Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
ATR
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments.
This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles.
Core Components:
Regression Techniques:
Users can choose one of three regression methods:
1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets.
2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda).
3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors.
Each regression method calculates a trend line that serves as the basis for trading decisions.
Risk Management Measures:
The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands:
1 - ATR (Average True Range)
2 - Standard Deviation
3 - Bollinger Bands Width
4 - Keltner Channel Width
5 - Chaikin Volatility
6 - Historical Volatility
7 - Ulcer Index
8 - ATRP (ATR Percentage)
9 - KAMA Efficiency Ratio
The chosen measure determines the width of the bands around the regression line, adapting to market volatility.
How It Works:
Regression Calculation:
The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line.
For Ridge Regression, users can adjust the lambda parameter for regularization.
LOESS allows customization of the point span, adaptiveness, and exponent for local weighting.
Risk Band Calculation:
The chosen risk measure is calculated and normalized.
A user-defined risk multiplier is applied to adjust the sensitivity.
Upper and lower bounds are created around the regression line based on this risk measure.
Trading Signals:
Long entries are triggered when the price crosses above the regression line.
Short entries occur when the price crosses below the regression line.
Optional stop-loss and take-profit mechanisms use the calculated risk bands.
Customization and Flexibility:
Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear).
The choice of risk measure allows adaptation to various market volatility conditions.
Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy.
Unique Aspects:
Comprehensive Regression Options:
Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions.
Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics.
Unified Framework:
By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management.
Adaptability:
The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options.
How to Use:
Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear).
Choose a risk measure that aligns with your trading style and the market's current volatility characteristics.
Adjust the length parameter to match your preferred timeframe for analysis.
Fine-tune the risk multiplier to set the desired sensitivity of the trading bands.
Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands.
Monitor the regression line for potential trend changes and the risk bands for entry/exit signals.
By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
Fractal Breakout Trend Following StrategyOverview
The Fractal Breakout Trend Following Strategy is a trend-following system which utilizes the Willams Fractals and Alligator to execute the long trades on the fractal's breakouts which have a high probability to be the new uptrend phase beginning. This system also uses the normalized Average True Range indicator to filter trades after a large moves, because it's more likely to see the trend continuation after a consolidation period. Strategy can execute only long trades.
Unique Features
Trend and volatility filtering system: Strategy uses Williams Alligator to filter the counter-trend fractals breakouts and normalized Average True Range to avoid the trades after large moves, when volatility is high
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Flexible Risk Management: Users can choose the stop-loss percent (by default = 3%) for trades, but strategy also has the dynamic stop-loss level using down fractals.
Methodology
The strategy places stop order at the last valid fractal breakout level. Validity of this fractal is defined by the Williams Alligator indicator. If at the moment of time when price breaking the last fractal price is higher than Alligator's teeth line (8 period SMA shifted 5 bars in the future) this is a valid breakout. Moreover strategy has the additional volatility filtering system using normalized ATR. It calculates the average normalized ATR for last user-defined number of bars and if this value lower than the user-defined threshold value the long trade is executed.
When trade is opened, script places the stop loss at the price higher of two levels: user defined stop-loss from the position entry price or down fractal validation level. The down fractal is valid with the rule, opposite as the up fractal validation. Price shall break to the downside the last down fractal below the Willians Alligator's teeth line.
Strategy has no fixed take profit. Exit level changes with the down fractal validation level. If price is in strong uptrend trade is going to be active until last down fractal is not valid. Strategy closes trade when price hits the down fractal validation level.
Risk Management
The strategy employs a combined approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined stop-loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 3% drop from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Williams Fractals to open long trade when price has broken the key resistance level to the upside. This resistance level is the last up fractal and is shall be broken above the Williams Alligator's teeth line to be qualified as the valid breakout according to this strategy. The Alligator filtering increases the probability to avoid the false breakouts against the current trend.
Moreover strategy has an additional filter using Average True Range(ATR) indicator. If average value of ATR for the last user-defined number of bars is lower than user-defined threshold strategy can open the long trade according to open trade condition above. The logic here is following: we want to open trades after period of price consolidation inside the range because before and after a big move price is more likely to be in sideways, but we need a trend move to have a profit.
Another one important feature is how the exit condition is defined. On the one hand, strategy has the user-defined stop-loss (3% below the entry price by default). It's made to give users the opportunity to restrict their losses according to their risk-tolerance. On the other hand, strategy utilizes the dynamic exit level which is defined by down fractal activation. If we assume the breaking up fractal is the beginning of the uptrend, breaking down fractal can be the start of downtrend phase. We don't want to be in long trade if there is a high probability of reversal to the downside. This approach helps to not keep open trade if trend is not developing and hold it if price continues going up.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.19%
Maximum Single Profit: +24.97%
Net Profit: +3036.90 USDT (+30.37%)
Total Trades: 83 (28.92% win rate)
Profit Factor: 1.953
Maximum Accumulated Loss: 963.98 USDT (-8.29%)
Average Profit per Trade: 36.59 USDT (+1.12%)
Average Trade Duration: 72 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h and higher time frames and the BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
RSI and ATR Trend Reversal SL/TPQuick History:
I was frustrated with a standard fixed percent TP/SL as they often were not receptive to quick market rallies/reversals. I developed this TP/SL and eventually made it into a full fledge strategy and found it did well enough to publish. This strategy can be used as a standalone or tacked onto another strategy as a TP/SL. It does function as both with a single line. This strategy has been tested with TSLA , AAPL, NVDA, on the 15 minutes timeframe.
HOW IT WORKS:
Inputs:
Length: Simple enough, it determines the length of the RSI and ATR used.
Multiplier: This multiplies the RSI and ATR calculation, more on this later.
Delay to prevent Idealization: TradingView will use the open of the bar the strategy triggers on when calculating the backtest. This can produce unrealistic results depending on the source. If your source is open, set to 0, if anything else, set to 1.
Minimum Difference: This is essentially a traditional SL/TP, it is borderline unnecessary, but if the other parameters are wacky this can be used to ensure the SL/TP. It multiplies the source by the percent, so if it is set to 10, the SL/TP is initialized at src +- 10%.
Source input: Self Explanatory, be sure to update the Delay if you use open.
CALCULATION:
Parameters Initialization:
The strategy uses Heikinashi values for calculations, this is not toggleable in parameters, but can be easily changed by changing hclose to equal src.
FUNCTION INITIALIZATION:
highest_custom and lowest_custom do the same thing as ta.highest and ta.lowest, however the built in ta library does not allow for var int input, so I had to create my own functions to be used here. I actually developed these years ago and have used them in almost every strategy since. Feel especially free to use these in your own scripts.
The rsilev is where the magic happens.
SL/TP min/max are initially calculated to be used later.
Then we begin by establishing variables.
BullGuy is used to determine the length since the last crossup or crossdown, until one happens, it returns na, breaking the function. BearGuy is used in all the calculations, and is the same as BullGuy, unless BullGuy is na, where BearGuy counts up from 1 on each bar from 0.
We create our rsi and have to modify the second one to suit the function. In the case of the upper band, we mirror the lower one. So if the RSI is 80, we want it to be 20 on the upper band.
the upper band and lower band are calculated the exact same way, but mirrored. For the purpose of writing, I'm going to talk about the lower band. Assume everything is mirrored for the upper one. It finds the highest source since the last crossup or crossdown. It then multiplies from 1 / the RSI, this means that a rapid RSI increase will increase the band dramatically, so it is able to capture quick rally/reversals. We add this to the atr to source ratio, as the general volatility is a massive factor to be included. We then multiply this number by our chosen amount, and subtract it from the highest source, creating the band.
We do this same process but mirrored with both bands and compared it to the source. If the source is above the lower band, it suggests an uptrend, so the lower band is outputted, and vice versa for the upper one.
PLOTTING:
We also determine the line color in the same manner as we do the trend direction.
STRATEGY:
We then use the source again, and if it crosses up or down relative to the selected band, we enter a long or short respectively.
This may not be the most superb independent strategy, but it can be very useful as a TP/SL for your chosen entry conditions, especially in volatile markets or tickers.
Thank you for taking the time to read, and please enjoy.
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
MMI Auto Backtesting StrategyDescription:
A strategy based on ATR with auto-backtesting capabilities, Take Profit and Stop Loss (either Normal or Trailing). It allows you to select ranges of values and step for each parameter, and backtest the strategy on a multitude of input combinations at once. You can alternatively use a constant value for each parameter. The backtesting results strive to be as close as possible to those given by Tradingview Strategy Tester.
The strategy displays a table with results for different input combinations. This has columns showing current input combination as well as the following stats: Net Profit, Number of trades, % of Profitable trades, Profit Factor, Max Drawdown, Max Runup, Average Trade and Average number of bars in a trade.
You can sort the table by any column (including sorting by multiple columns at the same time) to find, for example, input combination that gives highest Net Profit (or, if sorting by multiple columns, to find input combination with the best balance of Net Profit and % of Profitable trades). You can filter by any column as well (or multiple columns at the same time), using logical expressions like "< value", "> value", "<= value", ">= value". And you can use logical expressions like "< value%" for Net Profit, Max Drawdown, Max Runup and Average trade to filter by percentage value. You will see a "↓" symbol in column's header if that column is sorted from Highest to Lowest, a "↑" symbol if it's sorted from Lowest to Highest and a "𐕢" symbol if that column is being filtered.
The table has customisable styles (like text color, background color of cells, etc.), and can show the total number of backtested combinations with the time taken to test them. You can also change Initial Capital and Position Size (either Contracts, Currency or % of Equity).
Parameters:
The following parameters are located in the "INPUTS (USUAL STRATEGY)" group, and control the behaviour of strategy itself (not the auto-backtesting functionality):
- Period: ATR Length
- Multiplier: ATR Multiplier
- DPO: length of the filtering moving average
- SL: stop loss
- TP: take profit
- Use Stop Loss: enable stop loss
- Stop Loss Mode: stop loss mode (either Normal or Trailing)
- Use Take Profit: enable take profit
- Wicks: use high & low price, or close price
The strategy also has various parameters separated by different groups:
- INPUTS (AUTO-BACKTESTING): has the same parameters as the "INPUTS (USUAL STRATEGY)" group, but controls the input combinations for auto-backtesting; all the numeric parameters have 3 values: F/V (from), T (to) and S (step); if the checkbox to the left of F/V parameter is off, the value of F/V will indicate the constant value used for that parameter (if the checkbox is on, the values will be from F/V to T using step S)
- STRATEGY: contains strategy related parameters like Initial Capital and Position Size
- BACKTESTING: allows you to display either Percentage, Absolute or Both values in the table and has checkboxes that allow you to exclude certain columns from the table
- SORTING: allows you to select sorting mode (Highest to Lowest or vice versa) and has checkboxes in case you want to sort by multiple columns at the same time
- FILTERING: has a text field for each column of the strategy where you can type logical expressions to filter the values
- TABLE: contains styling parameters
Many parameters have the "(i)" description marker, so hover over it to see more details.
Problems:
- The script works best on lower timeframes and continuous markets (trades 24/7), in other cases the backtesting results may vary from those that Tradingview shows
- The script shows closest results when Take Profit and Stop Loss are not used
- Max Runup percentage value is often wrong
Limitations:
- As we are limited by the maximum time a script can be running (which is 20s for Free plan and 40s for Paid plans), we can only backtest several hundreds of combinations within that timeframe (though it depends on the parameters, market and timeframe of the chart you use)
Buying Selling Volume StrategyFirst I would like to give the original credit and thanks to @ceyhun for his amazing volume script.
The way I decided to convert it into a strategy is divided into multiple types.
First, I decided in order to smooth out the values and make it more accurate to adapt the values to multiple timeframes.
After that I took the initial values from the buyers and sellers , and made a rest operation between them to have a flat difference between the power of both sides.
WIth that later on I decided to to apply a volatility filter,in this case bollinger bands, in order to find out potential leading trends.
At the same time in order to filter even more, I decided to make use as well for weekly VWAP values of the asset used.
Lastly I added a dynamic risk management into it , based on the ATR Daily values of the asset values.
As for the rules used, for example for long, I am looking that the price of the asset is above the weekly VWAP, after that I am checking that the MTF volume rest operation is both bullish and above the upper side of the bollinger.
For short we would want the asset to be below the weekly VWAP, and the volume to be bearish and above the upper side of bollinger.
The exit is either based on daily ATR values multipliers, or if we have a reverse condition.
If you have any questions, please let me know !
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
[tradinghook] - Renko Trend Reversal Strategy - Renko Trend Reversal Strategy
Short Title: - Renko TRS
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
CCI+EMA Strategy with Percentage or ATR TP/SL [Alifer]This is a momentum strategy based on the Commodity Channel Index (CCI), with the aim of entering long trades in oversold conditions and short trades in overbought conditions.
Optionally, you can enable an Exponential Moving Average (EMA) to only allow trading in the direction of the larger trend. Please note that the strategy will not plot the EMA. If you want, for visual confirmation, you can add to the chart an Exponential Moving Average as a second indicator, with the same settings used in the strategy’s built-in EMA.
The strategy also allows you to set internal Stop Loss and Take Profit levels, with the option to choose between Percentage-based TP/SL or ATR-based TP/SL.
The strategy can be adapted to multiple assets and timeframes:
Pick an asset and a timeframe
Zoom back as far as possible to identify meaningful positive and negative peaks of the CCI
Set Overbought and Oversold at a rough average of the peaks you identified
Adjust TP/SL according to your risk management strategy
Like the strategy? Give it a boost!
Have any questions? Leave a comment or drop me a message.
CAUTIONARY WARNING
Please note that this is a complex trading strategy that involves several inputs and conditions. Before using it in live trading, it is highly recommended to thoroughly test it on historical data and use risk management techniques to safeguard your capital. After backtesting, it's also highly recommended to perform a first live test with a small amount. Additionally, it's essential to have a good understanding of the strategy's behavior and potential risks. Only risk what you can afford to lose .
USED INDICATORS
1 — COMMODITY CHANNEL INDEX (CCI)
The Commodity Channel Index (CCI) is a technical analysis indicator used to measure the momentum of an asset. It was developed by Donald Lambert and first published in Commodities magazine (now Futures) in 1980. Despite its name, the CCI can be used in any market and is not just for commodities. The CCI compares current price to average price over a specific time period. The indicator fluctuates above or below zero, moving into positive or negative territory. While most values, approximately 75%, fall between -100 and +100, about 25% of the values fall outside this range, indicating a lot of weakness or strength in the price movement.
The CCI was originally developed to spot long-term trend changes but has been adapted by traders for use on all markets or timeframes. Trading with multiple timeframes provides more buy or sell signals for active traders. Traders often use the CCI on the longer-term chart to establish the dominant trend and on the shorter-term chart to isolate pullbacks and generate trade signals.
CCI is calculated with the following formula:
(Typical Price - Simple Moving Average) / (0.015 x Mean Deviation)
Some trading strategies based on CCI can produce multiple false signals or losing trades when conditions turn choppy. Implementing a stop-loss strategy can help cap risk, and testing the CCI strategy for profitability on your market and timeframe is a worthy first step before initiating trades.
2 — AVERAGE TRUE RANGE (ATR)
The Average True Range (ATR) is a technical analysis indicator that measures market volatility by calculating the average range of price movements in a financial asset over a specific period of time. The ATR was developed by J. Welles Wilder Jr. and introduced in his book “New Concepts in Technical Trading Systems” in 1978.
The ATR is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The ATR can be used to set stop-loss orders. One way to use ATR for stop-loss orders is to multiply the ATR by a factor (such as 2 or 3) and subtract it from the entry price for long positions or add it to the entry price for short positions. This can help traders set stop-loss orders that are more adaptive to market volatility.
3 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
STRATEGY EXPLANATION
1 — INPUTS AND PARAMETERS
The strategy uses the Commodity Channel Index (CCI) with additional options for an Exponential Moving Average (EMA), Take Profit (TP) and Stop Loss (SL).
length : The period length for the CCI calculation.
overbought : The overbought level for the CCI. When CCI crosses above this level, it may signal a potential short entry.
oversold : The oversold level for the CCI. When CCI crosses below this level, it may signal a potential long entry.
useEMA : A boolean input to enable or disable the use of Exponential Moving Average (EMA) as a filter for long and short entries.
emaLength : The period length for the EMA if it is used.
2 — CCI CALCULATION
The CCI indicator is calculated using the following formula:
(src - ma) / (0.015 * ta.dev(src, length))
src is the typical price (average of high, low, and close) and ma is the Simple Moving Average (SMA) of src over the specified length.
3 — EMA CALCULATION
If the useEMA option is enabled, an EMA is calculated with the given emaLength .
4 — TAKE PROFIT AND STOP LOSS METHODS
The strategy offers two methods for TP and SL calculations: percentage-based and ATR-based.
tpSlMethod_percentage : A boolean input to choose the percentage-based method.
tpSlMethod_atr : A boolean input to choose the ATR-based method.
5 — PERCENTAGE-BASED TP AND SL
If tpSlMethod_percentage is chosen, the strategy calculates the TP and SL levels based on a percentage of the average entry price.
tp_percentage : The percentage value for Take Profit.
sl_percentage : The percentage value for Stop Loss.
6 — ATR-BASED TP AND SL
If tpSlMethod_atr is chosen, the strategy calculates the TP and SL levels based on Average True Range (ATR).
atrLength : The period length for the ATR calculation.
atrMultiplier : A multiplier applied to the ATR to set the SL level.
riskRewardRatio : The risk-reward ratio used to calculate the TP level.
7 — ENTRY CONDITIONS
The strategy defines two conditions for entering long and short positions based on CCI and, optionally, EMA.
Long Entry: CCI crosses below the oversold level, and if useEMA is enabled, the closing price should be above the EMA.
Short Entry: CCI crosses above the overbought level, and if useEMA is enabled, the closing price should be below the EMA.
8 — TP AND SL LEVELS
The strategy calculates the TP and SL levels based on the chosen method and updates them dynamically.
For the percentage-based method, the TP and SL levels are calculated as a percentage of the average entry price.
For the ATR-based method, the TP and SL levels are calculated using the ATR value and the specified multipliers.
9 — EXIT CONDITIONS
The strategy defines exit conditions for both long and short positions.
If there is a long position, it will be closed either at TP or SL levels based on the chosen method.
If there is a short position, it will be closed either at TP or SL levels based on the chosen method.
Additionally, positions will be closed if CCI crosses back above oversold in long positions or below overbought in short positions.
10 — PLOTTING
The script plots the CCI line along with overbought and oversold levels as horizontal lines.
The CCI line is colored red when above the overbought level, green when below the oversold level, and white otherwise.
The shaded region between the overbought and oversold levels is plotted as well.
Volatility Compression Breakout - LeafAlgo Pro StrategyThe Volatility Compression Breakout strategy is designed to identify periods of low volatility followed by potential breakout opportunities in the market. It aims to capture moments when the price consolidates within a narrow range, indicating a decrease in volatility, and anticipates a subsequent expansion in price movement. This strategy is based on our indicator of the same name (), but differs by offering many more options for the band/channel type and trend filters in addition to implementing the ability to use this strategy with algorithmic plug-ins (see details at the bottom).
This strategy features six types of bands/channels and five types of trend filters, for a total of 30 combinations. The six band/channel types are the Adaptive Gaussian MA channel (based on the Adaptive Gaussian MA that we previously published ()), standard Bollinger Bands, smoothed Bollinger Bands (basis is an EMA of the typical Bollinger Basis), Keltner Channels, a Quadratic Regression Channel (based on the channel that we previously published in the LeafAlgo Pro indicator ()), and Volatility-Based Mean Reversion Bands (). The five trend filters include an EMA, SMA, Weighted MA, McGinley Dynamic, and the Adaptive Gaussian MA itself.
Examples of the different band/channel types (all with EMA as the trend filter):
Adaptive Gaussian MA Channel:
Bollinger Bands:
Smoothed Bollinger Bands:
Keltner Channels:
Quadratic Regression Channel:
Volatility-Based Mean Reversion Bands:
Examples of the different trend filters (all with Keltner Channels):
EMA:
SMA:
WMA:
McGinley Dynamic:
Adaptive Gaussian MA:
How the Long/Short Entry Signals are Calculated:
A breakout signal upwards, accompanied by a long entry, is created when the high is greater than the secondary upper band (the upper band plus a standard deviation or with a multiplier, depending on which band/channel type is selected), the latest close is above the trend filter line, and the previous close was below the trend filter line. A break downwards, accompanied by a short entry, is created when the low is below the secondary lower band, the close is below the trend filter line, and the previous close was above the trend filter line. These conditions, along with a confirmed barstate, make up the strategy entry signals.
Coloration:
When the close price is above both the middle/basis and the trend filter, the bars are colored lime green, indicating a potential bullish market sentiment. When the close price is positioned above the basis but below the trend filter, or below the basis but above the trend filter, the bars are colored yellow, signifying a neutral or indecisive market condition. Conversely, when the close price falls below both the basis and the trend filter, the bars are colored fuchsia, suggesting a potential bearish market sentiment. Additionally, the coloration of the middle/basis line and the trend filter provides further visual cues for assessing the trend. When the close price is above the basis, the line is colored lime green, indicating a bullish trend. Conversely, when the close price is below the basis, the line is colored fuchsia, highlighting a bearish trend. Similarly, the trend line is colored lime green when the close price is above it, representing a bullish trend, and fuchsia when the close price is below it, indicating a bearish trend. The fill between the primary and secondary upper bands is colored lime and the fill between the primary and secondary lower bands is colored fuchsia. These colorations can be toggled on/off in the strategy settings menu.
How Changing Parameters Can Be Beneficial:
Modifying the parameters allows you to adapt the indicator to different market conditions and trading styles. For example, with Keltner Channels, increasing the compression period can help identify broader volatility patterns and major market shifts. On the other hand, decreasing the compression period provides more precise and timely signals for short-term traders. Adjusting the compression multiplier affects the width of the Keltner Channels. Higher multipliers increase the breakout threshold, filtering out smaller price movements and providing more reliable signals during significant market shifts. Lower multipliers make the indicator more sensitive to smaller price ranges, generating more frequent but potentially less reliable signals.
Changing the type of trend filter can drastically change your results. Test out each trend filter type and determine which one will work best for your purposes. Further, the MA periods in the trend filter settings can help you align your trades with the prevailing market direction. Increasing the period smoothes out the trend, filtering out shorter-term fluctuations and focusing on more sustained moves. Decreasing the period allows for quicker responses to changes in trend, capturing shorter-term price swings.
By adjusting the parameters and incorporating additional analysis techniques, you can customize the strategy to suit your trading style and preferences. However, it is crucial to exercise caution, conduct thorough analysis, and practice proper risk management to increase the likelihood of successful trades. Remember that no strategy can guarantee profits, and continuous learning and adaptation are key to long-term trading success.
Take Profit/Stop Loss Settings:
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. The take profit and stop loss levels will be reflected as green and red lines respectively on the chart as they occur. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. The option for adding in a trailing stop has also been included, with options to choose between an ATR-based trail or a percentage-based trail. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview/Pineconnector Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else. If using Pineconnector, follow the same directions for setting up an alert, but use the ",buy,,risk=" syntax as noted in the tooltips.
Additional Sample Settings (for ETHUSDT-Binance 45M):
Band/Channel Type - Keltner Channels (Compression Period of 20, Multiplier of 1.8x)
Trend Filter - WMA (50 length, no offset, close as the source)
TP/SL - 3.0% TP / 2.0% SL, 0.005 trailed TP, no trailed SL
Chandelier Exit ZLSMA StrategyIntroducing a Powerful Trading Indicator: Chandelier Exit with ZLSMA
If you're a trader, you know the importance of having the right tools and indicators to make informed decisions. That's why we're excited to introduce a powerful new trading indicator that combines the Chandelier Exit and ZLSMA: two widely-used and effective indicators for technical analysis.
The Chandelier Exit (CE) is a popular trailing stop-loss indicator developed by Chuck LeBeau. It's designed to follow the price trend of a security and provide an exit signal when the price crosses below the CE line. The CE line is based on the Average True Range (ATR), which is a measure of volatility. This means that the CE line adjusts to the volatility of the security, making it a reliable indicator for trailing stop-losses.
The ZLEMA (Zero Lag Exponential Moving Average) is a type of exponential moving average that's designed to reduce lag and improve signal accuracy. The ZLSMA takes into account not only the current price but also past prices, using a weighted formula to calculate the moving average. This makes it a smoother indicator than traditional moving averages, and less prone to giving false signals.
When combined, the CE and ZLSMA create a powerful indicator that can help traders identify trend changes and make more informed trading decisions. The CE provides the trailing stop-loss signal, while the ZLSMA provides a smoother trend line to help identify potential entry and exit points.
In our indicator, the CE and ZLSMA are plotted together on the chart, making it easy to see both the trailing stop-loss and the trend line at the same time. The CE line is displayed as a dotted line, while the ZLSMA line is displayed as a solid line.
Using this indicator, traders can set their stop-loss levels based on the CE line, while also using the ZLSMA line to identify potential entry and exit points. The combination of these two indicators can help traders reduce their risk and improve their trading performance.
In conclusion, the Chandelier Exit with ZLSMA is a powerful trading indicator that combines two effective technical analysis tools. By using this indicator, traders can identify trend changes, set stop-loss levels, and make more informed trading decisions. Try it out for yourself and see how it can improve your trading performance.
Warning: The results in the backtest are from a repainting strategy. Don't take them seriously. You need to do a dry live test in order to test it for its useability.
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Here is a description of each input field in the provided source code:
length: An integer input used as the period for the ATR (Average True Range) calculation. Default value is 1.
mult: A float input used as a multiplier for the ATR value. Default value is 2.
showLabels: A boolean input that determines whether to display buy/sell labels on the chart. Default value is false.
isSignalLabelEnabled: A boolean input that determines whether to display signal labels on the chart. Default value is true.
useClose: A boolean input that determines whether to use the close price for extrema calculations. Default value is true.
zcolorchange: A boolean input that determines whether to enable rising/decreasing highlighting for the ZLSMA (Zero-Lag Exponential Moving Average) line. Default value is false.
zlsmaLength: An integer input used as the length for the ZLSMA calculation. Default value is 50.
offset: An integer input used as an offset for the ZLSMA calculation. Default value is 0.
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Ty for checking this out and good luck on your trading journey! Likes and comments are appreciated. 👍
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Credits to:
▪ @everget – Chandelier Exit (CE)
▪ @netweaver2022 – ZLSMA
JS-TechTrading: Supertrend-Strategy_Basic versionAre you looking for a reliable and profitable algorithmic trading strategy for TradingView? If so, you might be interested in our Supertrend basic strategy, which is based on three powerful indicators: Supertrend (ATR), RSI and EMA.
Supertrend is a trend-following indicator that helps you identify the direction and strength of the market. It also gives you clear signals for entry and exit points based on price movements.
RSI is a momentum indicator that measures the speed and change of price movements. It helps you filter out false signals and avoid overbought or oversold conditions.
EMA is a moving average indicator that smooths out price fluctuations and shows you the long-term trend of the market. It helps you confirm the validity of your trades and avoid trading against the trend.
Our Supertrend basic strategy combines these three indicators to give you a simple yet effective way to trade any market. Here's how it works:
- For long trades, you enter when the price is above Supertrend and pulls back below it (the low of the candle crosses Supertrend) and then rebounds above it (the high of the next candle goes above the pullback candle). You exit when the price closes below Supertrend or when you reach your target profit or stop loss.
- For short trades, you enter when the price is below Supertrend and pulls back above it (the high of the candle crosses Supertrend) and then drops below it (the low of the next candle goes below the pullback candle). You exit when the price closes above Supertrend or when you reach your target profit or stop loss.
- You can also use RSI and EMA filters to improve your results. For long trades, you only enter if RSI is above 50 and price is above 200 EMA. For short trades, you only enter if RSI is below 50 and price is below 200 EMA.
- You can set your stop loss and target profit as a percentage of your entry price or based on other criteria. You can also adjust the parameters of each indicator according to your preferences and risk tolerance.
Our Supertrend basic strategy is easy to use and has been tested on various markets and time frames. It can help you capture consistent profits while minimizing your losses.
Seer's HutThis is a strategy based on Exponential Moving Averages or Volume Weighted Moving Averages against Adaptive fib resistance / support level and profit percentage which can be definetly defined by user and targeting small profits(profits will be raised by leverages).
In this strategy, there are predefined values which are collected one by one with statistical background and backtests. This gives an advantage to see which ratios are working better for each symbol. Also this statistics are re-evaluated monthly and if there is a need they are going to be changed with the help of libraries. Also IT IS RECOMMENDED TO USE IN DAILY INTERVAL GRAPHICS!!!!
When we deep dive to strategy, it is based on profit percentages. it is similar to the MOST system. MOST only changes the way with default value of %2. But this hardcoded strategy is not working well with each Symbol.
So this is the point where DC and ADR Statistics are involved.
For Ex. while BTC is suits well with %2, it does not do wonders for RSR or RUNE which is 4-5% for each.
There is 3 options for setting the statistical usage of this indicator.
1. Auto calculated based on 1000 days of ADR and DC
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2. Using Library where statistical values are stored.
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3. User-defined values used. Yeah you read it right. Fully on-demand changes are supported. Which gives freedom to users for setup their own Adaptive FIB and Profit Percentages.
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Based on this 3 options, TP and SL points are calculated on bar closures. Strategy Orders are also shown / raised with the closures.
Ok, system calculates these values but how to read / use them. what is this strategy based on ?
This strategy is mostly looking for minimizing the LOSS in case of any stop. So because of this, in each TP, system gives order signal to close half of the remaining open position.
There are 7 type of orders
OL : Open Long (Close Short and Open Long if in position)
CL 50 : Close Long - %50 of Open Position
CL 100 : Close Long - Close all position
OS : Open Short (Close Long and Open Short if in position)
CL 50 : Close Short - %50 of Open Position
CL 100 : Close Short - Close all position
TP5 : Highest TP reached. Close all position.
Script checks cross of EMA / VWMA and adFib to decide open a position. In reversal / crosses, adFib line had been set to defined Fib. Percentage (FP) level.
For creating the TP points, Profit Percentage (PP) parameter had been used which I briefly introduce at the beginning with the options.
One important topic about this strategy, it is not stacking / pyramiding the positions. Which means, it always calculate one way position. For example we are in the long position after OL signal.
We reached TP values and take profits. Later on due to FP crossing EMA, OS order signal given. This means you have to close all long position and open short position.
But beware. These calculated points are based on given values or calculated regarding to average ADR / DC ratings. For supporting strategy, several methods also had been included in the options.
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These are:
1. MA plotting (Optional 4 EMA, 1WMA) - checking for Golden and Death Cross
2. Bollinger Bands (Length 25 and Multiplier 2.5 set as default. Used in correlation with TEMA)
3. Kama 2 / Kama 5 - Crossing speaks of Trend way
4. TEMA (TEMA 50, VWMA 25 calculations and plotting. Used for TEMA 50 / VWMA 25 / SMA 25 cross checks for weakening or strengthening trend analysis)
5. ATR plotting
6. Chandelier Exit plotting (Widely used for calculating Stop levels in market)
7. PSAR (Widely used for indicating trend reversal)
Also for the ease of use, if the users does not want to plot any values on the graph and just want to see the values there is couple of tables also included.
1. EMA info
2. KAMA info
3. Order info
4. TP/SL info
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Some important notes:
1. To minimize the stop just after the order opening candle in volatile grounds, system prevents to raise new order signals if there is a signal already raised in last 4 candle.
2. if system reach and give close order in one of the TP points (For Ex TP1.), then index goes down and goes up again same TP (above TP1 in scenario) after 4 candle, system gives a close order signal again in the same TP.
3. There is a Profit Factor value had been shown at Order Info table. This information shows how profitable is the setup regarding to given FP and PP values.
In general market conditions, A Profit Factor above 1.50 is considered good enough and above 2.0 it is considered ideal. A strategy with profit factor less than 1.20 suggests too bigger a risk taken for making money.
In some cases automatic ADR and DC calculations are not good enough. so if you want to find a good Profit Factor value, you can change the system automatic calculation to manual value entering and you can see the results directly with in this field.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Self Optimizing Supertrend [Starbots]Self Optimizing Supertrend Strategy. (non-repainting)
Script constantly tests 15 Supertrend combinations for maximum profitability and trades based on the best performing combination.
You will notice that signal lines switch after a bar close sometimes, this is when the strategy optimizes to the better combination and change plots, strategy is dynamic.
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# Average True Range (ATR)
The Average True Range (ATR) is a tool used in technical analysis to measure volatility. Unlike many of today's popular indicators, the ATR is not used to indicate the direction of price. Rather, it is a metric used solely to measure volatility, especially volatility caused by price gaps or limit moves.
# Supertrend
A Super Trend is a trend following indicator similar to moving averages. It is plotted on price and the current trend can simply be determined by its placement vis-a-vis price. It is a very simple indicator and is constructed with the help of just two parameters- period and multiplier.
When we construct the Supertrend indicator strategy, the default parameters are 10 for Average True Range (ATR) and 3 for its multiplier. The average true range (ATR) plays a key role in ‘Supertrend’ as the indicator uses ATR to compute its value and it signals the degree of price volatility.
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-Turn on Supertrend Profit Dashboard and spot the worst/best performing combination. You can change them to get the best performance overall.
-Backtesting Range - backtest within your desired time window. Example: 'from 01 / 01 /2020 to 01 / 01 /2023'.
-Optimizing range - you can decrease the amount of bars/data for optimizing script. This way you can keep it up to date to more recent market by selecting optimizing range to optimize it just from the recent 3-6months of data for example. Strategy before this selected range will normally trade (backtest) based on the fifth buying condition (5. Supertrend Factor) parameter in your menu (1.6 by default) if you turn this on.
*I recommend 'Optimizing Range' turned off actually, use max amount of available bars in your history for optimization script.
- Strategy is trading on the bar close without repaint. You can trade Long-Sell or Long- Short. Alerts available, insert webhook messages.
- Turn on Profit Calendar for better overview of how your strategy performs monthly/annualy
- Recommended ATR Length : 10 (default), higher timeframes usually performs good on the shorter period lengths 6-10, smaller timeframes on the larger ATR period length 10-20.
- Recommended Sources : hl2 (default Supertrend), close, hlc3, hlcc4 (when scalping/day trading and market is uptrending good, you can use 'volume' as a source, comes in handy)
- Recommended Smoothing Moving Average for ATR : We smooth the ATR calculation with moving average, traders usually use SMA as a moving average here, but you can use alternatives like EMA, HMA. Try them if this improves your results.
- Recommended TF : 15min, 30min, 1h, 2h, 4h, 8h, 1d (low timeframes works good if you have no fees like Binance currently do on BTC for example otherwise you probably want to use 1/2h+ chart)
- Supertrend Factor parameters : pre-set Supertrend Factors are very good and common in trading world, you don't need to change them, but you can do it at free will. Traders usually use Supertrend factor of 2 or 3, use parameters around this numbers.
- Notes window : add your custom comments in or save your webhook message text inside here for later use.
- Trading Session: in a session, you have to specify the time range for every day. It will trade only within this window and close trades when it's out. Session from 9am to 5pm will look like that: 0900-1700 or 7am to 4:30pm 0700-1630. After the colon, you can specify days of the week for your trading session. 1234567 trading all days, 23456 – Monday to Friday ('1 is Sunday here'). 0000-0000:1234567 by default will trade every day nonstop. 00.00am to 00.00pm and 1234567 every day of the week for example - Cryptocurrencies.
This script is simple to use for any trader as it saves a lot of time for searching good parameters on your own. It's self-optimizing and adjusting to the markets on the go.
Wunder Volatility botWunder Volatility bot
We have used the Average True Range (ATR) in many of its trading versions.
1. ATR with MA. This indicator includes the ATR as well as the simple moving average, which helps to restore the expected market.
2. We apply percentage based ATR to determine how volatile the market is and whether to buy or sell at that time. For trading, we will filter the market and make trades only within the specified range. This range will adjust depending on the asset, so you will need to change the settings if you are trading multiple assets.
3. A function for calculating risk on the portfolio (your deposit) has been added to the Wunder Volatility bot script. When this option is enabled, you get a calculation of the entry amount in dollars relative to your Stop Loss. In the settings, you can select the risk percentage on your portfolio. The loss will be calculated from the amount that will be displayed on the chart.
For example, if your deposit is $1000 and you set the risk to 1%, with a Stop Loss of 5%, the entry volume will be $200. The loss at SL will be $10.10, which is your 1% risk or 1% of the deposit.
**Important!** The risk per trade must be less than the Stop Loss value. If the risk is greater than SL, then you should use leverage.
The amount of funds entering the trade is calculated in dollars. This option was created if you want to send the dollar amount from Tradingview to the exchange. However, putting your volume in dollars you get the incorrect net profit and drawdown indication in the backtest results, as TradingView calculates the backtest volume in contracts.
To display the correct net profit and drawdown values in Tradingview Backtest results, use the ”Volume in contract” option.
TradePro's 2 EMA + Stoch RSI + ATR StrategySaw TradePro's "NEW BEST HIGHEST PROFITING STRATEGY WITH CRAZY RESULTS - 2 EMA+ Stochastic RSI+ ATR", and was curious on the back testing results. This strategy is an attempt to recreate it.
This strategy uses 50 / 200 EMAs, Stochastic RSI and ATR.
Long Entry Criteria:
- 50 EMA > 200 EMA
- Price closes below 50 EMA
- Stochastic RSI has gone into oversold < 20
- Stochastic RSI crosses up while making higher low from previous cross up
Short Entry Criteria:
- 50 EMA < 200 EMA
- Price closes above 50 EMA
- Stochastic RSI has gone into overbought > 80
- Stochastic RSI crosses down while making lower high from previous cross down
Stop-loss is set to ATR stop-loss
Take Profit is 2x the risk
All parameters are configurable.
Enjoy~~
Super 8 - 30M BTCWelcome to Super 8, the ultimate automatic trading script for Pine!
This bad boy is designed to go both long and short, and it's equipped with all the tools you need to maximize your profits. Whether you're looking to take profit, set a trailing stop, or protect yourself with a stop loss, Super 8 has you covered.
But that's not all! Super 8 is also loaded with 8 powerful indicators to help you make informed decisions. We've got the EMA, ADX, SAR, MACD, VOLUME, BOLLINGER BANDS, DONCHIAN, and ATR all working together to give you the best possible trading experience.
And if you want to take it to the next level, Super 8 also has a feature that lets you use stepped entries in normal mode or incremental 1,2,3,... to improve your average price. Plus, if you're using trailing stop, you can activate the Backtest precision to use lower timeframes.
But what's in a name? Super 8 is called that because it's just that... super! It's tailored specifically for the OKX:BTCUSDT.P pair, so you know you're getting the best possible results. it's highly adjustable and can be used with any other pair. So no matter what market you're trading in, Super 8 has got you covered.
So if you want to level up your trading game, give Super 8 a try. You won't be disappointed.
Certain Risks of Live Algorithmic Trading:
Backtesting Cannot Assure Actual Results.
The relevant market might fail or behave unexpectedly.
Your broker may experience failures in its infrastructure, fail to execute your orders in a correct or timely fashion or reject your orders.
The system you use for generating trading orders, communicating those orders to your broker, and receiving queries and trading results from your broker may fail.
Time lag at various point in live trading might cause unexpected behavior.
The systems of third parties in addition to those of the provider from which we obtain various services, your broker, and the applicable securities market may fail or malfunction.
WilliamTrendFollower StrategyThis strategy is based on signals from the WilliamTrendFollower indicator.
You can optimize the parameters of this strategy as you wish. I hope you get the most accurate result.
About WilliamTrendFollower:
With this indicator, we try to catch the trends in price. With continued use of this indicator, we expect it to eventually escape horizontal positions and catch up with continuous trends.
Combined with the WilliamsR indicator and the exponential moving average indicator.
The WilliamsR Fisher Transforms are combined with the ATR indicator to create a line that lags behind the moving average value.
Since it is a tracking indicator, we created a line that is more connected to the price and itself.
In this way, a curve close to the price line is obtained in uptrends and downtrends.
In this indicator, if you choose the parameters correctly, you can easily bypass the horizontal positions. This gives you a safe visualization of support and resistance points as well.
From the settings of these indicators, you can set the multiplier and the exponential moving average period.
It works in all time intervals.
But it was calculated without volume , instead it was created using fisher transforms, moving averages, and the average true range .
Moving Average Displaced Envelope & ATRTS Moving Average Displaced Envelope. These envelopes are calculated
by multiplying percentage factors with their displaced expotential
moving average (EMA) core.
How To Trade Using:
Adjust the envelopes percentage factors to control the quantity and
quality of the signals. If a previous high goes above the envelope
a sell signal is generated. Conversely, if the previous low goes below
the envelope a buy signal is given.
Average True Range Trailing Stops Strategy, by Sylvain Vervoort
The related article is copyrighted material from Stocks & Commodities Jun 2009
ATR TS used by filter for MADE signals.
WARNING:
- For purpose educate only
- This script to change bars colors.
SSL + Wave Trend StrategyStrategy incorporates the following features:
Risk management:
Configurable X% loss per stop loss
Configurable R:R ratio
Trade entry:
Based on strategy conditions below
Trade exit:
Based on strategy conditions below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Alerting:
Alerts on LONG and SHORT trade entries
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: SSL Hybrid baseline is BLUE
C2: SSL Channel crosses up (green above red)
C3: Wave Trend crosses up (represented by pink candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents resistance)
SHORT
C1: SSL Hybrid baseline is RED
C2: SSL Channel crosses down (red above green)
C3: Wave Trend crosses down (represented by orange candle body)
C4: Entry candle height is not greater than configured threshold
C5: Entry candle is inside Keltner Channel (wicks or body depending on configuration)
C6: Take Profit target does not touch EMA (represents support)
Trade exit:
Stop Loss: Size configurable with NNFX ATR multiplier
Take Profit: Calculated from Stop Loss using R:R ratio
Credits
Strategy is based on the YouTube video "This Unique Strategy Made 47% Profit in 2.5 Months " by TradeSmart.
It combines the following indicators to determine trade entry/exit conditions:
Wave Trend: Indicator: WaveTrend Oscillator by @LazyBear
SSL Channel: SSL channel by @ErwinBeckers
SSL Hybrid: SSL Hybrid by @Mihkel00
Keltner Channels: Keltner Channels Bands by @ceyhun
Candle Height: Candle Height in Percentage - Columns by @FreeReveller
NNFX ATR: NNFX ATR by @sueun123
