Dual RSI Differential - Strategy [presentTrading]█ Introduction and How it is Different
The Dual RSI Differential Strategy introduces a nuanced approach to market analysis and trading decisions by utilizing two Relative Strength Index (RSI) indicators calculated over different time periods. Unlike traditional strategies that employ a single RSI and may signal premature or delayed entries, this method leverages the differential between a shorter and a longer RSI. This approach pinpoints more precise entry and exit points, providing a refined tool for traders to exploit market conditions effectively, particularly in overbought and oversold scenarios.
Most important: it is a good eductional code for swing trading.
For beginners, this Pine Script provides a complete function that includes crucial elements such as holding days and the option to configure take profit/stop loss settings:
- Hold Days: This feature ensures that trades are not exited too hastily, helping traders to ride out short-term market volatility. It's particularly valuable for swing trading where maintaining positions slightly longer can lead to capturing significant trends.
- TPSL Condition (None by default): This setting allows traders to focus solely on the strategy's robust entry and exit signals without being constrained by preset profit or loss limits. This flexibility is crucial for learning to adjust strategy settings based on personal risk tolerance and market observations.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 RSI Calculation:
The RSI is a momentum oscillator that measures the speed and change of price movements. It is calculated using the formula:
RSI = 100 - (100 / (1 + RS))
Where RS (Relative Strength) = Average Gain of up periods / Average Loss of down periods.
🔶 Dual RSI Setup:
This strategy involves two RSI indicators:
RSI_Short (RSI_21): Calculated over a short period (21 days).
RSI_Long (RSI_42): Calculated over a longer period (42 days).
Differential Calculation:
The strategy focuses on the differential between these two RSIs:
RSI Differential = RSI_Long - RSI_Short
This differential helps to identify when the shorter-term sentiment diverges from longer-term trends, signaling potential trading opportunities.
BTCUSD Local picuture
🔶 Signal Triggers:
Entry Signal: A buy (long) signal is triggered when the RSI Differential exceeds -5, suggesting strengthening short-term momentum. Conversely, a sell (short) signal occurs when the RSI Differential falls below +5, indicating weakening short-term momentum.
Exit Signal: Trades are generally exited when the RSI Differential reverses past these thresholds, indicating a potential momentum shift.
█ Trade Direction
This strategy accommodates various trading preferences by allowing selections among long, short, or both directions, thus enabling traders to capitalize on diverse market movements and volatility.
█ Usage
The Dual RSI Differential Strategy is particularly suited for:
Traders who prefer a systematic approach to capture market trends.
Those who seek to minimize risks associated with rapid and unexpected market movements.
Traders who value strategies that can be finely tuned to different market conditions.
█ Default Settings
- Trading Direction: Both — allows capturing of upward and downward market movements.
- Short RSI Period: 21 days — balances sensitivity to market movements.
- Long RSI Period: 42 days — smoothens out longer-term fluctuations to provide a clearer market trend.
- RSI Difference Level: 5 — minimizes false signals by setting a moderate threshold for action.
Use Hold Days: True — introduces a temporal element to trading strategy, holding positions to potentially enhance outcomes.
- Hold Days: 5 — ensures that trades are not exited too hastily, helping to ride out short-term volatility.
- TPSL Condition: None — enables traders to focus solely on the strategy's entry and exit signals without preset profit or loss limits.
- Take Profit Percentage: 15% — aims for significant market moves to lock in profits.
- Stop Loss Percentage: 10% — safeguards against large losses, essential for long-term capital preservation.
متذبذبات
Multi Timeframe RSI Buy Sell Strategy [TradeDots]The "Multi Timeframe RSI Buy/Sell Strategy" is a trading strategy that utilizes Relative Strength Index (RSI) indicators from multiple timeframes to provide buy and sell signals.
This strategy allows for extensive customization, supporting up to three distinct RSIs, each configurable with its own timeframe, length, and data source.
HOW DOES IT WORK
This strategy integrates up to three RSIs, each selectable from different timeframes and customizable in terms of length and source. Users have the flexibility to define the number of active RSIs. These selections visualize as plotted lines on the chart, enhancing interpretability.
Users can also manage the moving average of the selected RSI lines. When multiple RSIs are active, the moving average is calculated based on these active lines' average value.
The color intensity of the moving average line changes as it approaches predefined buying or selling thresholds, alerting users to potential signal generation.
A buy or sell signal is generated when all active RSI lines simultaneously cross their respective threshold lines. Concurrently, a label will appear on the chart to signify the order placement.
For those preferring not to display order information or activate the strategy, an "Enable backtest" option is provided in the settings for toggling activation.
APPLICATION
The strategy leverages multiple RSIs to detect extreme market conditions across various timeframes without the need for manual timeframe switching.
This feature is invaluable for identifying divergences across timeframes, such as detecting potential short-term reversals within broader trends, thereby aiding traders in making better trading decisions and potentially avoiding losses.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 60%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TradeDots Stochastic Z-Score
Bullish Divergence Short-term Long Trade FinderThis script is a Bullish divergence trade finder built to find small periods where Bitcoin will likely rise from. It looks for bullish divergence followed by a higher low as long as the hour RSI value is below the 40 mark, if then it will enter an long. It marks out Buy signals on the RSI if the value dips below 'RSI Bull Condition Minimum' (Default 40) on the current time frame in view. It also marks out Sell signals found when the RSI is above the 'RSI Bearish Condition Minimum' (Default 50). The sell signals are bearish divergence that has occurred recently on the RSI. When a long is in play it will sell if it finds bearish divergence or the time frame in view reaches RSI value higher than the 'RSI Sell Value'(Default 75). You can set your stop loss value with the 'Stop loss Percentage' (default 5).
Available inputs:
RSI Period: relative strength measurement length(Typically 14)
RSI Oversold Level: the bottom bar of the RSI (Typically 30)
RSI Overbought Level: the top bar of the RSI (Typically 70)
RSI Bearish Condition Minimum: The minimum value the script will use to look for a pivot high that starts the Bearish condition to Sell (Default 50)
RSI Bearish Condition Sell Min: the minimum value the script will accept a bearish condition (Default 60)
RSI Bull Condition Minimum: the minimum value it will consider a pivot low value in the RSI to find a divergence buy (Default 40)
Look Back this many candles: the amount of candles thee script will look back to find a low value in the RSI (Default 25)
RSI Sell Value: The RSI value of the exit condition for a long when value is reached (Default 75)
Stop loss Percentage: Percentage value for amount to lose (Default 5)
The formula to enter a long is stated below:
If price finds a lower low and there is a higher low found following a lower low and price has just made another dip and price closes lower than the last divergence and Relative strength index hour value is less than 40 enter a long.
The formula to exit a long is stated below:
If the value drops below the stop loss percentage OR (the RSI value is greater than the value of the parameter 'RSI Sell Value' or bearish divergence is found greater than the parameter 'RSI Bearish Condition Minimum' )
This script was built from much strategy testing on BTC but works with alts (occasionally) also. It is most successful to my knowledge using the 15 min and 7 min time frames with default values. Hope it helps! Follow for further possible updates to this script or other entry or exit strategies.
snapshot:
I only have a Pro trading view account so I cannot share a larger data set about this script because the buy signals happen pretty rarely. The most amount that I could find within a view for me was 40 trades within a viewable time. The suggested/default parameters that I have do not occur very often so it limits the data set. Adjustments can be made to the parameters so that trades can be entered more often. The scripts success is dependent on the values of the parameters set by the user. This script was written to be used for BTC/USD or BTC/USDT trading. I am unable to share a larger dataset without putting out results that are intended to fail or having a premium account so reaching the 100 trade minimum is not possible with my account.
Stochastic Z-Score Oscillator Strategy [TradeDots]The "Stochastic Z-Score Oscillator Strategy" represents an enhanced approach to the original "Buy Sell Strategy With Z-Score" trading strategy. Our upgraded Stochastic model incorporates an additional Stochastic Oscillator layer on top of the Z-Score statistical metrics, which bolsters the affirmation of potential price reversals.
We also revised our exit strategy to when the Z-Score revert to a level of zero. This amendment gives a much smaller drawdown, resulting in a better win-rate compared to the original version.
HOW DOES IT WORK
The strategy operates by calculating the Z-Score of the closing price for each candlestick. This allows us to evaluate how significantly the current price deviates from its typical volatility level.
The strategy first takes the scope of a rolling window, adjusted to the user's preference. This window is used to compute both the standard deviation and mean value. With these values, the strategic model finalizes the Z-Score. This determination is accomplished by subtracting the mean from the closing price and dividing the resulting value by the standard deviation.
Following this, the Stochastic Oscillator is utilized to affirm the Z-Score overbought and oversold indicators. This indicator operates within a 0 to 100 range, so a base adjustment to match the Z-Score scale is required. Post Stochastic Oscillator calculation, we recalibrate the figure to lie within the -4 to 4 range.
Finally, we compute the average of both the Stochastic Oscillator and Z-Score, signaling overpriced or underpriced conditions when the set threshold of positive or negative is breached.
APPLICATION
Firstly, it is better to identify a stable trading pair for this technique, such as two stocks with considerable correlation. This is to ensure conformance with the statistical model's assumption of a normal Gaussian distribution model. The ideal performance is theoretically situated within a sideways market devoid of skewness.
Following pair selection, the user should refine the span of the rolling window. A broader window smoothens the mean, more accurately capturing long-term market trends, while potentially enhancing volatility. This refinement results in fewer, yet precise trading signals.
Finally, the user must settle on an optimal Z-Score threshold, which essentially dictates the timing for buy/sell actions when the Z-Score exceeds with thresholds. A positive threshold signifies the price veering away from its mean, triggering a sell signal. Conversely, a negative threshold denotes the price falling below its mean, illustrating an underpriced condition that prompts a buy signal.
Within a normal distribution, a Z-Score of 1 records about 68% of occurrences centered at the mean, while a Z-Score of 2 captures approximately 95% of occurrences.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
The following is the default setup on EURAUD 1h timeframe
Rolling Window: 80
Z-Score Threshold: 2.8
Signal Cool Down Period: 5
Stochastic Length: 14
Stochastic Smooth Period: 7
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 40%
FURTHER IMPLICATION
The Stochastic Oscillator imparts minimal impact on the current strategy. As such, it may be beneficial to adjust the weightings between the Z-Score and Stochastic Oscillator values or the scale of Stochastic Oscillator to test different performance outcomes.
Alternative momentum indicators such as Keltner Channels or RSI could also serve as robust confirmations of overbought and oversold signals when used for verification.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
Fine-tune Inputs: Fourier Smoothed Volume zone oscillator WFSVZ0Use this Strategy to Fine-tune inputs for the (W&)FSVZ0 Indicator.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame.
MEANINGFUL DESCRIPTION:
The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
The Wavelet & Fourier Smoothed Volume Zone Oscillator (W&)FSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the Discrete Fourier Transform . Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends.
By combining the Wavalet and Fourier aproximation with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions.
HOW TO USE THE INDICATOR:
The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well)
The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend.
HOW TO USE THE STRATEGY:
Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M.
When I ndicator/Strategy returns 0 or natural trend , Strategy Closes All it's positions.
ORIGINALITY & USFULLNESS:
Personal combination of Fourier and Wavalet aproximation of a price which results in less noise Volume Zone Oscillator.
The Wavelet Transform is a powerful mathematical tool for signal analysis, particularly effective in analyzing signals with varying frequency or non-stationary characteristics. It dissects a signal into wavelets, small waves with varying frequency and limited duration, providing a multi-resolution analysis. This approach captures both frequency and location information, making it especially useful for detecting changes or anomalies in complex signals.
The Discrete Fourier Transform (DFT) is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element.
This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding.
DETAILED DESCRIPTION:
My detailed description of the indicator and use cases which I find very valuable.
What is oscillator?
Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets.
What is volume zone oscillator?
Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price.
Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average.
What does this mean?
If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely.
If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely.
Rising means that VZO on close is higher than the previous day.
Falling means that VZO on close is lower than the previous day.
What if VZO is falling above 0 line?
It means we have a high probability of a bearish trend.
Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend.
In the next Image you can see that trend is negative on 4h, negative on 12h and positive on 1D. That means trend is negative.
I am sorry, the chart is a bit messy. The idea is to use the indicator over more than 1 Timeframe.
What is approximation and smoothing?
They are mathematical concepts for making a discrete set of numbers a
continuous curved line.
Fourier and Wavelet approximation of a close price are taken from aprox library.
Key Features:
You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length.
Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification.
Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics.
Choose between the traditional Fast Fourier Transform (FFT) , the innovative Double Discrete Fourier Transform (DTF32) and Wavelet soothed Fourier soothed price series to suit your analytical needs.
Image of Wavelet transform with FAST settings, Double Fourier transform with FAST settings. Improved noice reduction with SLOW settings, and standard FSVZO with SLOW settings:
Fast setting are setting by default:
VZO length = 2
NoiceR max Length = 2
Slow settings are:
VZO length = 5 or 7
NoiceR max Length = 8
As you can see fast setting are more volatile. I suggest averaging fast setting on 4h 12h 1d 2d 3d 4d W and M Timeframe to get a clear view on market trend.
What if I want long only when VZO is rising and above 15 not 0?
You have set Setting VzoDifference to 15. That reduces the number of trend changes.
Example of W&FSVZO with VzoDifference 15 than 0:
VZO crossed 0 line but not 15 line and that's why Indicator returns 0 in one case an 1 in another.
What is Smooth length setting?
A way of calculating Bullish or Bearish (W&)FSVZO .
If smooth length is 2 the trend is rising if:
rising = VZO > ta.ema(VZO, 2)
Meaning that we check if VZO is higher that exponential average of the last 2 elements.
If smooth length is 1 the trend is rising if:
rising = VZO_ > VZO_
Use this Strategy to fine-tune inputs for the (W&)FSVZO Indicator.
(Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data)
I suggest using " Close all " input False when fine-tuning Inputs for 1 TimeFrame . When you export data to Excel/Numbers/GSheets I suggest using " Close all " input as True , except for the lowest TimeFrame . I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
RSI Strategy with Manual TP and SL 19/03/2024This TradingView script implements a simple RSI (Relative Strength Index) strategy with manual take profit (TP) and stop-loss (SL) levels. Let's break down the script and analyze its components:
RSI Calculation: The script calculates the RSI using the specified length parameter. RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and typically values above 70 indicate overbought conditions while values below 30 indicate oversold conditions.
Strategy Parameters:
length: Length of the RSI period.
overSold: Threshold for oversold condition.
overBought: Threshold for overbought condition.
trail_profit_pct: Percentage for trailing profit.
Entry Conditions:
For a long position: RSI crosses above 30 and the daily close is above 70% of the highest close in the last 50 bars.
For a short position: RSI crosses below 70 and the daily close is below 130% of the lowest close in the last 50 bars.
Entry Signals:
Long entry is signaled when both conditions for a long position are met.
Short entry is signaled when both conditions for a short position are met.
Manual TP and SL:
Take profit and stop-loss levels are calculated based on the entry price and the specified percentage.
For long positions, the take profit level is set above the entry price and the stop-loss level is set below the entry price.
For short positions, the take profit level is set below the entry price and the stop-loss level is set above the entry price.
Strategy Exits:
Exit conditions are defined for both long and short positions using the calculated take profit and stop-loss levels.
Chart Analysis:
This strategy aims to capitalize on short-term momentum shifts indicated by RSI crossings combined with daily price movements.
It utilizes manual TP and SL levels, providing traders with flexibility in managing their positions.
The strategy may perform well in ranging or oscillating markets where RSI signals are more reliable.
However, it may encounter challenges in trending markets where RSI can remain overbought or oversold for extended periods.
Traders should backtest this strategy thoroughly on historical data and consider optimizing parameters to suit different market conditions.
Risk management is crucial, so traders should carefully adjust TP and SL percentages based on their risk tolerance and market volatility.
Overall, this strategy provides a structured approach to trading based on RSI signals while allowing traders to customize their risk management. However, like any trading strategy, it should be used judiciously and in conjunction with other forms of analysis and risk management techniques.
NASDAQ 100 Peak Hours StrategyNASDAQ 100 Peak Hours Trading Strategy
Description
Our NASDAQ 100 Peak Hours Trading Strategy leverages a carefully designed algorithm to trade within specific hours of high market activity, particularly focusing on the first two hours of the trading session from 09:30 AM to 11:30 AM GMT-5. This period is identified for its increased volatility and liquidity, offering numerous trading opportunities.
The strategy incorporates a blend of technical indicators to identify entry and exit points for both long and short positions. These indicators include:
Exponential Moving Averages (EMAs) : A short-term 9-period EMA and a longer-term 21-period EMA to determine the market trend and momentum.
Relative Strength Index (RSI) : A 14-period RSI to gauge the market's momentum.
Average True Range (ATR) : A 14-period ATR to assess market volatility and to set dynamic stop losses and trailing stops.
Volume Weighted Average Price (VWAP) : To identify the market's average price weighted by volume, serving as a benchmark for the trading day.
Our strategy uniquely applies a volatility filter using the ATR, ensuring trades are only executed in conditions that favor our setup. Additionally, we consider the direction of the EMAs to confirm the market's trend before entering trades.
Originality and Usefulness
This strategy stands out by combining these indicators within the NASDAQ 100's peak hours, exploiting the specific market conditions that prevail during these times. The inclusion of a volatility filter and dynamic stop-loss mechanisms based on the ATR provides a robust method for managing risk.
By focusing on the early trading hours, the strategy aims to capture the initial market movements driven by overnight news and the opening rush, often characterized by higher volatility. This approach is particularly useful for traders looking to maximize gains from short-term fluctuations while limiting exposure to longer-term market uncertainty.
Strategy Results
To ensure the strategy's effectiveness and reliability, it has undergone rigorous backtesting over a significant dataset to produce a sample size of more than 100 trades. This testing phase helps in identifying the strategy's potential in various market conditions, its consistency, and its risk-to-reward ratio.
Our backtesting adheres to realistic trading conditions, accounting for slippage and commission to reflect actual trading scenarios accurately. The strategy is designed with a conservative approach to risk management, advising not to risk more than 5-10% of equity on a single trade. The default settings in the script align with these principles, ensuring that users can replicate our tested conditions.
Using the Strategy
The strategy is designed for simplicity and ease of use:
Trade Hours : Focuses on 09:30 AM to 11:30 AM GMT-5, during the NASDAQ 100's peak activity hours.
Entry Conditions : Trades are initiated based on the alignment of EMAs, RSI, VWAP, and the ATR's volatility filter within the designated time frame.
Exit Conditions : Includes dynamic trailing stops based on ATR, a predefined time exit strategy, and a trend reversal exit condition for risk management.
This script is a powerful tool for traders looking to leverage the NASDAQ 100's peak hours, providing a structured approach to navigating the early market hours with a robust set of criteria for making informed trading decisions.
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
How to force strategies fire exit alerts not reversalsPineScript has gone a long way, from very simple and little-capable scripting language to a robust coding platform with reliable execution endpoints. However, this one small intuitivity glitch is still there and is likely to stay, because it is traditionally justified and quite intuitive for significant group of traders. I'm sharing this workaround in response to frequent inquiries about it.
What's the glitch? When setting alerts on strategies to be synchronized with TradingView's Strategy Tester events, using simple alert messages such as "buy" or "sell" based on entry direction seems straightforward by inserting {{strategy.order.action}} into the Create Alert's "Message" field. Because "buy" or "sell" are exactly the strings produced by {{strategy.order.action}} placeholder. However, complications arise when attempting to EXIT positions without reversing, whether triggered by price levels like Stop Loss or Take Profit, or logical conditions to close trades. Those bricks fall apart, because on such events {{strategy.order.action}} sends the same "sell" for exiting buy positions and "buy" for exiting sell positions, instead of something more differentiating like "closebuy" or "closesell". As a result reversal trades are opened, instead of simply closing the open ones.
This convention harkens back to traditional stock market practices, where traders either bought shares to enter positions or sold them to exit. However, modern trading encompasses diverse instruments like CFDs, indices, and Forex, alongside advanced features such as Stop Loss, reshaping the landscape. Despite these advancements, the traditional nomenclature persists.
And is poised to stay on TradingView as well, so we need a workaround to get a simple strategy going. Luckily it is here and is called alert_message . It is a parameter, which needs to be added into each strategy.entry() / strategy.exit() / strategy.close() function call - each call, which causes Strategy Tester to produce entry or exit orders. As in this example script:
line 12: strategy.entry(... alert_message ="buy")
line 14: strategy.entry(... alert_message ="sell")
line 19: strategy.exit(... alert_message ="closebuy")
line 20: strategy.exit(... alert_message ="closesell")
line 24: strategy.close(... alert_message ="closebuy")
line 26: strategy.close(... alert_message ="closesell")
These alert messages are compatible with the Alerts Syntax of TradingConnector - a tool facilitating auto-execution of TradingView alerts in MetaTrader 4 or 5. Yes, simple alert messages like "buy" / "sell" / "closebuy" / "closesell" suffice to carry the execution of simple strategy, without complex JSON files with multiple ids and such. Other parameters can be added (actually plenty), but they are only option and that's not a part of this story :)
Last thing left to do is to replace "Message" in Create Alert popup with {{strategy.order.alert_message}} . This placeholder transmits the string defined in the PineScript alert_message= parameter, as outlined in this publication. With this workaround, executing closing alerts becomes seamless within PineScript strategies on TradingView.
Disclaimer: this content is purely educational, especially please don't pay attention to backtest results on any timeframe/ticker.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
Bollinger and Stochastic with Trailing Stop - D.M.P.This trading strategy combines Bollinger Bands and the Stochastic indicator to identify entry opportunities in oversold and overbought conditions in the market. The aim is to capitalize on price rebounds from the extremes defined by the Bollinger Bands, with the confirmation of the Stochastic to maximize the probability of success of the operations.
Indicators Used
- Bollinger Bands Used to measure volatility and define oversold and overbought levels. When the price touches or breaks through the lower band, it indicates a possible oversold condition. Similarly, when it touches or breaks through the upper band, it indicates a possible overbought condition.
- Stochastic: A momentum oscillator that compares the closing price of an asset with its price range over a certain period. Values below 20 indicate oversold, while values above 80 indicate overbought.
Strategy Logic
- Long Entry (Buy): A purchase operation is executed when the price closes below the lower Bollinger band (indicating oversold) and the Stochastic is also in the oversold zone.
- Short Entry (Sell): A sell operation is executed when the price closes above the upper Bollinger band (indicating overbought) and the Stochastic is in the overbought zone.
PresentTrend RMI Synergy - Strategy [presentTrading] █ Introduction and How it is Different
The "PresentTrend RMI Synergy Strategy" is the combined power of the Relative Momentum Index (RMI) and a custom presentTrend indicator. This strategy introduces a multifaceted approach, integrating momentum analysis with trend direction to offer traders a more nuanced and responsive trading mechanism.
BTCUSD 6h L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The "PresentTrend RMI Synergy Strategy" intricately combines the Relative Momentum Index (RMI) and a custom SuperTrend indicator to create a powerful tool for traders.
🔶 Relative Momentum Index (RMI)
The RMI is a variation of the Relative Strength Index (RSI), but instead of using price closes against itself, it measures the momentum of up and down movements in price relative to previous prices over a given period. The RMI for a period length `N` is calculated as follows:
RMI = 100 - 100/ (1 + U/D)
where:
- `U` is the average upward price change over `N` periods,
- `D` is the average downward price change over `N` periods.
The RMI oscillates between 0 and 100, with higher values indicating stronger upward momentum and lower values suggesting stronger downward momentum.
RMI = 21
RMI = 42
For more information - RMI Trend Sync - Strategy :
🔶 presentTrend Indicator
The presentTrend indicator combines the Average True Range (ATR) with a moving average to determine trend direction and dynamic support or resistance levels. The presentTrend for a period length `M` and a multiplier `F` is defined as:
- Upper Band: MA + (ATR x F)
- Lower Band: MA - (ATR x F)
where:
- `MA` is the moving average of the close price over `M` periods,
- `ATR` is the Average True Range over the same period,
- `F` is the multiplier to adjust the sensitivity.
The trend direction switches when the price crosses the presentTrend bands, signaling potential entry or exit points.
presentTrend length = 3
presentTrend length = 10
For more information - PresentTrend - Strategy :
🔶 Strategy Logic
Entry Conditions:
- Long Entry: Triggered when the RMI exceeds a threshold, say 60, indicating a strong bullish momentum, and when the price is above the presentTrend, confirming an uptrend.
- Short Entry: Occurs when the RMI drops below a threshold, say 40, showing strong bearish momentum, and the price is below the present trend, indicating a downtrend.
Exit Conditions with Dynamic Trailing Stop:
- Long Exit: Initiated when the price crosses below the lower presentTrend band or when the RMI falls back towards a neutral level, suggesting a weakening of the bullish momentum.
- Short Exit: Executed when the price crosses above the upper presentTrend band or when the RMI rises towards a neutral level, indicating a reduction in bearish momentum.
Equations for Dynamic Trailing Stop:
- For Long Positions: The exit price is set at the lower SuperTrend band once the entry condition is met.
- For Short Positions: The exit price is determined by the upper SuperTrend band post-entry.
These dynamic trailing stops adjust as the market moves, providing a method to lock in profits while allowing room for the position to grow.
This strategy's strength lies in its dual analysis approach, leveraging RMI for momentum insights and presentTrend for trend direction and dynamic stops. This combination offers traders a robust framework to navigate various market conditions, aiming to capture trends early and exit positions strategically to maximize gains and minimize losses.
█ Trade Direction
The strategy provides flexibility in trade direction selection, offering "Long," "Short," or "Both" options to cater to different market conditions and trader preferences. This adaptability ensures that traders can align the strategy with their market outlook, risk tolerance, and trading goals.
█ Usage
To utilize the "PresentTrend RMI Synergy Strategy," traders should input their preferred settings in the Pine Script™ and apply the strategy to their charts. Monitoring RMI for momentum shifts and adjusting positions based on SuperTrend signals can optimize entry and exit points, enhancing potential returns while managing risk.
█ Default Settings
1. RMI Length: 21
The 21-period RMI length strikes a balance between capturing momentum and filtering out market noise, offering a medium-term outlook on market trends.
2. Super Trend Length: 7
A SuperTrend length of 7 periods is chosen for its responsiveness to price movements, providing a dynamic framework for trend identification without excessive sensitivity.
3. Super Trend Multiplier: 4.0
The multiplier of 4.0 for the SuperTrend indicator widens the trend bands, focusing on significant market moves and reducing the impact of minor fluctuations.
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The "PresentTrend RMI Synergy Strategy" represents a significant step forward in trading strategy development, blending momentum and trend analysis in a unique way. By providing a detailed framework for understanding market dynamics, this strategy empowers traders to make more informed decisions.
CCI based support and resistance strategy
WARNING:
Commissions and slippage has not been considered! Don’t take it easy adding commissions and slippage could turns a fake-profitable strategy to a real disaster.
We consider account size as 10k and we enter 1000 for each trade.
Less than 100 trades is too small sample community and it’s not reliable, Also the performance of the past do not guarantee future performance. This result was handpicked by author and will differ by other timeframes, instruments and settings.
*PLEASE SHARE YOUR SETTINGS THAT WORK WITH THE COMMUNITY.
Introduction:
The CCI-based dynamic support and resistance is a "Bands and Channels" kind of indicator consisting an upper and lower band. This is a strategy which uses CCI-based (Made by me) indicator to execute trades.
SL and TP are calculated based on max ATR during last selected time period. You can edit strategy settings using "Ksl", "Ktp" and the other button for time period. “KSL” and “KTP” are 2.5 and 5 by default.
Bands are calculated regarding CCI previous high and low pivot. CCI length, right pivot length and left pivot length are 50.
A dynamic support and resistance has been calculated using last upper-cci minus a buffer and last lower-cci plus the buffer. The buffer is 10.
If "Trend matter?" button is on you can detect trend by color of the upper and lower line. Green is bullish and red is bearish! "Trend matter?" is on.
The "show mid?" button makes mid line visible, which is average of upper and lower lines, visible. The button is not active by default.
Reaction to the support could be a buy signal while a reaction to the resistance could interpreted as a sell signal.
How this strategy work?
Donald Lambert, a technical analyst, created the CCI, or Commodity Channel Index, which he first published in 1980. CCI is calculated regarding CCI can be used both as trend-detector or an oscillator. As an oscillator most traders believe in static predefined levels. Overbought and oversold candles which are clear in the chart could be used as sell and buy signals.
During my trading career I’ve noticed that there might be some reversal points for the CCI. I believe CCI could have to potential to reverse more from lately reversal point. Of course, just like other trading strategies we are talking about probabilities. We do not expect a win trade each time.
On price chart
Now this the question! What price should the instrument reach that CCI turns to be equal to our reversing aim for CCI? Imagine we have found last important bearish reversal of CCI in 200. Now, if we need the CCI to be 200 what price should we wait for?
How to calculate?
This is the CCI formula:
CCI = (Typical Price - SMA of TP) / (0.015 x Mean Deviation)
Where, Typical Price (TP) = (High + Low + Close)/3
For probable reversing points, high and low pivots of 50 bars have been used.
So we do have an Upper CCI and a Lower CCI. They are valid until the next pivot is available.
By relocating factors in CCI formula you can reach the “Typical Price”.
“
Typical Price = CCI (0.015 * Mean Deviation) + SMA of TP
So we could have a Support or Resistance by replacing CCI with Upper and Lower CCI.
A buy signal is valid if the trend is bullish (or “trend matter” is off) and lowest low of last 2 candles is lower than support and close is greater than both support and open.
A Sell signal is produced in opposite situation.
There are 2+1 options for trend!
Trend matter box is on by default, which means we’ll just open trades in direction of the trend. It’s available to turn it off.
Other 2 options are cross and slope. Cross calculated by comparing fast SMA and slow SMA. The slope one differentiate slow SMA to last “n” one.
Considering last day and today highest ATR as the ATR to calculating SL and TP is our unique technique.
Monthly Performance Table by Dr. MauryaWhat is this ?
This Strategy script is not aim to produce strategy results but It aim to produce monthly PnL performance Calendar table which is useful for TradingView community to generate a monthly performance table for Own strategy.
So make sure to read the disclaimer below.
Why it is required to publish?:
I am not satisfied with the monthly performance available on TV community script. Sometimes it is very lengthy in code and sometimes it showing the wrong PNL for current month.
So I have decided to develop new Monthly performance or return in value as well as in percentage with highly flexible to adjust row automatically.
Features :
Accuracy increased for current month PnL.
There are 14 columns and automatically adjusted rows according to available trade years/month.
First Column reflect the YEAR, from second column to 13 column reflect the month and 14 column reflect the yearly PnL.
In tabulated data reflects the monthly PnL (value and (%)) in month column and Yearly PnL (value and (%)) in Yearly column.
Various color input also added to change the table look like background color, text color, heading text color, border color.
In tabulated data, background color turn green for profit and red for loss.
Copy from line 54 to last line as it is in your strategy script.
Credit: This code is modified and top up of the open-source code originally written by QuantNomad. Thanks for their contribution towards to give base and lead to other developers. I have changed the way of determining past PnL to array form and keep separated current month and year PnL from array. Which avoid the false pnl in current month.
Strategy description:
As in first line I said This strategy is aim to provide monthly performance table not focused on the strategy. But it is necessary to explain strategy which I have used here. Strategy is simply based on ADX available on TV community script. Long entry is based on when the difference between DIPlus and ADX is reached on certain value (Set value in Long difference in Input Tab) while Short entry is based on when the difference between DIMinus and ADX is reached on certain value (Set value in Short difference in Input Tab).
Default Strategy Properties used on chart(Important)
This script backtest is done on 1 hour timeframe of NSE:Reliance Inds Future cahrt, using the following backtesting properties:
Balance (default): 500 000 (default base currency)
Order Size: 1 contract
Comission: 20 INR per Order
Slippage: 5 tick
Default setting in Input tab
Len (ADX length) : 14
Th (ADX Threshhold): 20
Long Difference (DIPlus - ADX) = 5
Short Difference (DIMinus - ADX) = 5
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
Disclaimer:
This script not provide indicative of any future results.
This script don’t provide any financial advice.
This strategy is only for the readymade snippet code for monthly PnL performance calender table for any own strategy.
RSI & Backed-Weighted MA StrategyRSI & MA Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators that work best together: the Relative Strength Index (RSI) and the Moving Average (MA). We're going to use the RSI as a trend-follower indicator, rather than a reversal indicator as most are used to. To the signals sent by the RSI, we'll add a condition on the chart's MA, filtering out irrelevant signals and considerably increasing our winning rate. This is a medium/long-term strategy. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RSI :
The RSI is one of the best-known and most widely used indicators in trading. Its purpose is to warn traders when an asset is overbought or oversold. It was designed to send reversal signals, but we're going to use it as a trend indicator by increasing its length to 20. The RSI formula is as follows :
RSI (n) = 100 - (100 / (1 + (H (n)/L (n))))
With n the length of the RSI, H(n) the average of days closing above the open and L(n) the average of days closing below the open.
MA :
The Moving Average is also widely used in technical analysis, to smooth out variations in an asset. The SMA formula is as follows :
SMA (n) = (P1 + P2 + ... + Pn) / n
where n is the length of the MA.
However, an SMA does not weight any of its terms, which means that the price 10 days ago has the same importance as the price 2 days ago or today's price... That's why in this strategy we use a RWMA, i.e. a back-weighted moving average. It weights old prices more heavily than new ones. This will enable us to limit the impact of short-term variations and focus on the trend that was dominating. The RWMA used weights :
The 4 most recent terms by : 100 / (4+(n-4)*1.30)
The other oldest terms by : weight_4_first_term*1.30
So the older terms are weighted 1.30 more than the more recent ones. The moving average thus traces a trend that accentuates past values and limits the noise of short-term variations.
PARAMETERS :
RSI Length : Lenght of RSI. Default is 20.
MA Type : Choice between a SMA or a RWMA which permits to minimize the impact of short term reversal. Default is RWMA.
MA Length : Length of the selected MA. Default is 19.
RSI Long Signal : Minimum value of RSI to send a LONG signal. Default is 60.
RSI Short signal : Maximum value of RSI to send a SHORT signal. Default is 40.
ROC MA Long Signal : Maximum value of Rate of Change MA to send a LONG signal. Default is 0.
ROC MA Short signal : Minimum value of Rate of Change MA to send a SHORT signal. Default is 0.
TP activation in multiple of ATR : Threshold value to trigger trailing stop Take Profit. This threshold is calculated as multiple of the ATR (Average True Range). Default value is 5 meaning that to trigger the trailing TP the price need to move 5*ATR in the right direction.
Trailing TP in percentage : Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases. Default is 3%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD with a timeframe set to 6h. Parameters are set as follows :
MA type: RWMA
MA Length: 19
RSI Long Signal: >60
RSI Short Signal : <40
ROC MA Long Signal : <0
ROC MA Short Signal : >0
TP Activation in multiple ATR : 5
Trailing TP in percentage : 3
ENTER RULES :
The principle is very simple:
If the asset is overbought after a bear market, we are LONG.
If the asset is oversold after a bull market, we are SHORT.
We have defined a bear market as follows : Rate of Change (20) RWMA < 0
We have defined a bull market as follows : Rate of Change (20) RWMA > 0
The Rate of Change is calculated using this formula : (RWMA/RWMA(20) - 1)*100
Overbought is defined as follows : RSI > 60
Oversold is defined as follows : RSI < 40
LONG CONDITION :
RSI > 60 and (RWMA/RWMA(20) - 1)*100 < -1
SHORT CONDITION :
RSI < 40 and (RWMA/RWMA(20) - 1)*100 > 1
EXIT RULES FOR WINNING TRADE :
We have a trailing TP allowing us to exit once the price has reached the "TP Activation in multiple ATR" parameter, i.e. 5*ATR by default in the profit direction. TP trailing is triggered at this point, not limiting our gains, and securing our profits at 3% below this trigger threshold.
Remember that the True Range is : maximum(H-L, H-C(1), C-L(1))
with C : Close, H : High, L : Low
The Average True Range is therefore the average of these TRs over a length defined by default in the strategy, i.e. 20.
RISK MANAGEMENT :
This strategy may incur losses. The method for limiting losses is to set a Stop Loss equal to 3*ATR. This means that if the price moves against our position and reaches three times the ATR, we exit with a loss.
Sometimes the ATR can result in a SL set below 10% of the trade value, which is not acceptable. In this case, we set the SL at 10%, limiting losses to a maximum of 10%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
EUR/USD 45 MIN Strategy - FinexBOTThis strategy uses three indicators:
RSI (Relative Strength Index) - It indicates if a stock is potentially overbought or oversold.
CCI (Commodity Channel Index) - It measures the current price level relative to an average price level over a certain period of time.
Williams %R - It is a momentum indicator that shows whether a stock is at the high or low end of its trading range.
Long (Buy) Trades Open:
When all three indicators suggest that the stock is oversold (RSI is below 25, CCI is below -130, and Williams %R is below -85), the strategy will open a buy position, assuming there is no current open trade.
Short (Sell) Trades Open:
When all three indicators suggest the stock is overbought (RSI is above 75, CCI is above 130, and Williams %R is above -15), the strategy will open a sell position, assuming there is no current open trade.
SL (Stop Loss) and TP (Take Profit):
SL (Stop Loss) is 0.45%.
TP (Take Profit) is 1.2%.
The strategy automatically sets these exit points as a percentage of the entry price for both long and short positions to manage risks and secure profits. You can easily adopt these inputs according to your strategy. However, default settings are recommended.
Adaptive SMI Ergodic StrategyThe Adaptive SMI Ergodic Strategy aims to capture the momentum and direction of a financial asset by leveraging the Stochastic Momentum Index Indicator (SMI) in an ergodic form. The strategy uses two lengths for the SMI, a shorter and a longer one, and an Exponential Moving Average (EMA) to serve as the signal line. Additionally, the strategy incorporates customizable overbought and oversold thresholds to improve the probability of successful trade execution.
How It Works:
Long Entry: A long position is taken when the ergodic SMI crosses over the EMA signal line, and both the SMI and EMA are below the oversold threshold.
Short Entry: A short position is initiated when the ergodic SMI crosses under the EMA signal line, and both the SMI and EMA are above the overbought threshold.
The strategy plots the SMI in yellow and the EMA signal line in purple. Horizontal lines indicate the overbought and oversold thresholds, and a colored background helps in visually identifying these zones.
Parameters:
Long Length: The length of the long EMA in SMI calculation.
Short Length: The length of the short EMA in SMI calculation.
Signal Line Length: The length for the EMA serving as the signal line.
Oversold: Customizable threshold for the oversold condition.
Overbought: Customizable threshold for the overbought condition.
Historical Context: The SMI Indicator
The Stochastic Momentum Index (SMI) was developed by William Blau in the early 1990s as an enhancement to traditional stochastic oscillators. The SMI provides a range of values like a traditional stochastic, but it differs in that it calculates the distance of the current close relative to the median of the high/low range, as opposed to the close relative to the low. As a result, the SMI is less erratic and more responsive, offering a clearer picture of market trends.
In recent years, the SMI has been adapted into ergodic forms to facilitate smoother data analysis, reduce lag, and improve trading accuracy. The Adaptive SMI Ergodic Strategy leverages these modern enhancements to offer a more robust, customizable trading strategy that aligns with various market conditions.
YinYang RSI Volume Trend StrategyThere are many strategies that use RSI or Volume but very few that take advantage of how useful and important the two of them combined are. This strategy uses the Highs and Lows with Volume and RSI weighted calculations on top of them. You may be wondering how much of an impact Volume and RSI can have on the prices; the answer is a lot and we will discuss those with plenty of examples below, but first…
How does this strategy work?
It’s simple really, when the purchase source crosses above the inner low band (red) it creates a Buy or Long. This long has a Trailing Stop Loss band (the outer low band that's also red) that can be adjusted in the Settings. The Stop Loss is based on a % of the inner low band’s price and by default it is 0.1% lower than the inner band’s price. This Stop Loss is not only a stop loss but it can also act as a Purchase Available location.
You can get back into a trade after a stop loss / take profit has been hit when your Reset Purchase Availability After condition has been met. This can either be at Stop Loss, Entry or None.
It is advised to allow it to reset in case the stop loss was a fake out but the call was right. Sometimes it may trigger stop loss multiple times in a row, but you don’t lose much on stop loss and you gain lots when the call is right.
The Take Profit location is the basis line (white). Take Profit occurs when the Exit Source (close, open, high, low or other) crosses the basis line and then on a different bar the Exit Source crosses back over the basis line. For example, if it was a Long and the bar’s Exit Source closed above the basis line, and then 2 bars later its Exit Source closed below the basis line, Take Profit would occur. You can disable Take Profit in Settings, but it is very useful as many times the price will cross the Basis and then correct back rather than making it all the way to the opposing zone.
Longs:
If for instance your Long doesn’t need to Take Profit and instead reaches the top zone, it will close the position when it crosses above the inner top line (green).
Please note you can change the Exit Source too which is what source (close, open, high, low) it uses to end the trades.
The Shorts work the same way as the Long but just opposite, they start when the purchase source crosses under the inner upper band (green).
Shorts:
Shorts take profit when it crosses under the basis line and then crosses back.
Shorts will Stop loss when their outer upper band (green) is crossed with the Exit Source.
Short trades are completed and closed when its Exit Source crosses under the inner low red band.
So, now that you understand how the strategy works, let’s discuss why this strategy works and how it is profitable.
First we will discuss Volume as we deem it plays a much bigger role overall and in our strategy:
As I’m sure many of you know, Volume plays a huge factor in how much something moves, but it also plays a role in the strength of the movement. For instance, let’s look at two scenarios:
Bitcoin’s price goes up $1000 in 1 Day but the Volume was only 10 million
Bitcoin’s price goes up $200 in 1 Day but the Volume was 40 million
If you were to only look at the price, you’d say #1 was more important because the price moved x5 the amount as #2, but once you factor in the volume, you know this is not true. The reason why Volume plays such a huge role in Price movement is because it shows there is a large Limit Order battle going on. It means that both Bears and Bulls believe that price is a good time to Buy and Sell. This creates a strong Support and Resistance price point in this location. If we look at scenario #2, when there is high volume, especially if it is drastically larger than the average volume Bitcoin was displaying recently, what can we decipher from this? Well, the biggest take away is that the Bull’s won the battle, and that likely when that happens we will see bullish movement continuing to happen as most of the Bears Limit Orders have been fulfilled. Whereas with #2, when large price movement happens and Bitcoin goes up $1000 with low volume what can we deduce? The main takeaway is that Bull’s pressured the price up with Market Orders where they purchased the best available price, also what this means is there were very few people who were wanting to sell. This generally dictates that Whale Limit orders for Sells/Shorts are much higher up and theres room for movement, but it also means there is likely a whale that is ready to dump and crash it back down.
You may be wondering, what did this example have to do with YinYang RSI Volume Trend Strategy? Well the reason we’ve discussed this is because we use Volume multiple times to apply multiplications in our calculations to add large weight to the price when there is lots of volume (this is applied both positively and negatively). For instance, if the price drops a little and there is high volume, our strategy will move its bounds MUCH lower than the price actually dropped, and if there was low volume but the price dropped A LOT, our strategy will only move its bounds a little. We believe this reflects higher levels of price accuracy than just price alone based on the examples described above.
Don’t believe us?
Here is with Volume NOT factored in (VWMA = SMA and we remove our Volume Filter calculation):
Which produced -$2880 Profit
Here is with our Volume factored in:
Which produced $553,000 (55.3%)
As you can see, we wen’t from $-2800 profit with volume not factored to $553,000 with volume factored. That's quite a big difference! (Please note previous success does not predict future success we are simply displaying the $ amounts as example).
Now how about RSI and why does it matter in this strategy?
As I’m sure most of you are aware, RSI is one of the leading indicators used in trading. For this reason we figured it would only make sense to incorporate it into our calculations. We fiddled with RSI for quite awhile and sometimes what logically seems to be the right way to use it isn’t. Now, because of this, our RSI calculation is a little odd, but basically what we’re doing is we calculate the RSI, then turn it into a percentage (between 0-1) that can easily be multiplied to the price point we need. The price point we use is the difference between our high purchase zone and our low purchase zone. This allows us to see how much price movement there is between zones. We multiply our zone size with our RSI multiplication and we get the amount we will add +/- to our basis line (white line). This officially creates the NEW high and low purchase zones that we are actually using and displaying in our trades.
If you found that confusing, here are some examples to why it is an important calculation for this strategy:
Before RSI factored in:
Which produced 27.8% Profit
After RSI factored in:
Which produced 553% Profit
As you can see, the RSI makes not only the purchase zones more accurate, but it also greatly increases the profit the strategy is able to make. It also helps ensure an relatively linear profit slope so you know it is reliable with its trades.
This strategy can work on pretty much anything, but you should tweak the values a bit for each pair you are trading it with for best results.
We hope you can find some use out of this simple but effective strategy, if you have any questions, comments or concerns please let us know.
HAPPY TRADING!
Stochastic StrategyThis strategy is designed to make trading decisions based on the Stochastic Oscillator (Stoch) indicator with settings of (7,2,2). The strategy opens a long (buy) position when the Stoch indicator crosses above the 50 level from below. Conversely, it opens a short (sell) position when the Stoch indicator crosses below the 50 level from above. Additionally, when a long position is opened, any existing short position is closed, and vice versa.
Key Parameters:
Stochastic Oscillator Settings: Length = 7, SmoothK = 2, SmoothD = 2.
Overbought Level: 80.
Oversold Level: 20.
Strategy Description:
The Stochastic Oscillator (Stoch) is calculated based on the closing price, high price, and low price with a period of 7, and both the %K and %D lines are smoothed with periods of 2.
When the %K line crosses above the oversold level (20), it generates a long (buy) signal.
When the %K line crosses below the overbought level (80), it generates a short (sell) signal.
The strategy visually marks long and short signals on the chart using upward and downward triangles, respectively.
The strategy automatically enters long or short positions when the respective conditions are met.
If a long position is opened, any existing short position is closed, and vice versa.
Please note that this is a basic example of a trading strategy and does not take into account all possible risk factors or optimizations. Before using this strategy in live trading, it's essential to thoroughly test and customize it to suit your specific needs, and carefully analyze the results. Trading carries risks, and it's important to use proper risk management techniques when implementing any trading strategy.
Strategy Gaussian Anomaly DerivativeConcept behind this Strategy :
Considering a normal "buy/sell" situation, an asset would be bought in average at the median price following a Gaussian like concept. A higher or lower average trend would significate that the current perceived value is respectively higher or lower than the current median price, which mean that the buyers are evaluating the price underpriced or overpriced.
This behaviour would be even more relevent depending on its derivative evolution.
Therefore, this Strategy setup is based on this Gaussian like concept anomaly of average close positionning compare to high-low average derivative, such as the derivative of the following ploted basic signal : 1-(high+low)/(2*close).
This Strategy can actually be used like a trend change and continuation strength indicator aswell.
In the Setup Signal part :
You can define the filtering of the basis signal "1-(high+low)/(2*close)" on EMA or SMA as you wish.
You can define the corresponding period and the threathold as a mutiply of the average 1/3 of all time value of the basis signal.
You can define the SMA filtering period of the Derivative signal and the corresponding threathold on the same mutiply of the average 1/3 of all time value of the derivative.
In the Setup Strategy part :
You can set up your strategy assesment based on Long and/or Short. You can also define the considered period.
The most successful tuned strategies I did were based on the derivative indicator with periods on the basis signal and the derivative under 30, can be 1 to 3 of te derivative and 7 to 21 for the basis signal. The threathold depends on the asset volatility aswell, 1 is usually the most efficient but 0 to 10 can be relevent depending on the situation I met. You can find an example of tuning for this strategy based on Kering's case hereafter.
I hoping that you will enjoy using this Strategy, don't hesitate to comment, to question, to correct or complete it ! I would be very curious about similar famous approaches that would have already been made.
Thank to you !
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
Vortex Cross w/MA ConfirmationThis script is a trading strategy that combines the Vortex Indicator and a Moving Average (MA) to generate potential entry signals for long and short positions.
1. Vortex Indicator:
The Vortex Indicator consists of two lines: Vortex Positive (VIP) and Vortex Negative (VIM). It is designed to identify trend direction and measure the strength of a trend.
2. Moving Average (MA):
The script uses a chosen type of Moving Average (SMA, EMA, SMMA, WMA, or VWMA) to smooth the price data. The smoothed line is referred to as the "Smoothing Line."
3. Determine Long and Short Conditions:
The script looks for potential long entry signals when VIP crosses above VIM, highlighting each crossover on the chart, and the closing price is above the Smoothing Line. It searches for short entry signals when VIM crosses above VIP, with the closing price is below the Smoothing Line. When the long or short conditions are met, the strategy enters either a long or short position accordingly.
Potential Usage:
The strategy can be utilized in trending markets, where the Vortex Indicator helps identify trend direction and strength, and the Moving Average smooths the price data to filter out some noise. It aims to capture trends and ride them while avoiding false signals during choppy or sideways markets.
