Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
指數移動平均線(EMA)
Long EMA Strategy with Advanced Exit OptionsThis strategy is designed for traders seeking a trend-following system with a focus on precision and adaptability.
**Core Strategy Concept**
The essence of this strategy lies in use of Exponential Moving Averages (EMAs) to identify potential long (buy) positions based on the relative positions of short-term, medium-term, and long-term EMAs. The use of EMAs is a classic yet powerful approach to trend detection, as these indicators smooth out price data over time, emphasizing the direction of recent price movements and potentially signaling the beginning of new trends.
**Customizable Parameters**
- **EMA Periods**: Users can define the periods for three EMAs - long-term, medium-term, and short-term - allowing for a tailored approach to capture trends based on individual trading styles and market conditions.
- **Volatility Filter**: An optional Average True Range (ATR)-based volatility filter can be toggled on or off. When activated, it ensures that trades are only entered when market volatility exceeds a user-defined threshold, aiming to filter out entries during low-volatility periods which are often characterized by indecisive market movements.
- **Trailing Stop Loss**: A trailing stop loss mechanism, expressed as a percentage of the highest price achieved since entry, provides a dynamic way to manage risk by allowing profits to run while cutting losses.
- **EMA Exit Condition**: This advanced exit option enables closing positions when the short-term EMA crosses below the medium-term EMA, serving as a signal that the immediate trend may be reversing.
- **Close Below EMA Exit**: An additional exit condition, which is disabled by default, allows positions to be closed if the price closes below a user-selected EMA. This provides an extra layer of flexibility and risk management, catering to traders who prefer to exit positions based on specific EMA thresholds.
**Operational Mechanics**
Upon activation, the strategy evaluates the current price in relation to the set EMAs. A long position is considered when the current price is above the long-term EMA, and the short-term EMA is above the medium-term EMA. This setup aims to identify moments where the price momentum is strong and likely to continue.
The strategy's versatility is further enhanced by its optional settings:
- The **Volatility Filter** adjusts the sensitivity of the strategy to market movements, potentially improving the quality of the entries during volatile market conditions.
The Average True Range (ATR) is a key component of this filter, providing a measure of market volatility by calculating the average range between the high and low prices over a specified number of periods. Here's how you can adjust the volatility filter settings for various market conditions, focusing on filtering out low-volatility markets:
Setting Examples for Volatility Filter
1. High Volatility Markets (e.g., Cryptocurrencies, Certain Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: Setting the multiplier to a lower value, such as 1.0 or 1.2, can be beneficial in high-volatility markets. This sensitivity allows the strategy to react to volatility changes more quickly, ensuring that you're entering trades during periods of significant movement.
2. Medium Volatility Markets (e.g., Major Equity Indices, Medium-Volatility Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: A multiplier of 1.5 (default) is often suitable for medium volatility markets. It provides a balanced approach, ensuring that the strategy filters out low-volatility conditions without being overly restrictive.
3. Low Volatility Markets (e.g., Some Commodities, Low-Volatility Forex Pairs):
ATR Periods: Increasing the ATR period to 20 or 25 can smooth out the volatility measure, making it less sensitive to short-term fluctuations. This adjustment helps in focusing on more significant trends in inherently stable markets.
ATR Multiplier: Raising the multiplier to 2.0 or even 2.5 increases the threshold for volatility, effectively filtering out low-volatility conditions. This setting ensures that the strategy only triggers trades during periods of relatively higher volatility, which are more likely to result in significant price movements.
How to Use the Volatility Filter for Low-Volatility Markets
For traders specifically interested in filtering out low-volatility markets, the key is to adjust the ATR Multiplier to a higher level. This adjustment increases the threshold required for the market to be considered sufficiently volatile for trade entries. Here's a step-by-step guide:
Adjust the ATR Multiplier: Increase the ATR Multiplier to create a higher volatility threshold. A multiplier of 2.0 to 2.5 is a good starting point for very low-volatility markets.
Fine-Tune the ATR Periods: Consider lengthening the ATR calculation period if you find that the strategy is still entering trades in undesirable low-volatility conditions. A longer period provides a more averaged-out measure of volatility, which might better suit your needs.
Monitor and Adjust: Volatility is not static, and market conditions can change. Regularly review the performance of your strategy in the context of current market volatility and adjust the settings as necessary.
Backtest in Different Conditions: Before applying the strategy live, backtest it across different market conditions with your adjusted settings. This process helps ensure that your approach to filtering low-volatility conditions aligns with your trading objectives and risk tolerance.
By fine-tuning the volatility filter settings according to the specific characteristics of the market you're trading in, you can enhance the performance of this strategy
- The **Trailing Stop Loss** and **EMA Exit Conditions** provide two layers of exit strategies, focusing on capital preservation and profit maximization.
**Visualizations**
For clarity and ease of use, the strategy plots the three EMAs and, if enabled, the ATR threshold on the chart. These visual cues not only aid in decision-making but also help in understanding the market's current trend and volatility state.
**How to Use**
Traders can customize the EMA periods to fit their trading horizon, be it short, medium, or long-term trading. The volatility filter and exit options allow for further customization, making the strategy adaptable to different market conditions and personal risk tolerance levels.
By offering a blend of trend-following principles with advanced risk management features, this strategy aims to cater to a wide range of trading styles, from cautious to aggressive. Its strength lies in its flexibility, allowing traders to fine-tune settings to their specific needs, making it a potentially valuable tool in the arsenal of any trader looking for a disciplined approach to navigating the markets.
Zero-lag Volatility-Breakout EMA Trend StrategyThis is a simple volatility-breakout strategy which uses the difference in two different zero-lag* EMAs (explained below on what exactly I mean by this) to track the upwards or downwards strength of an instrument. When the difference breaks above a Bollinger Band of a configurable standard deviation multiple, the strategy enters based off the direction of the base EMA used (i.e. if the difference breaks above and the current EMA is rising, a long entry is produced. If the difference breaks above and the current EMA is falling, a short entry is produced).
The two EMA-type metrics used to calculate the volatility difference are calculated by the following formula:
top_ema = math.max(src, ta.ema(src, length))
bottom_ema = math.min(src, ta.ema(src, length))
ema_difference = (top_ema - bottom_ema) - 1
This produces a difference which responds immediately to large price movements, instead of lagging if it used strictly the EMA itself.
SETTINGS
Source : The source of the strategy - close, hlc3, another indicator plot, etc.
EMA Difference Length : The length of both the EMA difference statistics and the base EMA used to calculate the entry side.
Standard Deviation Multiple : The Bollinger Bands multiple used when the difference is breaking out.
Use Binary Strategy : The strategy has two configurations: Binary and Rapid-Exit. 'Binary' means that it will not close a long position until a short position is generated, and vice-versa. 'Rapid-Exit' will close a long or short position once the difference reaches the middle Bollinger Band MA. This means that turning on 'Binary' will expose you to more market risk, but potentially greater market return. Turning off 'Binary' will exit quickly and reduce drawdown.
The strategy results below use 10% equity and 0.1% fees per trade.
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:
Advanced EMA Cross with Normalized ATR Filter, Controlling ADX
Description:
This strategy is based on EMA cross strategy and additional filters are used to get better results, a normalized ATR filter, and ADX control...
It aims to provide traders with a code base that generates signals for long positions based on market conditions defined by various indicators.
How it Works:
1. EMA: Uses short (8 periods) and long (20 periods) EMAs to identify crossovers.
2. ATR: Uses a 14-period ATR, normalized to its 20-period historical range, to filter out noise.
3. ADX: Uses a 14-period RMA to identify strong trends.
4. Volume: Filters trades based on a 14-period SMA of volume.
5. Super Trend: Uses a Super Trend indicator to identify the market direction.
How to Use:
- Buy Signal: Generated when EMA short crosses above EMA long, and other conditions like ATR and market direction are met.
- Sell Signal: Generated based on EMA crossunder and high ADX value.
Originality and Usefulness:
This script combines EMA, ATR, ADX, and Super Trend indicators to filter out false signals and identify more reliable trading opportunities.
USD Strength in the code is not working, just simulated it as PSEUDO CODE:
Strategy Results:
- Account Size: $1000
- Commission: Not considered
- Slippage: Not considered
- Risk: Manageable through parameters, now less than 5% per trade
- Dataset: Aim for more than 100 trades for a sufficient sample size
- Test Conditions: Test in 30 min chart for BTCUSDT
IMPORTANT NOTE: This script should be used for educational purposes and should not be considered as financial advice.
Chart:
- The script's output is plotted as Buy and Sell signals on the chart.
- No other scripts are included for clarity.
- Have tested with 30mins period
- You are encouraged to play with parameters, let me know if it helps you and/or if you can upgrade the code to a better level.
WHY DID I USE ATR AND ADX?
ATR filter is usually used for the following purposes.
Market Volatility: ATR measures how volatile the market is. High ATR values indicate that the price is experiencing significant fluctuations.
Filtering: Crossing a certain ATR threshold may indicate that the market is active enough to present trading opportunities.
Risk Management: ATR can also be used to set stop-loss and take-profit levels, helping to manage risk effectively.
And ADX is usually used for;
Trend Strength: ADX measures the strength of a trend. High ADX values indicate a strong trend.
Filtering: An ADX value above a certain level suggests that the trend is strong and it might be safer to trade.
Versatility: ADX does not indicate the direction of the trend, only its strength. This makes it useful in both bullish and bearish markets.
Using these indicators together can help filter out false signals and produce more reliable trading signals. While ATR helps to determine if the market is active enough, ADX measures the strength of the trend. Combined, they can create a more complex and effective trading strategy.
I've used ADX data to support generating a buy signal after a golden cross (bullish trend) and waiting until this is a strong trend. It sounds good to check for different trend strengths for bullish and bearish markets to decide a buy signal. Additionally I used ATR to check if the market has enough fluctuations.
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.
CC Trend strategy 2- Downtrend ShortTrend Strategy #2
Indicators:
1. EMA(s)
2. Fibonacci retracement with a mutable lookback period
Strategy:
1. Short Only
2. No preset Stop Loss/Take Profit
3. 0.01% commission
4. When in a profit and a closure above the 200ema, the position takes a profit.
5. The position is stopped When a closure over the (0.764) Fibonacci ratio occurs.
* NO IMMEDIATE RE-ENTRIES EVER!*
How to use it and what makes it unique:
This strategy will enter often and stop quickly. The goal with this strategy is to take losses often but catch the big move to the downside when it occurs through the Silvercross/Fibonacci combination. This is a unique strategy because it uses a programmed Fibonacci ratio that can be used within the strategy and on any program. You can manipulate the stats by changing the lookback period of the Fibonacci retracement and looking at different assets/timeframes.
This description tells the indicators combined to create a new strategy, with commissions and take profit/stop loss conditions included, and the process of strategy execution with a description of how to use it. If you have any questions feel free to PM me and boost if you found it helpful. Thank you, pineUSERS!
CHEATCODE1
Buy Only Strategy with Dynamic Re-Entry and ExitThe strategy aims to create a simple buy-only trading system based on moving average crossovers and the Weekly Commodity Channel Index (CCI) or Weekly Average Directional Index (ADX). It generates buy signals when the fast-moving average crosses above the slow-moving average and when the Weekly CCI and or Weekly ADX meet the specified conditions.
The strategy also allows for dynamic re-entry, which means it can open new long positions if the price goes above the three moving averages after an exit. However, the strategy will exit the long position if the price closes below the third moving average.
ENTRY CONDITIONS
The script defines the conditions for generating buy signals. It checks for two conditions for a valid buy signal:
• If the fast-moving average crosses above the slow-moving average -THERE IS Dynamic Re-Entry also
• If the user chooses HE OR SHE CAN FILTER TRADES BY USING CCI OR ADX
Dynamic Re-Entry:
the script allows for dynamic re-entry. If there is no active long position and the price is above all three moving averages a new long position is opened.
Exit Conditions
The script defines the exit condition for closing a long position. If the price closes below the third moving average, the script closes the long position.
IMPORTANT NOTICE
ONLY DAILY TIME FRAME
THERE WOULD BE WHIPSAW USE YOUR OWN ACCUMEN TO MINIMISE THEM
ITS ONLY BUY STRATEGY
EXIT CAN BE STRATEGY BASED OR SET PROFIT AND TARGETS AS PER RISK APETITE /RISK MANAGEMENT
DONT TRADE OPTIONS ON THIS
SUITABLE FOR STOCKS OF USA AND INDIAN MARKETS
ALWAYS REMEMBER TO DO YOUR OWN RESEARCH BEFORE TRADING AND INVESTING
Yesterday's High v.17.07Yesterday’s High Breakout it is a trading system based on the analysis of yesterday's highs, it works in trend-following mode therefore it opens a long position at the breakout of yesterday's highs even if they occur several times in one day.
There are several methods for exiting a trade, each with its own unique strategy. The first method involves setting Take-Profit and Stop-Loss percentages, while the second utilizes a trailing-stop with a specified offset value. The third method calls for a conditional exit when the candle closes below a reference EMA.
Additionally, operational filters can be applied based on the volatility of the currency pair, such as calculating the percentage change from the opening or incorporating a gap to the previous day's high levels. These filters help to anticipate or delay entry into the market, mitigating the risk of false breakouts.
In the specific case of INJ, a 12% Take-Profit and a 1.5% Stop-Loss were set, with an activated trailing-stop percentage, TRL 1 and OFF 0.5.
To postpone entry and avoid false breakouts, a 1% gap was added to the price of yesterday's highs.
Name: Yesterday's High Breakout - Trend Follower Strategy
Author: @tumiza999
Category: Trend Follower, Breakout of Yesterday's High.
Operating mode: Spot or Futures (only long).
Trade duration: Intraday.
Timeframe: 30M, 1H, 2H, 4H
Market: Crypto
Suggested usage: Short-term trading, when the market is in trend and it is showing high volatility.
Entry: When there is a breakout of Yesterday's High.
Exit: Profit target or Trailing stop, Stop loss or Crossunder EMA.
Configuration:
- Gap to anticipate or postpone the entry before or after the identified level
- Rate of Change for Entry Condition
- Take Profit, Stop Loss and Trailing Stop
- EMA length
Backtesting:
⁃ Exchange: BINANCE
⁃ Pair: INJUSDT
⁃ Timeframe: 4H
- Treshold: 1
- Gap%: 1
- SL: 1.5
- TP:12
- TRL: 1
- OFF-TRL: 0.5
⁃ Fee: 0.075%
⁃ Slippage: 1
- Initial Capital: 10000 USDT
- Position sizing: 10% of Equity
- Start : 2018-07-26 (Out Of Sample from 2022-12-23)
- Bar magnifier: on
Credits: LucF for Pine Coders (f_security function to avoid repainting using security)
Disclaimer: Risk Management is crucial, so adjust stop loss to your comfort level. A tight stop loss can help minimise potential losses. Use at your own risk.
How you or we can improve? Source code is open so share your ideas!
Leave a comment and smash the boost button!
Thanks for your attention, happy to support the TradingView community.
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
Bollinger Bands Modified (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses two indicators Bollinger Bands and EMA (optional for EMA).
Calculates Bollinger Bands, EMA, highest high, and lowest low values based on the input parameters, evaluating the conditions to determine potential long and short entry signals.
The conditions include checks for crossovers and crossunders of the price with the upper and lower Bollinger Bands, as well as the position of the price relative to the EMA.
The script also incorporates the option to add an inside bar pattern check for additional information.
Entry Position
Long Position:
Price cross over the superior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is above EMA.
Short Position:
Price cross under the inferior band of bollinger bands.
The EMA is used to add support for trend analysis, it is an optional input, when used, it checks if price is under EMA.
Risk Management
Stop Loss:
The stop loss is calculated based on the input highest high (for short position) and lowest low (for long position).
It gets the length based on the input from the last candles to set which is the highest high and which is the lowest low.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
9:22 5 MIN 15 MIN BANKNIFTY9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters
The 9:22 5 MIN 15 MIN BANKNIFTY Strategy with Additional Filters is a trend-following strategy designed for trading the BANKNIFTY instrument on a 5-minute chart. It aims to capture potential price movements by generating buy and sell signals based on moving average crossovers, breakout confirmations, and additional filters.
Key Features:
Fast MA Length: 9
Slow MA Length: 22
ATR Length: 14
ATR Filter: 0.5
Trailing Stop Percentage: 1.5%
Pullback Threshold: 0.5
Minimum Candle Body Percentage: 0.5
Use Breakout Confirmation: Enabled
Additional Filters:
Volume Threshold: Set a minimum volume requirement for trades.
Trend Filter: Optionally enable a trend filter based on a higher timeframe moving average.
Momentum Filter: Optionally enable a momentum filter using the RSI indicator.
Support/Resistance Filter: Optionally enable a filter based on predefined support and resistance levels.
Buy and Sell Signals:
Buy Signal: A buy signal is generated when the fast moving average crosses above the slow moving average, with additional confirmation from breakout and volume criteria, along with optional trend, momentum, and support/resistance filters.
Sell Signal: A sell signal is generated when the fast moving average crosses below the slow moving average, with similar confirmation and filtering criteria as the buy signal.
Exit Strategy:
The strategy employs a trailing stop-loss mechanism based on a percentage of the average entry price. The stop-loss is dynamically adjusted to protect profits while allowing for potential upside.
Please note that this strategy should be thoroughly backtested and evaluated in different market conditions before applying it to live trading. It is also recommended to adjust the parameters and filters according to individual preferences and risk tolerance.
Feel free to customise and adapt the description as needed to suit your preferences and the specific details of your strategy.
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.
LowFinder_PyraMider_V2This strategy is a result of an exploration to experiment with other ways to detect lows / dips in the price movement, to try out alternative ways to exit and stop positions and a dive into risk management. It uses a combination of different indicators to detect and filter the potential lows and opens multiple positions to spread the risk and opportunities for unrealized losses or profits. This script combines code developed by fellow Tradingview community_members.
LowFinder
The lows in the price movement are detected by the Low finder script by RafaelZioni . It finds the potential lows based on the difference between RSI and EMA RSI. The MTF RSI formula is part of the MTFindicators library developed by Peter_O and is integrated in the Low finder code to give the option to use the RSI of higher timeframes. The sensitivity of the LowFinder is controlled by the MA length. When potential lows are detected, a Moving Average, a MTF Stochastic (based the the MTFindiicators by Peter_O) and the average price level filter out the weak lows. In the settings the minimal percentage needed for a low to be detected below the average price can be specified.
Order Sizing and Pyramiding
Pyramiding, or spreading multiple positions, is at the heart of this strategy and what makes it so powerful. The order size is calculated based on the max number of orders and portfolio percentage specified in the input settings. There are two order size modes. The ‘base’ mode uses the same base quantity for each order it opens, the ‘multiply’ mode multiplies the quantity with each order number. For example, when Long 3 is opened, the quantity is multiplied by 3. So, the more orders the bigger the consecutive order sizes. When using ‘multiply’ mode the sizes of the first orders are considerably lower to make up for the later bigger order sizes. There is an option to manually set a fixed order size but use this with caution as it bypasses all the risk calculations.
Stop Level, Take Profit, Trailing Stop
The one indicator that controls the exits is the Stop Level. When close crosses over the Stop Level, the complete position is closed and all orders are exited. The Stop Level is calculated based on the highest high given a specified candle lookback (settings). There is an option to deviate above this level with a specified percentage to tweak for better results. You can activate a Take Profit / Trailing Stop. When activated and close crosses the specified percentage, the Stop Level logic changes to a trailing stop to gain more profits. Another option is to use the percentage as a take profit, either when the stop level crosses over the take profit or close. With this option active, you can make this strategy more conservative. It is active by default.
And finally there is an option to Take Profit per open order. If hit, the separate orders close. In the current settings this option is not used as the percentage is 10%.
Stop Loss
I published an earlier version of this script a couple of weeks ago, but it got hidden by the moderators. Looking back, it makes sense because I didn’t pay any attention to risk management and save order sizing. This resulted in unrealistic results. So, in this script update I added a Stop Loss option. There are two modes. The ‘average price’ mode calculates the stop loss level based on a given percentage below the average price of the total position. The ‘equity’ mode calculates the stop loss level based on a given percentage of your equity you want to lose. By default, the ‘equity’ mode is active. By tweaking the percentage of the portfolio size and the stop loss equity mode, you can achieve a quite low risk strategy set up.
Variables in comments
To sent alerts to my exchange I use a webhook server. This works with a sending the information in the form of a comment. To be able to send messages with different quantities, a variable is added to the comment. This makes it possible to open different positions on the exchange with increasing quantities. To test this the quantities are printed in the comment and the quantities are switched off in the style settings.
This code is a result of a study and not intended for use as a worked out and full functioning strategy. Use it at your own risk. To make the code understandable for users that are not so much introduced into pine script (like me), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
VWAP+15EMA with RSIVWAP+EMA+RSI Strategy for the group MelléCasH
This strategy will enter a long position when the closing price is above both the VWAP and the 15 EMA, and the RSI is above the specified overbought level. It will exit the position when the price falls by the specified stop loss percentage, rises by the specified take profit percentage, or when the trailing stop loss (which trails the highest price achieved after the position was entered by the specified percentage) is hit. The VWAP, EMA, and RSI indicators are also plotted on the chart for reference.
Daily Investments Index ScalpThis strategy is based on the DIDI index with our own confirmations and calculated SL/TP .
You can change every setting if you want it to use for another pair, but this is fine tuned for NATURALGAS
The entries are taken when:
Long:
- Buy signal from the DIDI indicator
- Long EMA is underneath the Short EMA
- Price must be Above the Long EMA
- TP1 (default) - ATR based first TP is ATR * 1.2 Multiplier
- TP2 (default) - ATR based first TP is ATR * 2 Multiplier
- TP2 SL is the strategy entry price when we hit the first TP
- SL (default) - Latest swing low with a look back of 17 candles
Short:
- Sell signal from the DIDI indicator
- Long EMA is Above the Short EMA
- Price must be Below the Long EMA
- TP1 (default) - ATR based first TP is ATR * 1.2 Multiplier
- TP2 (default) - ATR based first TP is ATR * 2 Multiplier
- TP2 SL is the strategy entry price when we hit the first TP
- SL (default) - Latest swing low with a look back of 17 candles
It's fairly simple, and i think you can use this base so extend your own strategy
Good luck :)
If you have any questions, feel free to comment
Negroni MA & RSI Strategy, plus trade entry and SL/TP optionsI will start with the context, and some things to think about when using a strategy tool to back-test ideas.
CONTEXT
FIRST: This is derived from other people's work, but I honestly hadn't found a mixed indicator MA strategy tool that does what this now does. If it is out there, apologies!!
This tool can help back-test various MA trends (SMA, EMA, HMA, VWMA); as well as factoring in RSI levels (or not); and can factor in a fixed HTF MA (or not). You can apply a 'retest entry' or a 'breakout entry', and you can also apply various risk mgt for SL/TP orders: 1) No SL/TP; or 2) a fixed %, or 3) dynamic ATR multipliers.
Find below, some details explaining what this tool is attempting to do.
Thank you, tack, salute!
THINGS TO REVIEW (it is not just about 'profitability'!!)
Whilst discretion is always highly encouraged as a trader, and a 100% indicator-driven strategy is VERY unlikely to yield sustainable results going forward, at the very least back-testing your strategies can help provide some guidance, not just on win rate Vs profit factor, but other things including:
a) Trade frequency: if a strategy has an 75% win rate and profit factor of 4, with all your parameters and confluence checks, but only triggers 3 trades every 5 years, is that realistically implementable to your trading situation if you have a $10,000 account?
b) Trade entry type: is it consistently better to wait for a retest of an 'MA zone', or is it better to market buy/sell on breakout of the 'MA zone'?
c) Risk management (SL/TP): is it consistently better to have a fixed static % for SL/TP ("I always place my stops 2% away, whether it is EURUSD or BTCUSDT"), or would you be better placed to try using an ATR multiplier of the respective assets?
d) Moving average type: is your old faithful 100 EMA really serving you well, or is the classic SMA more reliable, or how about the HMA, or the VWMA? Is the 100/200 cross holding up, or do you need something more sensitive? Is there any significant difference between a 10 EMA/20 EMA trend zone compared to a 13 EMA /25 EMA zone?
e) Confluence: Do added confluence checks (RSI, higher timeframe MA) actually improve profitability? But even if they do, is at the cost of cutting too many trades?
INPUTS AND PARAMETERS
Choice 1) Entry Strategy: Retest or Breakout - You can select both!
[ ]:
a) RETEST entry strat: price crosses UNDER FastMA INTO the 'MA trend zone'.
b) BREAKOUT entry strat: price crosses OVER FastMA OUT the 'MA trend zone'.
Choice 2) Risk Management (SL and TP) - You can select more than 1 strategy!
a) No SL/TP: Long trades are closed when the LOW crosses back UNDER the fastMA again, and shorts are closed when the HIGH crosses back OVER the fastMA again.
b) Static % SL/TP: Your SL/TP will be a fixed % away from avg. position price... WARNING: You should change this for various asset classes; FX vol is not the same as crypto altcoin vol!
c) Dynamic ATR SL/TP: Your SL/TP is a multiple of your selected ATR range (default is 50, see 'info' when you select ATR range). ATR accounts for the change in vol of different asset classes somewhat, HOWEVER... you should probably still not have the same multiplier trading S&P500 as you would trading crypto altcoins!
Then select your preferred parameters: EMA, SMA, HMA, VWMA, etc. You can mix and match, and most options have a info/tooltip guide.
RSI note: If you don't care for RSI levels, then set buy signal at 1... i.e always buys! Similarly set sell signal at 99.
ATR note: standard ATR length is usually 14, however... your SL/TP will move POST entry, and can tighten or widen your initial SL/TP... for better AND usually for worse! Go find a trade (strat 3) on the chart, look at the SL/TP lines, now change the number to 5, you'll see.
Fixed HTF MA note: If you don't care for HTF MA confluence, just change the timeframe/options to match the 'Slow MA' options you've chosen.
Fibonacci Moving Averages Input(FibMAI) Fibonacci Moving Averages Input is a strategy based on moving averages cross-over or cross-under signals. The bullish golden cross appears on a chart when a stock's short-term moving average crosses above its long-term moving average. The bearish death cross appears on a chart when a stock’s short-term moving average, crosses below its long-term moving average. The general market consensus values used are the 50-day moving average and the 200-day moving average.
With the (FibMAI) Fibonacci Moving Averages Input strategy you can use any value you choose for your bullish or bearish cross. For visual display purposes I have a lot of the Fib Moving Averages 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987 shown while hiding the chart candlesticks. But to use this indicator I click on only a couple of MA's to see if there's a notable cross-over or cross-under pattern signal. Then, most importantly, I back test those values into the FibMAI strategy Long or Short settings input.
For example, this NQ1! day chart has it's Long or Short settings input as follows:
Bullish =
FibEMA34
cross-over
FibEMA144
Bearish =
FibEMA55
cross-under
FibSMA144
As you can see you can mix or match 4 different MA's values either Exponential or Simple.
Default color settings:
Rising value = green color
Falling value = red color
Default Visual FibMA settings:
FibEMA's 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181
Default Visual MA settings:
SMA's 50, 100, 150, 200
Default Long or Short settings:
Bullish =
FibEMA34
cross-over
FibEMA144
Bearish =
FibEMA55
cross-under
FibSMA144
NIFTY 50 5mint StrategyThis is an intraday strategy for NIFTY50 Based First candle High and Low breakout.
The strategy takes user inputs for the start and end dates, start and end months, and start and end years, which define the time range to trade. The user can also specify the maximum number of trades to take during the time range and the length of the Exponential Moving Average ( EMA ) used in the strategy
In this strategy, the First candle's high and low are calculated and used as entry and exit points for trades. If the close price breaks above the First candle's high, a buy signal is generated. Conversely, if the close price breaks below the First candle's low, a sell signal is generated.
The strategy uses the Exponential Moving Average ( EMA ) as a filter to close entered positions either long or short, EMA also acts Target. If the close price falls below the EMA, a long position is closed, and if the close price rises above the EMA, a short position is closed or the PreviousCandleClose is above the First candle's high a short position is closed, When the PreviousCandleClose is below the First candle's low a long position is closed, First candle's high act as Stoploss
The strategy limits the number of trades taken within the specified time range, and if the time range is exceeded, all positions are closed.
Finally, the strategy plots the First candle's high and low, EMAs on the chart for visual reference.
Default settings work best with the 5mint candle, you may tweak settings according to your needs.
backtesting helps in interpreting how the trading strategy would have behaved in the past, and forward testing (paper trading) informs the traders how it would perform now.
Ema ScalpThis is another simple strategy based on ema
Entry Buy - 1) when close crossover ema then buy and only open one trade till it not close
2) if previous buy trade is profitable open another trade and check again trade is profitable or not
3)if trade is not profitable reset and wait for sell condition...
Entry Sell -1) when close crossunder ema then sell and only open one trade till it not close
2) if previous sell trade is profitable open another trade and check again trade is profitable or not
3) if trade is not profitable reset and wait for buy condition.....
stop loss and take profit is percentage based ...
Strategy Myth-Busting #13 - MultiEMA+BXTrender - [SP/MYN]#13 on the Myth-Busting bench, we are automating the "I Found The Highest Win Rate 15 Minute Scalping Trading Strategy Ever" strategy from "TradeIQ" who claims to have backtested this manually and achieved 410% profit over 100 trades within 6 months on Natural Gas with 79 Wins / 21 Losses with an astounding 3.96% Max Drawdown.
It was quite challenging emulating the same subjective EMA pullback logic along with the dependent sequencing of events necessary to enter a trade and we might improve on this to make it better in the future. Super kudos to @spdoinkal who helped with this strategy. If you have ideas on how this could be improved on, would love to hear about them.
As is, we were unable to substantiate similar results to what was manually backtested by TradeIQ, we do however see potential here. Given some optimizations and improvements to the the entry logic accommodating for a wider more variable margin after pullbacks reestablish above/below the fast EMA we think the performance of this strategy could certainly be improved upon. So not sure if we have totally myth busted this completely at this point in time.
This strategy uses a combination of 2 open-source public indicators:
3 EMA's (Trading View Internal)
B-Xtrender by Puppytherapy
Three separate (21), (89) and (200) EMA's are used as a means to confirm and keep entry out of ranged markets. When the 3 EMA's are all clumped up together with no distance it's indicative of a flat or ranged market. This is then used in conjunction with B-XTrender as a means to detect the trend direction. B-XTrender which is a trend following indicator originally published in the IFTA Journal by Bharat Jhunjhunwala. It uses both a short and long term lengths along with a compound EMA used as a means to smooth and sample trend direction.
Trading Rules
15 min candles but other lower time-frames
Stop Loss on previous swing high/low
No Take Profit, Exit on new red/green circles from BX-Trender
Long
EMA Green (21) on top, White (89)in middle and red (200) on bottom and there is distance between EMA's need to be spaced, otherwise in a ranged market
Price action must pull back into 89 EMA (White line) either close or touching it.
Once pullback occurs wait for BX Trender to issue a new green circle and BX Trend line must be green and above 0
Price action must also pull up back above the (Green Line) EMA 21
Short
EMA Red (200) on top, White (89) in middle and Green (21) on bottom and there is distance between EMA's need to be spaced, otherwise in a ranged market
Price action must pull back into 89 EMA (White line) either close or touching it.
Once pullback occurs wait for BX Trender to issue a new red circle and BX Trend line must be red and below 0
Price action must also pull up back below the (green Line) EMA 21
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Strategy Myth-Busting #23 - 2xEMA+DPO- [MYN]#23 on the Myth-Busting bench, we are automating the "Best Funded Account Trading Strategy (Pass EVERY Challenge!)" strategy from "Trade with Pat" who claims this strategy will pass every trading challenge out there.
This strategy uses 3 open source indicators. 2 EMA's. The first one (Slow) is set to a length of 40 and a fast EMA which is set to 12. This strategy uses the crossover of the fast( 12) EMA over the Slow EMA ( 40 ) as the primary means to enter a long position. The opposite when the fast EMA crosses under the slow EMA as a means to indicate a short position. This strategy uses the DPO (Detrended Price Oscillaor) from the Uptrend Price DPO indicator in the same way we would traditionally use a stochastic or moving average convergence/divergence indicator like the MACD . Basically, the DPO helps evaluate and estimate the length of the price cycle from peak to peek or through to trough and in this strategy confirms entry of a long / short condition complimenting the EMA crossover/crossunders.
And as always, If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
EMA x2 ( 40 and 12)
Untrend Price DPO indicator by jTradeuh
Trading Rules
1 or 4 hour candles
Stop loss at previous highest-high (Short) and lowest-low (Long).
Take Profit 2 - 2.5 the risk
Strategy Template includes open source code from the following:
Performance Summary Dashboard by @VertMT
Time Of Day Window by @ddctv
Monthly Table Performance Dashboard by @QuantNomad
