of the price channel, the strategy enters a short position.
The strategy exits a position after a certain number of bars have passed since the entry, as specified by the exit_length input.
In summary, this strategy attempts to trade in accordance with the prevailing market conditions by identifying sideways markets and trends and making trades based on price movements within a dynamically-adjusted price channel.
This strategy takes a read on the market and either takes a channel strategy or trades volatility based on current trend. Works well on 2, 3 ,4, 12 hour for BTC. It’s my first attempt and creating a strategy. I am very interested in constructive criticism. I will look into better risk management, maybe a trailing stop loss. Other suggestions welcome. This is my first attempt at a strategy.
Here are the settings I used.
Inputs
Length 20
Exit 10
ATR 3.2
Dates I picked when I got into Crypto
Properties
Capital 1000
Order size 2 Contracts
Pyramiding 1
Commission .05
VIX Futures Spread StrategyThis script was an exercise in learning Pinescript and exploring the futures curve of the VIX in relation to SPY. Was deleted by TV, trying to republish it now with updated parameters for slippage and commission and a more detailed description.
"VIX Futures Spread Strategy" is a trading strategy that capitalizes on the spread between the 3-month VIX futures (VIX3M) and the spot VIX index. This strategy is based on the idea that the VIX futures spread can serve as a contrarian indicator of market sentiment, with extreme negative spreads potentially signaling oversold conditions and opportunities for long positions.
Ordinarily the VIX curve is in contango as futures contracts are priced at a premium to the current spot price and are used to hedge future uncertainty in the market. When the spot price of VIX spikes the curve can invert and enter backwardation; this strategy detects this condition and uses it as a trigger to open a long position in SPY. The spread going negative tends to correlate with excessive fear and uncertainty in the short term while expecting lower volatility in the long term, in this case 3 months out.
The strategy is designed to enter a long position when the VIX futures spread is negative and to exit the position when the spread rises above 3 -- when the curve is in contango again. The strategy employs a pyramiding approach, allowing up to 10 additional orders to be placed while the entry condition is met, with each order consisting of 10 contracts. This approach aims to maximize potential profits during periods of favorable market conditions.
In this strategy, the VIX futures spread is calculated as the difference between the 3-month VIX futures (VIX3M) and the spot VIX index. The spread is plotted as a histogram on the chart, with the zero line representing no spread, and horizontal lines at 0 and 3 indicating the entry and exit thresholds, respectively.
The strategy's backtesting settings use an initial capital of HKEX:10 ,000, a commission of 0.5% per trade, and a maximum of 10 pyramiding orders, and a slippage of 2 ticks.
Please note that this strategy is intended for educational purposes and should not be considered as financial advice. Before using this strategy in live trading, make sure to thoroughly test and optimize its parameters to suit your risk tolerance and specific trading conditions.
BTC 4h bot 2.0 StrategyThis is Strategy version of BTC 4h bot 2.0.
Optimized for pairs BTC vs stablecoins, 4h timeframe.
HOW IT WORKS:
Script is based on the fact that there are certain phases of the market when there is a greater probability that BTC will go to one side or the other. To evaluate which phase we are in, the script uses "Main trend" and "Confirmation signals".
Main trend
- Is composed of a combination of several supertrends and moving averages. A Supertrend is a trend following indicator that helps in identifying whether we are in an uptrend or a downtrend. A higher factor is used to capture the main trend and not just small movements. In case the market goes sideways, the Supertrend does not work well, so it is a combination of multiple supertrends along with moving averages to differentiate a real strong trend from a range.
- It can be seen on the graph as a thick solid line.
- In an uptrend is green, in a downtrend red, gray represents the neutral zone.
Confirmation signals
- Are several script-evaluated indicators such as RSI , MACD , ADX and others, which serve to confirm the trend. In this case, it is the opposite way to the Main trend. Confirmation signals are used here to detect small movements. They are trying to capture bullish and bearish price momentum.
- On the graph they are seen as dashed lines above or below the Main trend (in the gray zone they are in the middle).
- It indicates only two signals, green for buy and red for sell.
HOW TO USE IT:
if the Main trend and Confirmation signals are of the same color, it will send a buy or sell signal, depending on which phase of the trend it is in. If the Main trend is e.g. in an uptrend and the market is going up, Confirmation signals should generate a lot of signals. But if the market starts to go in the opposite direction, Confirmation signals should generate fewer signals or none at all, thus reducing the number of wrong trades. In the gray zone of the Main trend it does not open positions.
To close position is possible to use stop loss and take profit or alternative could be to set very high TP value, thereby letting the script close the positions by itself.
The default setting is:
TP: 3.9%
SL: 4.7%.
In this case, it is a strategy to find out how the script worked in the past period. The longest period in which it is possible to test BTCUSD is on the Bitstamp exchange. The script works consistently well over a long period of time, using past probabilities, but this does not guarantee future results.
[Strategy]Turtle's 20day High Low Break StrategyJapanese below / 日本語説明は下記
Overview
I have made this strategy mimicking the legendary traders group, Turtle’s 20days high low break strategy with more options available for take profit(TP) and stop loss(SL) conditions.
The main component of the strategy is same as my indicator, Previous N days/weeks/months high/low(see the link below) and with this strategy, you can backtest previous N days high/low break strategy.
Unlike the indicator, you can specify another previous N days high/low as TP condition. This is because Turtle used 10days low as TP condition for 20days high break buy strategy, according to articles/books about them.
ATR and other factors which is said to be used in their original strategy are not included in this strategy.
Previous N Days/Weeks/Months High Low
What is Turtle?
Turtle is the group of traders founded by Richard Dennis and William Eckhardt to prove their theory that good traders can be trained or not.
It is said that Turtle had made more than 175 million dollars over 5 years and some of the traders has become fund managers or successful individual traders even after the experiment.
What is this strategy like?
The strategy generates long entries once prices break previous N days highs and short entries when previous N days lows broken.
N is user input so you can adjust it for your own strategy.
As mentioned above, you can also specify another set of different previous N days high/low for TP conditions.
e.g. 55 days high(low) break for entry and 20days low(high) break for take profit condition.
How to use it?
What this strategy shows is almost same as the indicator, Previous N days/weeks/months high/low.
It displays previous N days/weeks/months highs and lows and you can set up entry condition based on previous N days high/low.
Previous N weeks/months highs/lows can be used as take profit points when you develop your own strategy based on this.
See the parameters below for the rest of the details.
Parameters
TP condition:
You can select from “Pips”, “When opposite entries” or “Previous high low break”.
When “When opposite entries” selected, the strategy exits the open positions when opposite directional entries happened. e.g. Long positions will be closed when short entries made.
If you would like to exit positions with specific previous N days highs/lows, you can enter N in Previous N days High/Low for TP field with “Previous high low break” selected.
SL condition:
You can select from “Pips” or “Swing High/Low”.
If “Swing High/Low” selected, left bars and right bars need input to determine swing high/low.
Note: If you select “pips” in TP/SL conditions, it currently works only for forex pairs.
What timeframe is the best for this strategy?
As this strategy is for swing trading, longer timeframes are the best.
Base on my quick check upon strategy’s performance over USD pairs in forex, daily timeframe works best, however, it could fit in with lower timeframes such as 4H and 1H by adjusting TP/SL conditions.
Look at the sample result below. The result shows the strategy’s performance for USDJPY for over 40 years on Daily timeframe and it performs fairly good with more than 2 profit factor over long period of time with up-trending equity curve.
It is just a simulation but the data shows Turtle’s strategy still works.
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概要
伝説のトレーダー集団タートルの20日高値・安値ブレイク手法を模倣して作成したストラテジーです。
利益確定や損切り条件を設定可能なようにして、より柔軟性を持たせています。
ストラテジーの主要な構造は過去にリリースしたインジケーターPrevious N days/weeks/months high/lowと同じです(下記リンク参照)。
このストラテジーを使うと、過去N日高値・安値のブレイク手法のバックテストを行うことが可能です。
また、前述のインジケーターとは異なり、このストラテジーでは利益確定条件のために、もう一つ別の過去N日高値・安値を設定することができます。これはタートルが20日高値のブレイクで買いエントリーを行う場合、10日安値ブレイクを手仕舞いの基準として使っていたことからです。
タートルのオリジナル手法ではATRやその他の要素も用いられていたようですが、このストラテジーには含まれていません。
Previous N Days/Weeks/Months High Low
タートルとは何か？
タートルとは、「優れたトレーダーは育成可能か？」の問いを証明するために、投資家リチャード・デニス氏とウィリアム・エックハート氏によって組織されたトレーダー集団です。
タートルは5年間に渡って1億7千5百万ドル以上を稼ぎ出したと言われており、この実験終了後にはヘッジファンドを運営する者や個人投資家として成功したトレーダーを輩出したことで知られています。
このストラテジーの特徴
このストラテジーは、価格が過去N日高値をブレイクした時にロングエントリーを、過去N日安値をブレイクした時にショートエントリーを実行します。
Nはパラメーターで指定可能なので、皆さんの独自の手法開発のために調整することができます。
また、前述の通り、利益確定条件としてエントリー条件とは別の過去N日高値・安値を指定することが可能です。
例：エントリーには55日の高値・安値のブレイクを用い、決済には20日高値・安値のブレイクを用いるなど。
使い方
このストラテジーは前述のインジケーターとほぼ同じ内容のラインを表示します。
過去N日、N週間、Nヶ月の高値・安値を表示でき、エントリーの条件として過去N日高値・安値を指定することができます。
過去N週・Nヶ月高値・安値ラインは利益確定の目安に用いるなど、皆さんが独自の手法を構築するときの参考として使ってください。
その他のパラメーターについては以下の詳細を参照ください。
パラメーター：
TP condition（利益確定条件）:
“Pips(Pips指定)”, “When opposite entries(逆方向エントリー時)” or “Previous N days high low break(過去N日高値・安値)”から選択することができます。
“When opposite entries” を選択した場合、現在のポジションは、現在ポジションとは逆方向のエントリー条件が満たされた時に、決済されます。
例: ロングポジションはショートのエントリーが実行されると同時に決済される。
特定の過去N日高値・安値ブレイクを決済条件としたい場合は、“Previous N days high low break”を選択の上、該当するN日を”Previous N days High/Low for TP”の項目に入力してください。
SL condition(損切り基準):
“Pips(Pips指定)”、“Swing High/Low(スウィングハイ・ロー)”から選択することができます。
“Swing High/Low”選択時は、高値・安値決定に必要な左右のバーの本数を指定します。
注：TP、SL条件でPipsを選択した場合は、現時点では為替通貨ペアのみに機能します。
このストラテジーに最適の時間軸は？
当ストラテジーはスウィングトレードの手法となっているため、長期の時間軸が適しています。
為替のドルストレートペアでの結果を見てみると日足が最も適していますが、利益確定や損切り条件を調整することで、4時間足や1時間足向きにもアレンジできると思います。
上に示したストラテジーの例は、ドル円の日足における過去40年間以上でのバックテストの結果ですが、これだけの長期に渡って右上がりのエクイティカーブとともにプロフィットファクター2近くを維持するなど、かなり良い結果と言えるのではないでしょうか。
これは一つのシミュレーション結果に過ぎませんが、データを見る限りタートルの手法は現在でも機能すると言えるでしょう。
Heikin Ashi SupertrendAbout this Strategy
This supertrend strategy uses the Heikin Ashi candles to generate the supertrend but enters and exits trades using normal candle close prices. If you use the standard built in Supertrend indicator on Heikin Ashi candles, it will produce very unrealistic backtesting results because it uses the Heikin Ashi prices instead of the real prices. However, by signaling the supertrend reversals using Heikin Ashi while using standard candle close prices for the entries and exits, it corrects the backtesting errors and gives you a more realistic equity curve. You should set the chart to use standard candles and then hide them (the strategy creates the candles).
This strategy includes:
Plotting of Heikin Ashi candles
Heikin Ashi Supertrend
Long and Short Entry Signals
Move stop loss after trade is X% in profit
Profit Target
Stop Loss
Built in Alertatron automation
Alertatron Trade Automation Integration
For Alertatron integration, be sure to configure the strategy settings and "Enable Webhook Messages" before creating an alert with {{strategy.order.alert_message}} in the body of your alert message. Be sure to enable webhooks and point it to your Incoming Alertatron webhook URL.
Notes
While this strategy does pretty well during trending markets, It's worth noting that the Buy and Hold ROI is much better during peak times of the bull market
Not financial advice. Do not risk more than you can afford to lose.
[fpemehd] SSL Baseline StrategyHello Guys! Nice to meet you all!
This is my third script!
This Logic is trend following logic, This detects long & short trends based on SSL Hybrid Baseline.
This fits to the longer time frame like 4hr and 1d.
### Long Condition
1. close > SSL Hybrid baseline upper k
- Baseline is the ma of close price. (You can choose ma type and length)
- Upper k is the upper Keltner Channel.
### Short Condition
1. close < SSL Hybrid baseline lower k
- Baseline is the ma of close price. (You can choose ma type and length)
- Lower k is the lower Keltner Channel.
### Etc
1. Added Stoploss based on highest high or lowest low with lookback.
2. Strategy Template is based on @kevinmck100 template. Thank you!
4 Pack Scalping ToolThe 4 Squeeze Scalp tool is a tool that I have developed over the past few years. I was always fascinated by the fact that most people don’t know where price is heading. While Fibonacci and other linear type methods work it never gelled with me. I started by going deep into the fundamentals of momentum with an understanding that an object in motion heading in a particular direction tends to stay heading in that direction (until something derails it). Price, in my opinion, is no different.
Price can move up, down and sideways. And it moves in a wave, getting stronger over time until eventually pulling back and starting over again. In my mind, the compression of price and the relationship of that pressure to various lengths of time as well as RSI, ADX and DMI across these same time frames gives you a view on how the underlying price momentum is building up and releasing. For trading you want to be building a trade when pressure starts to build and you want to take profits when the wave starts to pull back and build for the next cycle.
Each dot represents a length of the momentum indicator and the line inside the oscillator is a weighted composite of the underlying momentum structure for each of the lengths selected. A trade follows the directional alignment of the line (red = down, yellow = neutral / chop, green = up) and the dots should be aligned from the bottom to the top (bright green = very bullish, dark green = neutral / bullish, dark red = neutral / bearish, bright red = very bearish). When the line and the dots are aligned you will have a high probability trade.
The backtest results below are based on 2 years of backtesting, using a 2 contract trade on a 100K account. While the absolute return is not meaningful the win rate and PF are great for a trade on CL on this timeframe. The tool can be used on any asset over any timeframe in a multitude of combinations.
To get access to the tool, please contact the author.
3Commas Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Trend Identifier StrategyTrend Identifier Strategy for 1D BTC.USD
The indicator smoothens a closely following moving average into a polynomial like plot and assumes 4 staged cycles based on the first and the second derivatives. This is an optimized strategy for long term buying and selling with a Sortino Ratio above 3. It is designed to be a more profitable alternative to HODLing. It can be combined with 'Accumulation/Distribution Bands & Signals' and 'Exponential Top and Bottom Finder'.
ET TurnaroundMondayET TurnaroundMonday - two red bars, on Monday go long and exit when close > yeasterday High
Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures, options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
Advantages of this script:
Strategy has high net profit of 255% at backtests
Backtests show high accuracy around 75%
Low Drawdowns of around 14% at backtests
Strategy is sustainable to market slumps and can be used for long-term trading
The strategy provides a large number of entries which is good for diversification
Can be applied to any market and quote currency
Easy to configure user interface settings
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
VXD Cloud Edition for Python-Binance-bots.VXD Cloud Edition for Python-Binance-bots.
to overcome sideways market conditions this cloud configured for low timeframe.
every TA is same as VXD Cloud Edition but custom alert message for bots.
Risk:Reward Calculation
Risk of Ruin Setting can now selected between Fixed $ or %
if Buy your Stoploss will be Swing low
if Sell your Stoploss will be Swing high and can be setting at Pivot Setting
then Auto Position Sizing and TP line will be calculated form there and will show in Orange color line (Draw Position Box is available)
Tailing SL when price greater than RR=1
Alert Setting
{{strategy.order.alert_message}}
Python-Bot
github.com
There are 2 mode : one-way mode and hedge mode is different script in my Github profile.
read README.MD and there's video tutorial in thai language.
Pls study app.py and it's script before deploy for your own safty and your own risk, I'm NOT responsible for your loss.
Stochastic Rsi+Ema - Auto Buy Scalper Scirpt v.0.3Simple concept for a scalping script, written for 5 minute candles, optimized for BTC.
1st script I've created from scratch, somewhat from scratch. Also part of the goal of this one is to hold coin as often as possible, whenever it's sideways or not dropping significantly.
Designed to buy on the stochastic bottoms (K>D and rising, and <17)
Then and sell after 1 of 3 conditions;
a. After the price goes back up at least 1 % and then 1-2 period ema reversal
b. After the rsi reversal (is dropping) and K
Dividend Pension TableHello, you all know about dividend retirement.
It was very difficult to calculate the retirement with dividends by making regular purchases in shares. Thanks to this tool, it is now very easy.
You can start the strategy by choosing the history of the dividend investment, choosing how many units you will receive in a regular amount each month, or the value for money.
In the table on the side, you will see the amount of your regular purchases, dividend income and the amount of your purchases.
Your total investment and savings will also be visible at the top of the chart.
With this table, you will be able to see the analysis of all dividend-paying stocks. Excel era is over :)
Strategy Oil Z ScoreObjective is to find forward looking indicators to find good entries into major index's.
In similar vein to my Combo Z Score script I have implemented one looking at oil and oil volatility. Interestingly the script out performs WITHOUT applying the EMA in longer timeframes but under performs in shorter timeframes, for example 2007 vs 2019. Likely due to the bullish nature of the past decade (by and large). You have some options on the underlying included Oil vs OVX (Best), MOVE vs OVX and VIX vs OVX. Oil vs OVX out performs Combo Z Script. Favours Spy over QQQ or derivations (SPXL etc).
Buy Monday, Exit WednesdayStrategy to go long at end of Monday before market closes and exit before Wednesday close, or at stop loss or take profit percentages
This runs strategy on entering by weekday name and also by session time.
Implemented are also Take Profit and Stop Loss to exit position using custom inputs.
Added stop loss and take profit plot lines
