FVG Positioning Average with 200EMA Auto Trading [Pakun]Description
Strategy Name and Purpose
FVG Positioning Average with 200EMA Auto Trading
This strategy uses Fair Value Gaps (FVG) combined with a 200-period Exponential Moving Average (EMA) and Average True Range (ATR) to generate trend-based trading signals. It is designed to help traders identify high-probability entry points by leveraging the gaps between fair value prices and current market prices.
Originality and Usefulness
This script combines multiple indicators to create a cohesive trading strategy that is greater than the sum of its parts. While FVG is a powerful tool on its own, combining it with the EMA and ATR adds layers of confirmation and risk management, enhancing its effectiveness. Here’s how the components work together:
Fair Value Gap (FVG): Identifies gaps in the market where price action has not fully filled, indicating potential reversal or continuation points.
200-period Exponential Moving Average (EMA): Acts as a trend filter to ensure trades are taken in the direction of the overall trend, improving the probability of success.
Average True Range (ATR): Used to filter out insignificant gaps and set dynamic stop-loss levels based on market volatility, enhancing risk management.
Entry Conditions
Long Entry
The close price crosses above the downtrend FVG.
The close price, FVG up average, and down average are all above the 200 EMA, indicating a strong bullish trend.
Short Entry
The close price crosses below the uptrend FVG.
The close price, FVG up average, and down average are all below the 200 EMA, indicating a strong bearish trend.
Exit Conditions
For long positions, the stop loss is set at the recent low, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
For short positions, the stop loss is set at the recent high, and the take profit is set at a point with a risk-reward ratio of 1:1.5.
Risk Management
Account Size: 1,000,000 yen
Commission and Slippage: 2 pips commission and 1 pip slippage per trade
Risk per Trade: 10% of account equity
The stop loss is based on the recent low or recent high, ensuring trades are exited when the market moves against the position.
Settings Options
FVG Lookback: Set the lookback period for calculating FVGs.
Lookback Type: Choose the type of lookback (Bar Count or FVG Count).
ATR Multiplier: Set the multiplier for ATR to filter significant gaps.
EMA Period: Set the period for the EMA to adjust the trend filter sensitivity.
Show FVGs on Chart: Choose whether to display FVGs on the chart for visual confirmation.
Bullish/Bearish Color: Set the color for bullish and bearish FVGs to distinguish them easily.
Show Gradient Areas: Choose whether to display gradient areas to highlight the zones of interest.
Sufficient Sample Size
The strategy has been backtested with 113 trades, providing a sufficient sample size to evaluate its performance.
Notes
This strategy is based on historical data and does not guarantee future results.
Thoroughly backtest and validate results before using in live trading.
Market volatility and other external factors can affect performance and may not yield expected results.
Acknowledgment
This strategy uses the FVG Positioning Average Strategy indicator. Thanks to for their contribution.
Clean Chart Explanation
The script is published with a clean chart to ensure that its output is readily identifiable and easy to understand. No other scripts are included on the chart, and any drawings or images used are specifically to illustrate how the script works.
Moving Averages
Scalp Slayer (i)📊 The Foundation: Core Parameters and Inputs
Filter Number: This parameter is the cornerstone of the script’s sensitivity control. It adjusts the threshold for market volatility that the script considers significant enough for a trade. By default, it's set to 1.5, striking a balance between aggressiveness and conservatism. Traders can tweak this number to make the script more or less sensitive to price fluctuations. A higher number captures smaller, more frequent price movements, ideal for an aggressive trading style. Conversely, a lower number filters out minor noise, focusing on more substantial movements.
EMA Trend Period: The Exponential Moving Average (EMA) is critical for identifying the market's direction. The script uses an EMA calculated over a default period of 50 bars to discern whether the market is trending up or down. This helps in making decisions that align with the overall market trend, thereby increasing the likelihood of successful trades.
Lookback Period: This parameter, set to 20 periods by default, is used to calculate recent highs and lows. These values are crucial for setting realistic take profit and stop-loss levels, as they reflect recent market behavior. The lookback period helps the script adapt to current market conditions by analyzing recent price actions to identify key support and resistance levels.
Color Settings: For enhanced visualization, the script allows customization of colors for take profit and stop-loss markers. By default, take profit levels are marked in orange, and stop-loss levels in red. This color coding helps traders quickly identify important levels on the chart.
Visibility Controls: The script includes options to toggle the display of buy and sell labels, as well as to enable or disable strategy plotting for backtesting and real-time analysis. These controls help traders tailor the script’s visual output to their preferences, making it easier to focus on key trading signals.
🛠️ The Mechanics: How "Scalp Slayer (i)" Operates
1. Calculating the Trading Range and Trend EMA
True Range Calculation: The script begins by calculating the true range, which is the difference between the high and low prices of a bar. This measure of volatility is crucial for identifying significant price movements.
EMA of True Range: The script then smooths the true range using an Exponential Moving Average (EMA). This helps filter out minor price fluctuations, ensuring that the script only reacts to meaningful changes in price. The sensitivity of this filter is adjusted by the filter number, which multiplies the EMA to fine-tune the script's responsiveness to price changes.
Trend EMA: To determine the market’s trend, the script calculates an EMA over the close prices for the specified trend period (default is 50). This trend EMA acts as a benchmark for identifying whether the market is trending up or down. The script uses this trend filter to ensure trades are made in the direction of the prevailing market trend, thereby reducing the risk of trading against the trend.
2. Identifying Recent Highs and Lows
Recent Highs and Lows: The script uses the lookback period to identify the highest and lowest prices over a set number of bars. These recent highs and lows serve as reference points for setting take profit and stop-loss levels. By analyzing recent price action, the script ensures that these levels are relevant to current market conditions, providing a dynamic and contextually accurate approach to risk management.
🔄 Strategic Entry and Exit Conditions
3. Defining Buy and Sell Conditions
Buy Condition: The script establishes a set of criteria for entering a buy trade. First, the closing price must be above the trend EMA, indicating an upward trend. Additionally, the script looks for a sequence of candles showing progressively higher closes, signifying strong upward momentum. The current trading range must exceed the EMA of the true range, confirming that the market is experiencing significant movement. This combination of trend alignment and momentum ensures that buy trades are placed in favorable market conditions.
Sell Condition: Similarly, for sell trades, the script requires the closing price to be below the trend EMA, indicating a downward trend. It also checks for a sequence of candles with progressively lower closes, indicating strong downward momentum. The trading range must again exceed the EMA of the true range, ensuring that the market is moving significantly. These conditions help ensure that sell trades are only taken when the market is likely to continue moving downwards, increasing the chances of profitable trades.
4. Executing Trades and Setting Profit Targets
Long Entry: When the buy condition is met, the script enters a long position at the closing price of the confirmation bar. It then sets a take profit level at the recent high, which serves as a realistic target based on recent price action. The stop-loss level is set at the recent low, providing a safety net against adverse price movements. This approach ensures that trades are closed at optimal points, maximizing profit while minimizing risk.
Short Entry: When the sell condition is met, the script enters a short position at the closing price of the confirmation bar. The take profit level is set at the recent low, and the stop-loss level is set at the recent high. This setup ensures that short trades are closed at favorable levels, capturing gains while protecting against potential losses.
5. Managing Take Profit and Stop Loss
Take Profit and Stop Loss Mechanism: The script continually monitors the market for conditions that meet the take profit or stop-loss criteria. For long trades, the script closes the position if the price reaches or exceeds the take profit level, ensuring profits are locked in. It also closes the position if the price drops to or below the stop-loss level, preventing further losses. For short trades, the script closes the position if the price drops to or below the take profit level, or rises to or above the stop-loss level. This dynamic management of trades helps ensure that profits are maximized while risks are minimized.
🌟 Enhanced Visuals and Debugging Features
Customizable and Informative Plots
Buy and Sell Labels: The script includes options to display labels for buy and sell signals on the chart. These labels provide clear visual cues for trading opportunities, making it easy to identify entry points at a glance. Traders can customize the visibility of these labels based on their preferences, helping them focus on the most important signals.
Take Profit and Stop Loss Markers: To aid in monitoring trades, the script displays distinctive markers for take profit and stop-loss levels. These markers are color-coded for easy differentiation and are placed on the chart to provide clear indications of where trades are likely to be closed. This visual representation helps traders quickly assess the status of their trades and make informed decisions.
Trend and Price Plots: The script plots the trend EMA and recent highs/lows on the chart for quick reference. These plots provide a visual representation of key levels and trends, helping traders make more informed decisions based on current market conditions. By displaying these critical levels, the script enhances situational awareness and aids in the decision-making process.
Debugging and Validation Tools
Bar Index Plotting: For those interested in validating the script's performance, the script includes options to plot the bar index. This feature allows traders to monitor the script's behavior in real-time, ensuring that it is functioning as expected. This can be particularly useful for debugging and optimizing the script.
Condition Printing: The script also includes options to print detailed information about take profit and stop-loss conditions. This feature provides insights into the script's decision-making process, helping traders understand why certain trades were executed or closed. By providing transparency into the script's logic, this feature aids in fine-tuning and improving the script's performance.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
MA MACD BB BackTesterOverview:
This Pine Script™ code provides a comprehensive backtesting tool that combines Moving Average (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands (BB). It is designed to help traders analyze market trends and make informed trading decisions by testing various strategies over historical data.
Key Features:
1. Customizable Indicators:
Moving Average (MA): Smooths out price data for clearer trend direction.
MACD: Measures trend momentum through MACD Line, Signal Line, and Histogram.
Bollinger Bands (BB): Identifies overbought or oversold conditions with upper and lower bands.
2. Flexible Trading Direction: Choose between long or short positions to adapt to different market conditions.
3. Risk Management: Efficiently allocate your capital with customizable position sizes.
4. Signal Generation:
Buy Signals: Triggered by crossovers for MACD, MA, and BB.
Sell Signals: Triggered by crossunders for MACD, MA, and BB.
5. Automated Trading: Automatically enter and exit trades based on signal conditions and strategy parameters.
How It Works:
1. Indicator Selection: Select your preferred indicator (MA, MACD, BB) and trading direction (Long/Short).
2. Risk Management Configuration: Set the percentage of capital to allocate per position to manage risk effectively.
3.Signal Detection: The algorithm identifies and plots buy/sell signals directly on the chart based on the chosen indicator.
4. Trade Execution: The strategy automatically enters and exits trades based on signal conditions and configured strategy parameters.
Use Cases:
- Backtesting: Evaluate the effectiveness of trading strategies using historical data to understand potential performance.
- Strategy Development: Customize and expand the strategy to incorporate additional indicators or conditions to fit specific trading styles.
ADDONS That Affect Strategy:
1. Indicator Parameters:
Adjustments to the settings of MACD (e.g., fast length, slow length), MA (e.g., length), and BB (e.g., length, multiplier) will directly impact the detection of signals and the strategy's performance.
2. Trading Direction:
Changing the trading direction (Long/Short) will alter the entry and exit conditions based on the detected signals.
3. Risk Management Settings:
Modifying the position size percentage affects capital allocation and overall risk exposure per trade.
ADDONS That Do Not Affect Strategy:
1. Visual Customizations:
Changes to the color, shape, and style of the plotted lines and signals do not impact the core functionality of the strategy but enhance visual clarity.
2. Text and Labels:
Modifying text labels for the signals (such as renaming "Buy MACD" to "MACD Buy Signal") is purely cosmetic and does not influence the strategy’s logic or outcomes.
Notes:
- Customization: The indicator is highly customizable to fit various trading styles and market conditions.
- Risk Management: Adjust position sizes and risk parameters according to your risk tolerance and account size.
- Optimization: Regularly backtest and optimize parameters to adapt to changing market dynamics for better performance.
Getting Started:
-Add the script to your chart.
-Adjust the input parameters to suit your analysis preferences.
-Observe the marked buy and sell signals on your chart to make informed trading decisions.
Uptrick:Intensity IndexPurpose:
The "Uptrick: Intensity Index" strategy is designed to provide traders with insights into the trend intensity of security by combining multiple moving averages and their relative positions. This versatile tool can be used effectively by both short-term and long-term traders to identify potential buy and sell signals based on specific conditions.
Explanation:
Input Parameters and Customization:
Moving Averages Lengths:
Adjust MA1, MA2, and MA3 lengths to change the calculation periods for the moving averages.
Trend Intensity Index SMA Length:
Adjust the length of the SMA applied to the TII.
Plot Colors:
Change the colors of the TII and TII MA plots for better visualization.
Background Colors and Transparency:
Set different colors for positive and negative TII MA values.
Control the transparency of the background color.
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MA1 (Length 10): Short-term moving average, useful for capturing short-term market trends.
MA2 (Length 20): Medium-term moving average, providing a balanced view of market trends.
MA3 (Length 50): Long-term moving average, offering insights into long-term market trends.
The script calculates the relative positions of the closing price to each moving average (rel1, rel2, rel3) to determine how far the current price deviates from each average.
Trend Intensity Index (TII):
The TII is calculated as the average of the relative positions (rel1, rel2, rel3), multiplied by 100 to convert it into a percentage. This index reflects the overall intensity of the trend, considering short-term, medium-term, and long-term perspectives.
The TII is plotted in blue, providing a visual representation of trend intensity.
SMA of TII:
An additional SMA is applied to the TII (matii) to smooth out fluctuations and provide a clearer long-term trend signal.
The SMA of TII is plotted in orange, offering a reference for long-term trend analysis.
Determining Potential Price Movements:
For Short-Term Traders:
When the blue TII line crosses above the orange SMA of TII line, it indicates a potential buy signal.
When the blue TII line crosses below the orange SMA of TII line, it indicates a potential sell signal.
For Long-Term Traders:
When the orange SMA of TII line crosses above the highlighted 0 line, it indicates a potential buy signal.
When the orange SMA of TII line crosses below the highlighted 0 line, it indicates a potential sell signal.
Plotting and Visualization:
The TII and its SMA are plotted with distinct colors for easy identification.
A horizontal line at 0 is plotted in gray to serve as a reference point for long-term trend signals.
The background color changes based on the value of the SMA of TII (matii):
Green background for matii values above 0, indicating bullish conditions.
Red background for matii values below 0, indicating bearish conditions.
Utility and Potential Usage:
The "Uptrick: Intensity Index" indicator is a powerful tool for both short-term and long-term traders, offering clear buy and sell signals based on the crossover of the TII and its SMA, as well as the position of the SMA relative to the zero line.
By consolidating multiple moving averages and their relative positions into a single indicator, traders can gain comprehensive insights into market trends and intensity.
The ability to adjust all inputs and toggle visibility options enhances the flexibility and utility of the indicator, making it suitable for various trading styles and market conditions.
Through its versatile design and advanced features, the "Uptrick: Intensity Index" indicator equips traders with actionable insights into trend intensity and potential price movements. By integrating this robust tool into their trading strategies, traders can navigate the markets with greater precision and confidence, thereby enhancing their trading outcomes.
WHAT SETTINGS TO HAVE FOR THE MOVING AVERAGE:
Short-term traders (day traders) might prefer a shorter SMA length (e.g., 5-20 periods) as they are looking for quick signals and react to price changes more rapidly.
Medium-term traders (swing traders) might opt for a medium SMA length (e.g., 20-50 periods) which can filter out some noise and provide a clearer signal on the trend.
Long-term traders (position traders) might choose a longer SMA length (e.g., 50-200 periods) to get a broader view of the market trend and avoid reacting to short-term fluctuations.
Versatile Moving Average StrategyVersatile Moving Average Strategy (VMAS)
Overview:
The Versatile Moving Average Strategy (VMAS) is designed to provide traders with a flexible approach to trend-following, utilizing multiple types of moving averages. This strategy allows for customization in choosing the moving average type and length, catering to various market conditions and trading styles.
Key Features:
- Multiple Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, VWMA, HULL, LSMA, and ALMA to best suit your trading needs.
- Customizable Inputs: Adjust the moving average length, source of price data, and stop-loss source to fine-tune the strategy.
- Target Percent: Set the percentage difference between successive profit targets to manage your risk and rewards effectively.
- Position Management: Enable or disable long and short positions, allowing for versatility in different market conditions.
- Commission and Slippage: The strategy includes realistic commission settings to ensure accurate backtesting results.
Strategy Logic:
1. Moving Average Calculation: The selected moving average is calculated based on user-defined parameters.
2. Entry Conditions:
- A long position is entered when the entry source crosses over the moving average, if long positions are enabled.
- A short position is entered when the entry source crosses under the moving average, if short positions are enabled.
3. Stop-Loss: Positions are closed if the stop-loss source crosses the moving average in the opposite direction.
4. Profit Targets: Multiple profit targets are defined, with each target set at an incremental percentage above (for long positions) or below (for short positions) the entry price.
Default Properties:
- Account Size: $10000
- Commission: 0.01% per trade
- Risk Management: Positions are sized to risk 80% of the equity per trade, because we get very tight stoploss when position is open.
- Sample Size: Backtesting has been conducted to ensure a sufficient sample size of trades, ideally more than 100 trades.
How to Use:
1. Configure Inputs: Set your preferred moving average type, length, and other input parameters.
2. Enable Positions: Choose whether to enable long, short, or both types of positions.
3. Backtest and Analyze: Run backtests with realistic settings and analyze the results to ensure the strategy aligns with your trading goals.
4. Deploy and Monitor: Once satisfied with the backtesting results, deploy the strategy in a live environment and monitor its performance.
This strategy is suitable for traders looking to leverage moving averages in a versatile and customizable manner. Adjust the parameters to match your trading style and market conditions for optimal results.
Note: Ensure the strategy settings used for publication are the same as those described here. Always conduct thorough backtesting before deploying any strategy in a live trading environment.
Entry Fragger - Strategy
For basic instructions please visit my other script "Entry Fragger".
The Signal Logic is explained there.
v1.4:
- Added advanced backtesting with fully customizable entries.
- Fully automated Buy Signals (profitable).
- Adjustable timeframes for signal logic. (requested)
Every setting affects the accuracy and profitability greatly now, based on settings applied.
The strategy performs best on high timeframes with larger capital and no leverage.
Useless for Forex, but absolutely smashes stocks and crypto on mid to high timeframes.
Please read through my other scripts description.
Set values as preferred and try your assets.
It does NOT work on low timeframes and forex!
Hint: BTC 4H, Custom Timeframe 1h, Moon Mode and Show Sell Signals enabled, R2R: 2.
Kaufman Adaptive Moving Average (KAMA) Strategy [TradeDots]"The Kaufman Adaptive Moving Average (KAMA) Strategy" is a trend-following system that leverages the adaptive qualities of the Kaufman Adaptive Moving Average (KAMA). This strategy is distinguished by its ability to adjust dynamically to market volatility, enhancing trading accuracy by minimizing the effects of false and delayed signals often associated with the Simple Moving Average (SMA).
HOW IT WORKS
This strategy is centered around use of the Kaufman Adaptive Moving Average (KAMA) indicator, which refines the principles of the Exponential Moving Average (EMA) with a superior smoothing technique.
KAMA distinguishes itself by its responsiveness to changes in market prices through an "Efficiency Ratio (ER)." This ratio is computed by dividing the recent absolute net price change by the cumulative sum of the absolute price changes over a specified period. The resulting ER value ranges between 0 and 1, where 0 indicates high market noise and 1 reflects stronger market momentum.
Using ER, we could get the smoothing constant (SC) for the moving average derived using the following formula:
fastest = 2/(fastma_length + 1)
slowest = 2/(slowma_length + 1)
SC = math.pow((ER * (fastest-slowest) + slowest), 2)
The KAMA line is then calculated by applying the SC to the difference between the current price and the previous KAMA.
APPLICATION
For entering long positions, this strategy initializes when there is a sequence of 10 consecutive rising KAMA lines. Conversely, a sequence of 10 consecutive falling KAMA lines triggers sell orders for long positions. The same logic applies inversely for short positions.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Golden Cross VWMA & EMA 4h PinescriptlabsThis strategy combines the 50-period Volume-Weighted Moving Average (VWMA) on the current timeframe with a 200-period Simple Moving Average (SMA) on the 4-hour timeframe. This combination of indicators with different characteristics and time horizons aims to identify strong and sustained trends across multiple timeframes.
The VWMA is a variant of the moving average that assigns greater weight to periods of higher volatility, helping to avoid misleading signals. On the other hand, the 4-hour SMA is used as an additional trend filter in a shorter-term horizon. By combining these two indicators, the strategy can leverage the strength of the VWMA to capture the main trend, but only when confirmed by the SMA in the lower timeframe.
Buy signals are generated when the VWMA crosses above the 4-hour SMA, indicating a potential bullish trend aligned in both timeframes. Sell signals occur on a bearish cross, suggesting a possible reversal of the main trend.
The default parameters are a 50-period VWMA and a 200-period 4-hour SMA. It is recommended to adjust these lengths according to the traded instrument and the desired timeframe. It is also crucial to use stop losses and profit targets to properly manage risk.
By combining indicators of different types and timeframes, this strategy aims to provide a more comprehensive view of trend strength.
Español:
Esta estrategia combina la Volume-Weighted Moving Average (VWMA) de 50 períodos en el timeframe actual con una Simple Moving Average (SMA) de 200 períodos en el timeframe de 4 horas. Esta combinación de indicadores de distinta naturaleza y horizontes temporales busca identificar tendencias fuertes y sostenidas en múltiples timeframes.
La VWMA es una variante de la media móvil que asigna mayor ponderación a los períodos de mayor volatilidad, lo que ayuda a evitar señales engañosas. Por otro lado, la SMA de 4 horas se utiliza como un filtro adicional de tendencia en un horizonte de corto plazo. Al combinar estos dos indicadores, la estrategia puede aprovechar la fortaleza de la VWMA para capturar la tendencia principal, pero sólo cuando es confirmada por la SMA en el timeframe menor.
Las señales de compra se generan cuando la VWMA cruza al alza la SMA de 4 horas, indicando una potencial tendencia alcista alineada en ambos horizontes temporales. Las señales de venta ocurren en el cruce bajista, sugiriendo una posible reversión de la tendencia principal.
Los parámetros predeterminados son: VWMA de 50 períodos y SMA de 4 horas de 200 períodos. Se recomienda ajustar estas longitudes según el instrumento operado y el horizonte temporal deseado. También es crucial utilizar stops y objetivos de ganancias para controlar adecuadamente el riesgo.
Al combinar indicadores de diferentes tipos y timeframes, esta estrategia busca brindar una visión más completa de la fuerza de la tendencia.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Moving average strategyNAME : Moving average strategy
SUMMARY
Long when Short MA period > Long MA period
Exit when Short MA period < Long MA period
Long only strategy, but you can modify this script.
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This strategy uses a moving average line.
It buys when the short-term moving average crosses the long-term moving average and sells when the long-term moving average crosses the short-term moving average.
You can use different moving average lines by setting the MA type.
You can use SMA, EMA, DEMA, TEMA, WMA, and VWMA.
You can also adjust the period of the moving average line.
Price Type sets the type of price that will be used for the moving average line. The options are Close price, Open price, High price, Low price, Typical price, and center price.
High MDD and long periods of sideways movement make it difficult to use in practice, even though the returns may seem high.
Hopefully, you can combine it with other indicators to create a good strategy.
Thank you.
Alligator + MA Trend Catcher [TradeDots]The "Alligator + MA Trend Catcher" is a trading strategy that integrates the William Alligator indicator with a Moving Average (MA) to establish robust entry and exit conditions, optimized for capturing trends.
HOW IT WORKS
This strategy combines the traditional William Alligator set up with an additional Moving Average indicator for enhanced trend confirmation, creating a user-friendly backtesting tool for traders who prefer the Alligator method.
The original Alligator strategy can frequently present fluctuations, even in well-established trends, leading to potentially premature exits. To mitigate this, we incorporate a Moving Average as a secondary confirmation measure to ensure the market trend has indeed shifted.
Here’s the operational flow for long orders:
Entry Signal: When the price rises above the Moving Average, it confirms a bullish market state. Enter if Alligator spread in an upward direction. The trade remains active even if the Alligator indicator suggests a trend reversal.
Exit Signal: The position is closed when the price falls below the Moving Average, and the Alligator spreads in the downward direction. This setup helps traders to maintain positions through the entirety of the trend for maximum gain.
APPLICATION
This strategy is tailored for assets with significant, well-defined trends, such as Bitcoin and Ethereum, which are known for their high volatility and substantial price movements.
This strategy offers a low win-rate but high reward configuration, making asset selection critical for long-term profitability. If you choose assets that lack strong price momentum, there's a high chance that this strategy may not be effective.
For traders seeking to maximize gains from large trends without exiting prematurely, this strategy provides an aggressive yet controlled approach to riding out substantial market waves.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Multi Timeframe RSI Buy Sell Strategy [TradeDots]The "Multi Timeframe RSI Buy/Sell Strategy" is a trading strategy that utilizes Relative Strength Index (RSI) indicators from multiple timeframes to provide buy and sell signals.
This strategy allows for extensive customization, supporting up to three distinct RSIs, each configurable with its own timeframe, length, and data source.
HOW DOES IT WORK
This strategy integrates up to three RSIs, each selectable from different timeframes and customizable in terms of length and source. Users have the flexibility to define the number of active RSIs. These selections visualize as plotted lines on the chart, enhancing interpretability.
Users can also manage the moving average of the selected RSI lines. When multiple RSIs are active, the moving average is calculated based on these active lines' average value.
The color intensity of the moving average line changes as it approaches predefined buying or selling thresholds, alerting users to potential signal generation.
A buy or sell signal is generated when all active RSI lines simultaneously cross their respective threshold lines. Concurrently, a label will appear on the chart to signify the order placement.
For those preferring not to display order information or activate the strategy, an "Enable backtest" option is provided in the settings for toggling activation.
APPLICATION
The strategy leverages multiple RSIs to detect extreme market conditions across various timeframes without the need for manual timeframe switching.
This feature is invaluable for identifying divergences across timeframes, such as detecting potential short-term reversals within broader trends, thereby aiding traders in making better trading decisions and potentially avoiding losses.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 60%
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
TradeDots Stochastic Z-Score
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
GM-8 and ADX Strategy with Second EMADescription:
This TradingView script implements a trading strategy based on the Moving Average (GM-8), the Average Directional Index (ADX), and the second Exponential Moving Average (EMA). The strategy utilizes these indicators to identify potential buy and sell signals on the chart.
Indicators:
GM-8 (Moving Average 8): This indicator calculates the average price of the last 8 periods and is used to identify trends.
ADX (Average Directional Index): The ADX measures the strength of a trend and is used to determine whether the market is moving in a particular direction or not.
Second EMA (Exponential Moving Average): This is an additional EMA line with a period of 59, which is used to provide additional confirmation signals for the trend.
Trading Conditions:
Buy Condition: A buy signal is generated when the closing price is above the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Sell Condition: A sell signal is generated when the closing price is below the GM-8 and the second EMA, and the ADX value is above the specified threshold.
Trading Logic:
If a buy condition is met, a long position is opened with a user-defined lot size.
If a sell condition is met, a short position is opened with the same user-defined lot size.
Positions are closed when the opposite conditions are met.
User Parameters:
Users can adjust the periods for the GM-8, the second EMA, and the ADX, as well as the threshold for the ADX and the lot size according to their preferences.
Note:
This script has been developed for use on a $100,000 account with FTMO, therefore the account size is set to $100,000. Please ensure that the strategy parameters and settings meet the requirements of your trading strategy and carefully review the results before committing real capital.
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Beschreibung:
Dieses TradingView-Skript implementiert eine Handelsstrategie, die auf dem gleitenden Mittelwert (GM-8), dem Average Directional Index (ADX) und der zweiten exponentiellen gleitenden Durchschnittslinie (EMA) basiert. Die Strategie verwendet diese Indikatoren, um potenzielle Kauf- und Verkaufssignale auf dem Chart zu identifizieren.
Indikatoren:
GM-8 (Gleitender Mittelwert 8): Dieser Indikator berechnet den Durchschnittspreis der letzten 8 Perioden und wird verwendet, um Trends zu identifizieren.
ADX (Average Directional Index): Der ADX misst die Stärke eines Trends und wird verwendet, um festzustellen, ob sich der Markt in eine bestimmte Richtung bewegt oder nicht.
Zweite EMA (Exponential Moving Average): Dies ist eine zusätzliche EMA-Linie mit einer Periode von 59, die verwendet wird, um zusätzliche Bestätigungssignale für den Trend zu liefern.
Handelsbedingungen:
Kaufbedingung: Es wird ein Kaufsignal generiert, wenn der Schlusskurs über dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Verkaufsbedingung: Es wird ein Verkaufssignal generiert, wenn der Schlusskurs unter dem GM-8 und der zweiten EMA liegt und der ADX-Wert über dem angegebenen Schwellenwert liegt.
Handelslogik:
Wenn eine Kaufbedingung erfüllt ist, wird eine Long-Position mit einer benutzerdefinierten Losgröße eröffnet.
Wenn eine Verkaufsbedingung erfüllt ist, wird eine Short-Position mit derselben benutzerdefinierten Losgröße eröffnet.
Positionen werden geschlossen, wenn die Gegenbedingungen erfüllt sind.
Benutzerparameter:
Benutzer können die Perioden für den GM-8, die zweite EMA und den ADX sowie den Schwellenwert für den ADX und die Losgröße nach ihren eigenen Präferenzen anpassen.
Hinweis:
Dieses Skript wurde für die Verwendung auf einem $100.000-Konto bei FTMO entwickelt, daher ist die Kontogröße auf $100.000 festgelegt. Bitte stellen Sie sicher, dass die Strategieparameter und -einstellungen den Anforderungen Ihrer Handelsstrategie entsprechen und dass Sie die Ergebnisse sorgfältig überprüfen, bevor Sie echtes Kapital einsetzen.
Kyrie Crossover ( @zaytradellc )Unlocking Market Dynamics: Kyrie Crossover Script by @zaytradellc
personalized trading success with the "Kyrie Crossover" script, meticulously crafted by @zaytrade. This innovative Pine Script, tailored to the birthdays of Kyrie and the script creator, combines the power of technical analysis with a touch of personalization to revolutionize your trading experience.
**Exponential Moving Average (EMA) Crossover Strategy:**
At the heart of the "Kyrie Crossover" script lies a sophisticated EMA crossover strategy. By utilizing a 10-period EMA and a 323-period EMA (symbolizing long term price action ), the strategy effectively captures market trends with precision and insight.
- **Short-Term EMA (10-period):** This EMA reacts swiftly to recent price changes, offering heightened sensitivity to short-term fluctuations. It excels in identifying immediate shifts in market sentiment, making it invaluable for pinpointing short-lived trends and potential reversal points.
- **Long-Term EMA (323-period):** In contrast, the long-term EMA provides a broader perspective by smoothing out short-term noise and focusing on longer-term trend direction. Its extended length filters out market noise effectively, providing a clear representation of the underlying trend's momentum and sustainability.
**Directional Movement Index (DMI) Metrics:**
The "Kyrie Crossover" script goes beyond traditional indicators by incorporating DMI metrics across multiple timeframes. By assessing trend strength and direction, traders gain valuable insights into market dynamics, allowing for informed decision-making.
**Simple Instructions to Profit:**
1. **Identify EMA Crossovers:** Look for instances where the short-term EMA (10-period) crosses above the long-term EMA (323-period) for a bullish signal, indicating a potential buying opportunity. Conversely, a crossover where the short-term EMA crosses below the long-term EMA signals a bearish trend and a potential selling opportunity.
2. **Confirm with DMI Metrics:** Validate EMA crossovers by checking DMI metrics across different timeframes (5 minutes, 15 minutes, 30 minutes, and 1 hour). Pay attention to color-coded indicators, with green indicating a bullish trend, red indicating a bearish trend, and white indicating no clear trend.
3. **Manage Risk:** Implement proper risk management techniques, such as setting stop-loss orders and position sizing based on your risk tolerance and trading objectives.
4. **Stay Informed:** Regularly monitor market conditions and adjust your trading strategy accordingly based on new signals and emerging trends.
Bitcoin Momentum StrategyThis is a very simple long-only strategy I've used since December 2022 to manage my Bitcoin position.
I'm sharing it as an open-source script for other traders to learn from the code and adapt it to their liking if they find the system concept interesting.
General Overview
Always do your own research and backtesting - this script is not intended to be traded blindly (no script should be) and I've done limited testing on other markets beyond Ethereum and BTC, it's just a template to tweak and play with and make into one's own.
The results shown in the strategy tester are from Bitcoin's inception so as to get a large sample size of trades, and potential returns have diminished significantly as BTC has grown to become a mega cap asset, but the script includes a date filter for backtesting and it has still performed solidly in recent years (speaking from personal experience using it myself - DYOR with the date filter).
The main advantage of this system in my opinion is in limiting the max drawdown significantly versus buy & hodl. Theoretically much better returns can be made by just holding, but that's also a good way to lose 70%+ of your capital in the inevitable bear markets (also speaking from experience).
In saying all of that, the future is fundamentally unknowable and past results in no way guarantee future performance.
System Concept:
Capture as much Bitcoin upside volatility as possible while side-stepping downside volatility as quickly as possible.
The system uses a simple but clever momentum-style trailing stop technique I learned from one of my trading mentors who uses this approach on momentum/trend-following stock market systems.
Basically, the system "ratchets" up the stop-loss to be much tighter during high bearish volatility to protect open profits from downside moves, but loosens the stop loss during sustained bullish momentum to let the position ride.
It is invested most of the time, unless BTC is trading below its 20-week EMA in which case it stays in cash/USDT to avoid holding through bear markets. It only trades one position (no pyramiding) and does not trade short, but can easily be tweaked to do whatever you like if you know what you're doing in Pine.
Default parameters:
HTF: Weekly Chart
EMA: 20-Period
ATR: 5-period
Bar Lookback: 7
Entry Rule #1:
Bitcoin's current price must be trading above its higher-timeframe EMA (Weekly 20 EMA).
Entry Rule #2:
Bitcoin must not be in 'caution' condition (no large bearish volatility swings recently).
Enter at next bar's open if conditions are met and we are not already involved in a trade.
"Caution" Condition:
Defined as true if BTC's recent 7-bar swing high minus current bar's low is > 1.5x ATR, or Daily close < Daily 20-EMA.
Trailing Stop:
Stop is trailed 1 ATR from recent swing high, or 20% of ATR if in caution condition (ie. 0.2 ATR).
Exit on next bar open upon a close below stop loss.
I typically use a limit order to open & exit trades as close to the open price as possible to reduce slippage, but the strategy script uses market orders.
I've never had any issues getting filled on limit orders close to the market price with BTC on the Daily timeframe, but if the exchange has relatively low slippage I've found market orders work fine too without much impact on the results particularly since BTC has consistently remained above $20k and highly liquid.
Cost of Trading:
The script uses no leverage and a default total round-trip commission of 0.3% which is what I pay on my exchange based on their tier structure, but this can vary widely from exchange to exchange and higher commission fees will have a significantly negative impact on realized gains so make sure to always input the correct theoretical commission cost when backtesting any script.
Static slippage is difficult to estimate in the strategy tester given the wide range of prices & liquidity BTC has experienced over the years and it largely depends on position size, I set it to 150 points per buy or sell as BTC is currently very liquid on the exchange I trade and I use limit orders where possible to enter/exit positions as close as possible to the market's open price as it significantly limits my slippage.
But again, this can vary a lot from exchange to exchange (for better or worse) and if BTC volatility is high at the time of execution this can have a negative impact on slippage and therefore real performance, so make sure to adjust it according to your exchange's tendencies.
Tax considerations should also be made based on short-term trade frequency if crypto profits are treated as a CGT event in your region.
Summary:
A simple, but effective and fairly robust system that achieves the goals I set for it.
From my preliminary testing it appears it may also work on altcoins but it might need a bit of tweaking/loosening with the trailing stop distance as the default parameters are designed to work with Bitcoin which obviously behaves very differently to smaller cap assets.
Good luck out there!
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.
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.
Triple MA HTF strategy - Dynamic SmoothingThe triple MA strategy is a simple but effective method to trade the trend. The advantage of this script over the existing triple MA strategies is that the user can open a lower time frame chart and select higher time frame inputs for different MA types mainting the visibility on the chart. The dynamic smoothing code makes sure the HTF trendlines are not jagged, but a fluid line visiable on the lower time frame chart. The script comes with a MA crossover and crossunder strategy explained below.
Moving Averages (MA) Crossover for Entry:
Long Entry: A long entry signal is triggered when the moving average line 1 crosses above the moving average line 2. This crossover indicates a potential shift in market sentiment towards the upside. However, to validate this signal, the strategy checks if the moving average 3 on a higher time frame (eg. 4 hour) is in an upward trend. This additional filter ensures that the trade aligns with the prevailing trend on a broader time scale, increasing the probability of success.
Short Entry: Conversely, a short entry signal occurs when the moving average line 1 crosses below the moving average line 2. This crossover suggests a possible downturn in market momentum. However, for a short trade to be confirmed, the strategy verifies that the moving average 3 on the higher time frame is in a downward trend. This confirmation ensures that the trade is in harmony with the overarching market direction.
Exit from Long Position: The strategy triggers an exit signal from a long position when the moving average line 1 crosses below the moving average line 2. This crossover indicates a potential reversal in the market trend, prompting the trader to close their long position and take profits or minimize losses.
Exit from Short Position: Similarly, an exit signal from a short position occurs when the moving average line 1 crosses above the moving average line 2. This crossover suggests a potential shift in market sentiment towards the upside, prompting the trader to exit their short position and manage their risk accordingly.
Features of the script
This Triple MA Strategy is basically the HTF Trend Filter displayed 3 times on the chart. For more infomation on how the MA with dynamic smoothing is calculated I recommend reading the following script:
For risk management I included a simple script to opt for % of eauity or # of contracts of in the instrument. For explanation on how the risk management settings work I refer to my ealier published script:
The strategy is a simplified example for setting up an entry and exit logic based on multiple moving avarages. Hence the script is meant for educational purposes only.
Crypto MVRV ZScore - Strategy [PresentTrading]█ Introduction and How it is Different
The "Crypto Valuation Extremes: MVRV ZScore - Strategy " represents a cutting-edge approach to cryptocurrency trading, leveraging the Market Value to Realized Value (MVRV) Z-Score. This metric is pivotal for identifying overvalued or undervalued conditions in the crypto market, particularly Bitcoin. It assesses the current market valuation against the realized capitalization, providing insights that are not apparent through conventional analysis.
BTCUSD 6h Long/Short Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy leverages the Market Value to Realized Value (MVRV) Z-Score, specifically designed for cryptocurrencies, with a focus on Bitcoin. This metric is crucial for determining whether Bitcoin is currently undervalued or overvalued compared to its historical 'realized' price. Below is an in-depth explanation of the strategy's components and calculations.
🔶Conceptual Foundation
- Market Capitalization (MC): This represents the total dollar market value of Bitcoin's circulating supply. It is calculated as the current price of Bitcoin multiplied by the number of coins in circulation.
- Realized Capitalization (RC): Unlike MC, which values all coins at the current market price, RC is computed by valuing each coin at the price it was last moved or traded. Essentially, it is a summation of the value of all bitcoins, priced at the time they were last transacted.
- MVRV Ratio: This ratio is derived by dividing the Market Capitalization by the Realized Capitalization (The ratio of MC to RC (MVRV Ratio = MC / RC)). A ratio greater than 1 indicates that the current price is higher than the average price at which all bitcoins were purchased, suggesting potential overvaluation. Conversely, a ratio below 1 suggests undervaluation.
🔶 MVRV Z-Score Calculation
The Z-Score is a statistical measure that indicates the number of standard deviations an element is from the mean. For this strategy, the MVRV Z-Score is calculated as follows:
MVRV Z-Score = (MC - RC) / Standard Deviation of (MC - RC)
This formula quantifies Bitcoin's deviation from its 'normal' valuation range, offering insights into market sentiment and potential price reversals.
🔶 Spread Z-Score for Trading Signals
The strategy refines this approach by calculating a 'spread Z-Score', which adjusts the MVRV Z-Score over a specific period (default: 252 days). This is done to smooth out short-term market volatility and focus on longer-term valuation trends. The spread Z-Score is calculated as follows:
Spread Z-Score = (Market Z-Score - MVVR Ratio - SMA of Spread) / Standard Deviation of Spread
Where:
- SMA of Spread is the simple moving average of the spread over the specified period.
- Spread refers to the difference between the Market Z-Score and the MVRV Ratio.
🔶 Trading Signals
- Long Entry Condition: A long (buy) signal is generated when the spread Z-Score crosses above the long entry threshold, indicating that Bitcoin is potentially undervalued.
- Short Entry Condition: A short (sell) signal is triggered when the spread Z-Score falls below the short entry threshold, suggesting overvaluation.
These conditions are based on the premise that extreme deviations from the mean (as indicated by the Z-Score) are likely to revert to the mean over time, presenting opportunities for strategic entry and exit points.
█ Practical Application
Traders use these signals to make informed decisions about opening or closing positions in the Bitcoin market. By quantifying market valuation extremes, the strategy aims to capitalize on the cyclical nature of price movements, identifying high-probability entry and exit points based on historical valuation norms.
█ Trade Direction
A unique feature of this strategy is its configurable trade direction. Users can specify their preference for engaging in long positions, short positions, or both. This flexibility allows traders to tailor the strategy according to their risk tolerance, market outlook, or trading style, making it adaptable to various market conditions and trader objectives.
█ Usage
To implement this strategy, traders should first adjust the input parameters to align with their trading preferences and risk management practices. These parameters include the trade direction, Z-Score calculation period, and the thresholds for long and short entries. Once configured, the strategy automatically generates trading signals based on the calculated spread Z-Score, providing clear indications for potential entry and exit points.
It is advisable for traders to backtest the strategy under different market conditions to validate its effectiveness and adjust the settings as necessary. Continuous monitoring and adjustment are crucial, as market dynamics evolve over time.
█ Default Settings
- Trade Direction: Both (Allows for both long and short positions)
- Z-Score Calculation Period: 252 days (Approximately one trading year, capturing a comprehensive market cycle)
- Long Entry Threshold: 0.382 (Indicative of moderate undervaluation)
- Short Entry Threshold: -0.382 (Signifies moderate overvaluation)
These default settings are designed to balance sensitivity to market valuation extremes with a pragmatic approach to trade execution. They aim to filter out noise and focus on significant market movements, providing a solid foundation for both new and experienced traders looking to exploit the unique insights offered by the MVRV Z-Score in the cryptocurrency market.
Four WMA Strategy with TP and SLBasically I read a research paper on how they used different moving averages for long entries and short entries, and it kind of dawned on me that I always used the same one for long entry or exit, or even swing trading. So I smashed this together to see what would happen.
The strategy combines the use of four different WMAs for identifying trade entry points, along with a predefined take profit (TP) and stop loss (SL) for risk management. Here's a detailed description of its features and how it operates:
Main Features
1. **WMAs as the Core Indicator**:
- The strategy uses four WMAs with different lengths. Two WMAs (`longM1` and `longM2`) are used for long entry signals, and the other two (`shortM1` and `shortM2`) for short entry signals.
- The lengths of these WMAs are adjustable through input parameters.
2. **Trade Entry Conditions**:
- A long entry is signaled when the shorter WMA crosses under the longer WMA .
- Conversely, a short entry is signaled when the shorter WMA crosses under the longer WMA.
3. **Take Profit and Stop Loss**:
- The strategy includes a take profit and stop loss mechanism.
- The TP and SL levels are set as a percentage of the entry price, with the percentage values being adjustable through input parameters.
4. **Visual Representation**:
- The WMAs are plotted on the chart for visual aid, each with a distinct color for easy identification.
How It Works
- The strategy continuously monitors the crossing of WMAs to detect potential entry points for long and short positions.
- Upon detecting a long or short condition, it automatically enters a trade and sets the corresponding TP and SL levels based on the current price and the specified percentages.
- The strategy then actively manages the trade, exiting the position when either the TP or SL level is reached.
Drawbacks
- **Overreliance on WMAs**: The strategy heavily relies on WMAs for trade signals. While WMAs are useful for identifying trends, they might not always provide timely entry and exit signals.
- **Market Conditions**: It may not perform well in highly volatile or sideways markets where WMA crossovers could lead to false signals.
- **Risk Management**: The fixed percentage for TP and SL might not be suitable for all market conditions. Traders might need to adjust these values frequently based on market volatility and their risk tolerance.
Apparently I need to emphasize to use brains when using indicators and setting them up to achieve the results you can or want. Also risk of 12% is considered very high so I lowered the numbers to 5%, which tanked the profits, try adjusting them on your own. Check the properties settings for more info on comission and slippage.
Conclusion
The "Four WMA Strategy with TP and SL" is suitable for traders who prefer a moving average-based approach to trading, combined with a straightforward mechanism for risk management through take profit and stop loss. However, like all strategies, it should be used with an understanding of its limitations and ideally tested thoroughly in various market conditions before applying it to live trading.
FlexiMA x FlexiST - Strategy [presentTrading]█ Introduction and How it is Different
The FlexiMA x FlexiST Strategy blends two analytical methods - FlexiMA and FlexiST, which are opened in my early post.
- FlexiMA calculates deviations between an indicator source and a dynamic moving average, controlled by a starting factor and increment factor.
- FlexiST, on the other hand, leverages the SuperTrend model, adjusting the Average True Range (ATR) length for a comprehensive trend-following oscillator.
This synergy offers traders a more nuanced and multifaceted tool for market analysis.
BTC 6H L/S Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy combines two components: FlexiMA and FlexiST, each utilizing unique methodologies to analyze market trends.
🔶FlexiMA Component:
- Calculates deviations between an indicator source and moving averages of variable lengths.
- Moving average lengths are dynamically adjusted using a starting factor and increment factor.
- Deviations are normalized and analyzed to produce median and standard deviation values, forming the FlexiMA oscillator.
Length indicator (50)
🔶FlexiST Component:
- Uses SuperTrend indicators with varying ATR (Average True Range) lengths.
- Trends are identified based on the position of the indicator source relative to the SuperTrend bands.
- Deviations between the indicator source and SuperTrend values are calculated and normalized.
Starting Factor (5)
🔶Combined Strategy Logic:
- Entry Signals:
- Long Entry: Triggered when median values of both FlexiMA and FlexiST are positive.
- Short Entry: Triggered when median values of both FlexiMA and FlexiST are negative.
- Exit Signals:
- Long Exit: Triggered when median values of FlexiMA or FlexiST turn negative.
- Short Exit: Triggered when median values of FlexiMA or FlexiST turn positive.
This strategic blend of FlexiMA and FlexiST allows for a nuanced analysis of market trends, providing traders with signals based on a comprehensive view of market momentum and trend strength.
█ Trade Direction
The strategy is designed to cater to various trading preferences, offering "Long", "Short", and "Both" options. This flexibility allows traders to align the strategy with their specific market outlook, be it bullish, bearish, or a combination of both.
█ Usage
Traders can effectively utilize the FlexiMA x FlexiST Strategy by first selecting their desired trade direction. The strategy then generates entry signals when the conditions for either the FlexiMA or FlexiST are met, indicating potential entry points in the market. Conversely, exit signals are generated when the conditions for these indicators diverge, thus signaling a potential shift in market trends and suggesting a strategic exit point.
█ Default Settings
1. Indicator Source (HLC3): Provides a balanced and stable price source, reducing the impact of extreme market fluctuations.
2. Indicator Lengths (20 for FlexiMA, 10 for FlexiST): Longer FlexiMA length smooths out short-term fluctuations, while shorter FlexiST length allows for quicker response to market changes.
3. Starting Factors (1.0 for FlexiMA, 0.618 for FlexiST): Balanced start for FlexiMA and a harmonized approach for FlexiST, resonating with natural market cycles.
4. Increment Factors (1.0 for FlexiMA, 0.382 for FlexiST): FlexiMA captures a wide range of market behaviors, while FlexiST provides a gradual transition to capture finer trend shifts.
5. Normalization Methods ('None'): Uses raw deviations, suitable for markets where absolute price movements are more significant.
6. Trade Direction ('Both'): Allows strategy to consider both long and short opportunities, ideal for versatile market engagement.
*More details:
1. FlexiMA
2. FlexiST
