RSI Strategy With TP/SL - Lower TFThis Pine Script strategy integrates the Relative Strength Index (RSI) for trade signals with user-defined Take Profit (TP) and Stop Loss (SL) levels. It's designed for flexible application in different market conditions, offering long, short, or dual-direction trading.
Short Description
The strategy uses the RSI to identify overbought and oversold market conditions:
Buy signal: When RSI drops below the specified "Buy Level."
Sell signal: When RSI rises above the "Sell Level."
Additionally, it manages risk and profit targets with:
Take Profit (TP): Exits trades when the price reaches a percentage gain.
Stop Loss (SL): Exits trades to limit losses if the price falls by a certain percentage.
The strategy is versatile and includes options for visualizing performance, monthly profit/loss data, and detailed trade metrics.
How to Use
Set Parameters:
RSI Period: Default is 14. Adjust based on your analysis.
RSI Buy/Sell Levels:
Buy Level: Default is 40. Consider higher levels for conservative entries.
Sell Level: Default is 60. Lower this for earlier exits.
Take Profit (%): Set your profit target (default: 5%).
Stop Loss (%): Set your risk tolerance (default: 2%).
Trade Direction: Choose "Long Only," "Short Only," or "Both."
Interpret Signals:
Buy signals appear when RSI crosses below the buy threshold.
Sell signals appear when RSI crosses above the sell threshold.
Risk Management:
The strategy dynamically calculates TP and SL levels for each trade.
TP/SL is applied using the percentage input based on the entry price.
Monitor Performance:
Review trade statistics in the "Strategy Tester."
Use the monthly performance table to track P/L across months.
Customize Alerts:
Alerts for buy, sell, TP, and SL events can be used to automate notifications.
Key Features
Configurable RSI Settings: Adaptable to various market conditions.
Risk Management: Built-in TP and SL management.
Customizable Trade Direction: Tailored for long-only, short-only, or both directions.
Monthly P/L Table: Visualizes performance trends over time.
Alerts: Notifies when critical trade events occur.
Please do your own research before ase this to your real trading.
عملة رقمية
Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
Rsi Long-Term Strategy [15min]Hello, I would like to present to you The "RSI Long-Term Strategy" for 15min tf
The "RSI Long-Term Strategy " is designed for traders who prefer a combination of momentum and trend-following techniques. The strategy focuses on entering long positions during significant market corrections within an overall uptrend, confirmed by both RSI and volume. The use of long-term SMAs ensures that trades are made in line with the broader market trend. The stop-loss feature provides risk management by limiting losses on trades that do not perform as expected. This strategy is particularly well-suited for longer-term traders who monitor 15-minute charts but look for substantial trend reversals or continuations.
Indicators and Parameters:
Relative Strength Index (RSI):
- The RSI is calculated using a 10-period length. It measures the magnitude of recent price changes to evaluate overbought or oversold conditions. The script defines oversold conditions when the RSI is at or below 30 and overbought conditions when the RSI is at or above 70.
Volume Condition:
-The strategy incorporates a volume condition where the current volume must be greater than 2.5 times the 20-period moving average of volume. This is used to confirm the strength of the price movement.
Simple Moving Averages (SMA):
- The strategy uses two SMAs: SMA1 with a length of 250 periods and SMA2 with a length of 500 periods. These SMAs help identify long-term trends and generate signals based on their crossover.
Strategy Logic:
Entry Logic:
A long position is initiated when all the following conditions are met:
The RSI indicates an oversold condition (RSI ≤ 30).
SMA1 is above SMA2, indicating an uptrend.
The volume condition is satisfied, confirming the strength of the signal.
Exit Logic:
The strategy closes the long position when SMA1 crosses under SMA2, signaling a potential end of the uptrend (a "Death Cross").
Stop-Loss:
A stop-loss is set at 5% below the entry price to manage risk and limit potential losses.
Buy and sell signals are highlighted with circles below or above bars:
Green Circle : Buy signal when RSI is oversold, SMA1 > SMA2, and the volume condition is met.
Red Circle : Sell signal when RSI is overbought, SMA1 < SMA2, and the volume condition is met.
Black Cross: "Death Cross" when SMA1 crosses under SMA2, indicating a potential bearish signal.
to determine the level of stop loss and target point I used a piece of code by RafaelZioni, here is the script from which a piece of code was taken
I hope the strategy will be helpful, as always, best regards and safe trades
;)
Project Monday Strategy [AlgoAI System]Overview
Project Monday is a sophisticated trading strategy designed for active market participants. This strategy can be used alongside other forms of technical analysis, providing traders with additional tools to enhance their market insights. While it offers a flexible approach for identifying and exploiting market inefficiencies, Project Monday does not fit every market condition and requires adjustments. Its core principles include technical analysis and risk management, all aimed at making informed trading decisions and managing risk effectively.
Features
Project Monday Strategy works in any market and includes many features:
Efficient Trading Presets: Offers ready-to-use presets that allow traders to start efficient trading with one click.
Confirmation Signals: Provides signals to help traders validate trends, emphasizing informed decision-making (not to be followed blindly).
Reversal Signals: Identifies signals to alert traders to potential reversals, encouraging careful analysis (not to be followed blindly).
Adaptability: Can be adjusted to fit different market conditions, ensuring ongoing effectiveness.
Multi-Market Application: Suitable for use across various asset classes including stocks, forex, commodities, and cryptocurrencies.
Integration: Can be used alongside other technical analysis tools for enhanced decision-making.
Position Sizing: Allows traders to determine optimal trade size using backtesting and trading performance dashboard.
Backtesting: Supports historical testing to refine and validate the strategy.
Continuous Monitoring: Includes features for ongoing performance evaluation and strategy adjustments.
Unique Project Monday Strategy Features on TradingView:
Adaptive Position Sizing: Dynamically adjusts the size of each position based on market conditions and predefined risk management criteria, ensuring optimal trade sizing and risk exposure.
Preliminary Position Opening: Allows traders to enter a position in anticipation of a signal confirmation, enabling them to capture early market movements and improve entry points.
Preliminary Position Closing: Enables traders to exit a position before a signal reversal, helping to lock in profits and minimize potential losses during volatile market conditions.
Adjusting Strategy Parameters:
Price Band Inputs:
Project Monday Strategy uses a set of configurable inputs to tailor its behavior according to the trader's preferences. The following are the key inputs for the price band calculations. Signals are not generated when the price remains within these bands.
“Length of Calculation” determines how many historical data points are used in the trend calculation. A shorter “Length of Calculation” will make the Price Band more responsive to recent price changes but may also increase the noise and the likelihood of false signals. A longer “Length of Calculation” will make the Price Band smoother, with less noise, but may cause more lag in reacting to price changes.
“Offset” determines the position of the Gaussian filter, which is used to weight the data points in the trend calculation. The offset is expressed as a fraction of the “Length of Calculation”, with a value between 0 and 1. A higher “Offset” will shift the Gaussian filter closer to the more recent data points, making the Price Band more responsive to recent price changes but potentially increasing noise. A lower “Offset” will shift the Gaussian filter closer to the centre of the window, resulting in a smoother Price Band but potentially introducing more lag.
“Sigma” refers to the standard deviation used in the Gaussian distribution function. This parameter determines the smoothness of the curve and the degree to which data points close to the centre of the “Length of Calculation” are weighted more heavily than those further away. A smaller “Sigma” will result in a narrower Gaussian filter, leading to a more responsive Price Band but with a higher chance of noise and false signals. A larger “Sigma” will result in a wider Gaussian filter, creating a smoother Price Band but with more lag.
Adjust the “Source” inputs to specify which type of price data should be used for strategy calculations and signal generation.
“Width of Band” input determines the multiplier for the band width. A higher value of “Width of Band” makes the price band wider, which generates fewer signals due to the lower probability of the price moving outside the band. Conversely, a lower multiplier makes the band narrower, generating more signals but also increasing the likelihood of false signals.
Direction input:
The Project Monday strategy includes an input to specify the direction of trades, allowing traders to control whether the strategy should consider long positions, short positions, or both. The following input parameter is used for this purpose:
This input parameter allows traders to define the type of positions the strategy will take. It has three options:
Only Long: The strategy will generate signals exclusively for buying or closing short positions, focusing on potential uptrends.
Only Short: The strategy will generate signals exclusively for selling or closing long positions, focusing on potential downtrends.
Both: The strategy will generate signals for both buying (long positions) and selling (short positions), allowing for a more comprehensive trading approach that captures opportunities in both rising and falling markets.
Signals Filter:
The Project Monday strategy includes inputs to filter signals based on higher timeframes and the length of the data used for filtering. These inputs help traders refine the strategy's performance by considering broader market trends and smoothing out short-term fluctuations.
Filter Timeframe input specifies the timeframe used for filtering signals. By choosing a higher timeframe, traders can filter out noise from shorter timeframes and focus on more significant trends. The options range from intraday minutes (e.g., 1, 5, 15 minutes) to daily (1D, 2D, etc.), weekly (1W, 2W, etc.), and monthly (1M) timeframes. This allows traders to align their strategy with their preferred trading horizon and market perspective.
Filter Length input defines the number of data points used for filtering signals on the selected timeframe. A longer filter length will smooth out the data more, helping to identify sustained trends and reduce the impact of short-term fluctuations. Conversely, a shorter filter length will make the filter more responsive to recent price changes, potentially generating more signals but also increasing sensitivity to market noise.
Adaptive Position Size:
The Project Monday strategy incorporates inputs for unique feature Adaptive Position Sizing (APS), which dynamically adjusts the size of trades based on market conditions and specified parameters. This feature helps optimize risk management and trading performance.
Enable Adaptive Position Size: Users can check or uncheck this box to enable or disable the Adaptive Position Size feature. When checked, the strategy dynamically adjusts position sizes based on the defined parameters. This allows traders to scale their positions according to market volatility and other factors, enhancing risk management and potentially improving returns. When unchecked, the strategy will not adjust position sizes adaptively, and positions will remain fixed as per other settings.
“Timeframe for Adaptive Position Size “input specifies the timeframe used for calculating the position size. Options range from intraday minutes (e.g., 30, 60 minutes) to daily (1D, 3D), weekly (1W), and monthly (1M) timeframes. Selecting an appropriate timeframe helps align position sizing calculations with the trader’s overall strategy and market perspective, ensuring that position sizes are adjusted based on relevant market data.
“APS Length” input defines the number of data points used to calculate the adaptive position size. A longer APS length will result in higher position sizes. Conversely, a shorter APS length will result in smaller position sizes.
Anticipatory Trading:
Project Monday Strategy includes inputs for unique feature Anticipatory Trading, allowing traders to open and close positions preliminarily based on certain conditions. This feature aims to provide an edge by taking action before traditional signals confirm.
Enable Preliminary Position Opening: Users can check or uncheck this box to enable or disable Preliminary Position Opening. When enabled, the strategy will open positions based on preliminary conditions before the standard signals are confirmed. This can help traders capitalize on early trend movements and potentially gain a better entry point.
Enable Preliminary Position Closing: Users can check or uncheck this box to enable or disable Preliminary Position Closing. When enabled, the strategy will close positions based on preliminary conditions before the standard exit signals are confirmed. This can help traders lock in profits or limit losses by exiting positions at the early signs of trend reversals.
“Position Size in %” input specifies the position size as a percentage of the trading capital. By setting this value, traders can control the amount of capital allocated to each trade. For example, a risk value of 40% means that 40% of the available trading capital will be used for each anticipatory trade. This helps in managing risk and ensuring that the position size aligns with the trader's risk tolerance and overall strategy.
Usage:
Signal Generation
Long signal indicates a potential uptrend, suggesting either buying or closing a short position. Short signal indicates a potential downtrend, suggesting either selling or closing a long position. Signals are generated on your chart when the price moves beyond a calculated price band based on the current trend.
Signal Filtering
The strategy includes a filtering mechanism based on the current or another timeframe. Filtering works best with higher timeframes. This component calculates the trend on a higher timeframe and predicts the trend, ensuring trades on the current timeframe are only opened if they align with the higher timeframe trend. Setting the right filter timeframe is crucial for obtaining the best signals.
Position Direction
Users can choose the direction of positions to open via the settings box. Options include only long positions, only short positions, or both.
Adaptive Position Size (APS)
Users can enable the Adaptive Position Size feature to adjust position sizes based on trend strength. The strategy evaluates the strength of the current trend based on a higher timeframe. The stronger the trend, the larger the position size for opening a position.
Anticipatory Trading
Users can activate this unique feature to enhance trading decisions. The strategy assesses the likelihood of receiving a main signal. If the opportunity appears strong, it opens a partial position, as specified in the settings box. As the probability of the signal strengthens, the strategy gradually increases the position size.
Exit Strategy
The strategy exits positions based on receiving a reverse signal. Positions opened through “Anticipatory trading” are exited incrementally as each preliminary signal reverses.
By following these steps, traders can implement the strategy to navigate various market scenarios, manage risk, and adjust trading performance over time. Adjusting parameters and monitoring signals diligently are key to adapting the strategy to individual trading styles and market conditions.
You will get
By purchasing the Project Monday strategy, you not only gain access to a cutting-edge system but also receive ready-to-use presets designed to help you start trading immediately and achieve optimal results. Additionally, you benefit from comprehensive support and the option to request custom presets for your desired financial instruments through our dedicated support team, ensuring you have the tools and assistance needed for successful trading.
Risk Disclaimer
This information is not a personalized investment recommendation, and the financial instruments or transactions mentioned in it may not be appropriate for your financial situation, investment objective(s), risk tolerance, and/or expected return. AlgoAI shall not be liable for any losses incurred in the event of transactions or investments in financial instruments mentioned in this information.
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
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!
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
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
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█ 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.
BitBell - EMA PullBack RSI EXO
🔵 Introduction
Version 1.1
This is a Pine 5 trend following strategy. It has a four strategy with several alerts and signals. The design intent is to produce a commercial grade signal generator that can be adapted to any symbol in cryptocurrency and only 1H Chart. Ideally, the script is reliable enough to be the basis of an automated trading system web-hooked to a server with API access to crypto brokerages. The strategy can be run in three different modes: long, short and bidirectional.
As a trend following strategy, the behavior of the script is to buy on strength and sell on weakness. As such the trade orders maintain its directional bias according to price pressure. What you will see on the chart is long positions on the left side of the mountain and short on the right. Long and short positions are not intermingled as long as there exists a detectable trend. This is extremely beneficial feature in long running bull or bear markets. The script uses multiple setups to avoid the situation where you got in on the trend, took a small profit but couldn’t get back in because the logic is waiting for a pullback or some other intricate condition.
Deep draw-downs are a characteristic of trend following systems and this system is no different. However, this script makes use of the TradingView pyramid feature with three NPUs to find better place and even you can change drop percentage in settings for another trigger, accessible from the properties tab.
When trend market break it will stop the trade and usually it takes 2-4 percent loss but don't worry it has prefect money management and you can use it for Futures market and even Spot market.
🔵 Design
This script uses twelve indicators on two time frames. The chart (primary) interval and one higher time frame which is based on the primary. The higher time frame identifies the trend for which the primary will trade. I’ve tried to keep the higher time frame around five times greater than the primary. The original trading algorithms are a port from a much larger program on another trading platform. I’ve converted some of the statistical functions to use standard indicators available on TradingView. The setups make heavy use of the Hull Moving Average in conjunction with EMAs that form the Bill Williams Alligator as described in his book “New Trading Dimensions” Chapter 3. Lag between the Hull and the EMAs form the basis of the entry and exit points. The alligator itself is used to identify the trend main body.
The entire script is around 740 lines of Pine code which is the maximum incidental size given the TradingView limits: local scopes, run-time duration and compile time. I’ve been working on this script for over a year and have tested it on various instruments stock crypto. It performs well on higher liquidity markets that have at least a year of historical data. Though it can be configured to work on any interval between 15 minutes and 4 hour, trend trading is generally a longer term paradigm. For day trading the 10 to 15 minute interval will allow you to catch momentum breakouts. For intraweek trades 30 minutes to 1 hour should give you a trade every other a day.
Inputs to the script use cone centric measurements in effort to avoid exposing adjustments to the various internal indicators. The goal was to keep the inputs relevant to the actual trade entry and exit locations as opposed to a series of MA input values and the like. As a result the strategy exposes over 12 inputs grouped into long or short sections. Inputs are available for the usual minimum profit and stop-loss as well as trade, modes, presets, reports and lots of calibrations. The inputs are numerous, I’m aware. Unfortunately, at this time, TradingView does not offer any other method to get data in the script. The usual initialization files such as cnf, cfg, ini, json and xml files are currently unsupported.
Example configurations for various instruments along with a detailed PDF user manual is available.
it has no repaint i guaranty this, and you can have 10 days free with comment and check it by yourself
One issue that comes up when comparing the strategy with the study is that the strategy trades show on the chart one bar later than the study. This problem is due to the fact that “strategy.entry()” and “strategy_close()” do not execute on the same bar called. The study, on the other hand, has no such limitation since there are no position routines. However, alerts that are subsequently fired off when triggered in the study are dispatched from the TradingView servers one bar later from the study plot. Therefore the alert you actually receive on your cell phone matches the strategy plot but is one bar later than the study plot.
Please be aware that the data source matters. Cryptocurrency has no central tick repository so each exchange supplies TradingView its feed. Even though it is the same symbol the quality of the data and subsequently the bars that are supplied to the chart varies with the exchange. This script will absolutely produce different results on different data feeds of the same symbol. Be sure to backtest this script on the same data you intend to receive alerts for. Any example settings I share with you will always have the exchange name used to generate the test results.
🟡 Usage
It sends long and short signals with pyramid orders of up to 3, meaning that the strategy can trigger up to 3 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (Long and LongX). Let’s describe the specific features of this strategy.
🔵 If Findes Supports And Ressitances And Trend Lines As Best As It Can, And You Can See:
🟢 Frist Simple Long Condition = It Look At The Trend Wait For RSI Cross 30 Number Then Ckeck Risk To Reward, check something else such as divergence:
🟢 Another Long Example:
🔴 Frist Simple Short Condition = It Look At The Trend Wait For RSI Cross 70 Number Then Ckeck Risk To Reward, check something else such as divergence:
🔴 Another Short Example:
The following steps provide a very brief set of instructions that will get you started but will most certainly not produce the best backtest. A trading system that you are willing to risk your hard earned capital will require a well crafted configuration that involves time, expertise and clearly defined goals. As previously mentioned, I have several example configs that I use for my own trading that I can share with you along with a PDF which describes each input in detail. To get hands on experience in setting up your own symbol from scratch please follow the steps below.
The input dialog box contains over 12 inputs, There are four options must to be configured: Choose Target, side, Choose Settings, Money Management,and settings that apply to both. The following steps address these four main options only.
Money Management System For Leverage 10:
Bot Finds Last Lower Low And Calculate Distance From Entry Price, Then Cross It To Initial Capitan And Cross Leverage =>
Position_Size = (((1.64) * (initial Capital)) * (leverage))
And Check Dominances Too For Getting Best Money Management Result
🔵 Settings
* Side, You Can Set Long Or Short Or Both.
* Choose Target, You Can Set One Target Or All Targets.
* Money Management, You Can ON Or OFF It, With OFF You Can USE It For SPOT Trades.
* Choose Settings, In This Field You Can Set Mathematical Optimization, Ddepends On Which Pair You USE.
* Clear With Daily PullBack?, With This Check Box You Can Clear Signals With Daily PullBack.
* Long X, You Can Set Long Leverage.
* Short X, You Can Set Short Leverage.
* Second Order X, You Can Set Pyramiding Leverage.
* Target Long, You Can Set Percent For Long Target.
* Target Short, You Can Set Percent For Short Target.
* Short Martin Percent, You Can Set Short Martingale Percent.
* Long Martin Percent, You Can Set Long Martingale Percent.
🟡 Pyraming 3
🟡 Commission Is 0.065 %
🟡 Slippage Is 10 ticks
🔴Only Use For 1 Hour Chart
🔴 CONCLUSION
We believe that success lies in the association of the user with the indicator, opposed to many traders who have the perspective that the indicator itself can make them become profitable. The reality is much more complicated than that.
The aim is to provide an indicator comprehensive, customizable, and intuitive enough that any trader can be led to understand this truth and develop an actionable perspective of technical indicators as support tools for decision making.
🔴 RISK DISCLAIMER
Trading is risky & most day traders lose money. All content, tools, scripts, articles, & education provided by BitBell are purely for informational & educational purposes only. Past performance does not guarantee future results.
Cyatophilum Bands PresetsThis is a pre-configured strategy for swing trading Bitcoin on the 2 hours chart, Ethereum on the 4 hours, and BNB on the 2 hours. (More presets can be added later on)
Built upon my generic indicator "Cyatophilum Bands D.E.", this indicator removes the struggle of having to copy all the settings, instead, a single dropdown input lets you choose the preset.
More info about the complete strategy here:
The strategy has been backtested over 5 years of historical data and forward tested for +4 months (since january 2023) with the goal to beat buy and hold returns .
The indicator shows real time strategy results and has custom alerts for BUY and SELL signals which can be used to automate the strategy.
When creating your alert, first set your alert messages in the indicator settings. Then, select the indicator and create the alert using "alert() function calls only".
A warning will appear on the chart if the preset and chart configuration is incorrect.
Plots like bands and trailing lines are disabled by default to improve performance but can be turned on in the style tab.
BNBUSDT 2H
A combination of deviation and ATR bands based on Donchian channels.
ETHUSDT 4H
A combination of deviation and ATR bands based on SMA and an ATR trailing stop.
BTCUSDT 2H
Based on Donchian channels breakout type with a tight 2% stop loss, and a 3% take profit that gets disabled when price is trending up to let the trailing stop do its job.
Disclaimer: Backtest results are not representative of future results.
Shorting when Bollinger Band Above Price with RSI (by Coinrule)The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
The relative strength index ( RSI ) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI can do more than point to overbought and oversold securities. It can also indicate securities primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
The short order is placed on assets that present strong momentum when it's more likely that it is about to reverse. The rule strategy places and closes the order when the following conditions are met:
ENTRY
The closing price is greater than the upper standard deviation of the Bollinger Bands
The RSI is less than 70.
EXIT
The trade is closed when the RSI is less than 70
The lower standard deviation of the Bollinger Band is less than the closing price.
This strategy was backtested from the beginning of 2022 to capture how this strategy would perform in a bear market.
The strategy assumes each order to trade 70% of the available capital to make the results more realistic. A trading fee of 0.1% is taken into account. The fee is aligned to the base fee applied on Binance, which is the largest cryptocurrency exchange by volume.
Token Metrics IndicatorThe Token Metrics Combined Indicator v2 is a comprehensive technical analysis tool designed to output Long/Short signals for crypto assets on TradingView. It combines multiple indicators, including Token Metrics Clouds, Token Metrics Trend Lines , Token Metrics Channels, and signals, to give a comprehensive outlook on the market trend and potential entry/exit points.
Users can backtest the signals to understand the strategy's historical performance, learn how to use it, identify its pros and cons, and determine the market conditions it best suits. It is important to note that the backtesting performance does not indicate future results.
The methods for calculating fixed stop-losses vary depending on the trading pattern. A fixed stop-loss is used for long-term trading, while a trading stop-loss is used for high-frequency trading. This provides flexible investment risk management, allowing you to assign different stop-loss percentages to different trading strategies.
The Length input allows users to control the indicator’s sensitivity, with a default value of 20 bars for long-term trading and 9 bars for high-frequency trading. The Adjustment Factor input has a default value of 0.1 and can be adjusted to adapt to changing levels of volatility . The Stop-loss input allows users to control their risk tolerance, with a default value of 8% for long-term trading and 2% for high-frequency trading.
Token Metrics Clouds incorporates a bullish / bearish trend indicator, which uses two adaptive moving averages that adapt to volatility , reducing false trend signals during range-bound environments and providing a more accurate representation of market trends.
The Token Metrics Trendline is a long-term indicator that uses an adaptive moving average to identify long-term trends. This can also be used for long-term resistance and support levels, providing a comprehensive overview of the current market situation for both long-term and high-frequency traders.
The Token Metrics Signals indicator provides long, short, and close signals, indicating when to enter and exit long or short positions based on the TM trend-following strategy.
The Token Metrics Channels indicator is a top/bottom indicator that adjusts to current levels of volatility . This uses adaptive Donchian channels to determine the previous short-term swing high and low, providing insight into where short-term resistance or support might be forming and where breakouts can occur. The look-back periods change according to the strategy time frame, offering a flexible and dynamic approach to market analysis.
Long-term trading is a trend-following strategy best suited for daily and weekly timeframes. This strategy works well in trending markets but may produce false signals in choppy or range-bound markets.
High-frequency trading is a mean-reverting strategy best suited for 15-minute, 30-minute, and 1-hour timeframes. This strategy performs well in choppy or range-bound markets but may not be effective in strong trending markets.
Ichimoku Cloud and ADX with Trailing Stop Loss (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
DMI is simple to interpret. When +DI > - DI, it means the price is trending up. On the other hand, when -DI > +DI, the trend is weak or moving on the downside. The ADX does not give an indication of the direction but about the strength of the trend.
Typically values of ADX above 25 mean that the trend is steeply moving up or down, based on the -DI and +DI positioning. This script aims to capture swings in the DMI, and thus, in the trend of the asset, using a contrarian approach.
Trading on high values of ADX, the strategy tries to spot extremely oversold and overbought conditions. Values of ADX above 45 may suggest that the trend has overextended and is maybe about to reverse.
This strategy combines the Ichimoku Cloud with the ADX indicator to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
MACD line crosses over the signal line
-DI is greater than +DI
ADX is greater than 45
Close Position:
3% increase trailing
3% decrease trailing
The script is backtested from December 2022 and provides good returns.
A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
RSI and MA with Trailing Stop Loss and Take Profit (by Coinrule)The relative strength index is a momentum indicator used in technical analysis. It measures the speed and magnitude of a coin's recent price changes to evaluate overvalued or undervalued conditions in the price of that coin. The RSI is displayed as an oscillator (a line graph essentially) on a scale of zero to 100. When the RSI reaches oversold levels, it can provide a signal to go long. When the RSI reaches overbought levels, it can mark a good exit point or alternatively, an entry for a short position. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
A moving average (MA) calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. Essentially it is used to help smooth out price data by creating a constantly updated average price.
The Strategy enters and closes trades when the following conditions are met:
Entry Conditions:
RSI is greater than 50
MA9 is greater than MA50
RSI increases by 5
Exit Conditions:
Price increases by 1% trailing
Price decreases by 2% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market. The strategy provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
MACD + RSI + ADX Strategy (ChatGPT-powered) by TradeSmartThis is a trading strategy made by TradeSmart, using the recommendations given by ChatGPT . As an experiment, we asked ChatGPT on which indicators are the most popular for trading. We used all of the recommendations given, and added more. We ended up with a strategy that performs surprisingly well on many crypto and forex assets. See below for exact details on what logic was implemented and how you can change the parameters of the strategy.
The strategy is a Christmas special , this is how we would like to thank the support of our followers.
The strategy has performed well on Forex, tested on 43 1-hour pairs and turned a profit in 21 cases. Also it has been tested on 51 crypto pairs using the 1-hour timeframe, and turned a profit in 45 cases with a Profit Factor over 1.4 in the top-5 cases. Tests were conducted without commission or slippage, unlike the presented result which uses 0.01% commission and 5 tick slippage.
Some of the top performers were:
SNXUSDT
SOLUSDT
CAKEUSDT
LINKUSDT
EGLDUSDT
GBPJPY
TRYJPY
USDJPY
The strategy was implemented using the following logic:
Entry strategy:
Long entry:
Price should be above the Simple Moving Average (SMA)
There should be a cross up on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be above the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Short entry:
Price should be under the Simple Moving Average (SMA)
There should be a cross down on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be below the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Exit strategy:
Stop Loss will be placed based on ATR value (with 1.5 Risk)
Take profit level will be placed with a 2.5 Risk/Reward Ratio
Open positions will be closed early based on the Squeeze Momentum (Long: change to red, Short: change to green)
NOTE! : The position sizes used in the example is with 'Risk Percentage (current)', according which the position size will be determined such
that the potential loss is equal to % of the current available capital. This means that in most of the cases, the positions are calculated using leverage.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Allow early TP/SL plots: false by default, Checking this option will result in the TP and SL lines to be plotted also on the signal candle rather than just the entry candle. Consider this only when manual trading, since backtest entries does not happen on the signal candle.
Entry Signal:
Fast Length: 12 by default
Slow Length: 26 by default
Source: hlcc4 by default
Signal Smoothing: 9 by default
Oscillator MA Type: EMA by default
Signal Line MA Type: EMA by default
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 14 by default
ATR Smoothing (of the SL): EMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier. Please select only one active stop loss. Default value (if nothing or multiple stop losses are selected) is the 'ATR Based Stop Loss'.
Candle Lookback (of the SL): 10 by default
Base Risk Multiplier: 1.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 2.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exit based on Squeeze Momentum: true by default, a Long position will be closed when Squeeze Momentum turns red inside an open position and a Short position will be closed when Squeeze Momentum turns green inside an open position
BB Length: 20 by default
BB Mult Factor: 1.0 by default
KC Length: 20 by default
KC Mult Factor: 1.5 by default
Use True Range (KC): Yes by default
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 1.5 by default
Order Type: Risk Percentage (current) by default, allows adjustment on how the position size is calculated: Cash: only the set cash ammount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade Risk Percentage (current): position size will be determined such that the potential loss is equal to % of the current available capital Risk Percentage (initial): position size will be determined such that the potential loss is equal to % of the initial capital
Trend Filter:
Use long trend filter: true by default, only enter long if price is above Long MA
Show long trend filter: true by default, plot the selected MA on the chart
MA Type (Long): SMA by default
MA Length (Long): 100 by default
MA Source (Long): close by default
Use short trend filter: true by default, only enter long if price is under Short MA
Show short trend filter: false by default, plot the selected MA on the chart
MA Type (Short): SMA by default
MA Length (Short): 100 by default
MA Source (Short): close by default
Simple RSI Limiter:
Limit using Simple RSI: true by default, if set to 'Normal', only enter long when Simple RSI is lower then Long Boundary, and only enter short when Simple RSI is higher then Short Boundary. If set to 'Reverse', only enter long when Simple RSI is higher then Long Boundary, and only enter short when Simple RSI is lower then Short Boundary.
Simple RSI Limiter Type:
RSI Length: 14 by default
RSI Source: hl2 by default
Simple RSI Long Boundary: 50 by default
Simple RSI Short Boundary: 50 by default
ADX Limiter:
Use ADX Limiter: true by default, only enter into any position (long/short) if ADX value is higher than the Low Boundary and lower than the High Boundary.
ADX Length: 5 by default
DI Length: 5 by default
High Boundary: 50 by default
Low Boundary: 20 by default
Use MA based calculation: Yes by default, if 'Yes', only enter into position (long/short) if ADX value is higher than MA (ADX as source).
MA Type: REMA by default
MA Length: 5 by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: EMA by default
MA Length: 10 by default
Session Limiter:
Show session plots: false by default, show crypto market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Date Range:
Limit Between Dates: false by default
Start Date: Jul 01 2021 00:00:00 by default
End Date: Dec 31 2022 00:00:00 by default
Trading Time:
Limit Trading Time: false by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 1234567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 1234567 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 0930-1600 by default, hours between which the trades can happen. The time is always in the exchange's timezone
Fine-tuning is highly recommended when using other asset/timeframe combinations.
VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on TradingView by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
Time Based Crypto DayTrade StrategyThis is a time based strategy, designed to enter and exit within the same day of the week, using different hours for entry and exit.
The script is long only direction, and it has no risk management inside, so use it with caution.
At the same time you can also calculate each individual hour return within a certain day, and make your own idea about the best moments to be enter.
In order to filter a bit from the bad trades, I have applied an ATR filter, to check if that volatility is rising in order to help eliminate some of the bad trades when there is no volatility around.
For this example, on BTC, it seems that for the last years, on tuesday and thursday, enterring at the beginning of the daily candle, 01:00hours and exit at 00:00 hours, seems to give positive results giving the idea that can be converted in some sort of edge into our favor.
However dont take this entirelly for granted and conduct your own searches
Fast EMA above Slow EMA with MACD (by Coinrule)An 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 exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the coin when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bullish
EMA8 is greater than EMA26
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include AXSUSDT on the 5-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly.
Additionally, the trailing stop loss and take profit conditions can also be changed to match your needs.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Crypto Tipster v2---------------------
Crypto Tipster v2
Hello again! We're back with a drastically improved Crypto Tipster v2 Indicator using over a dozen all new algorithms based around Technical Analysis, Price Action, Momentum Swings and Reversal Detection.
We've taken our time with version 2 of Crypto Tipster, putting all our best practices to work and ensuring it performs superbly across numerous crypto markets and timeframes - we have focused our efforts towards the larger timeframes, 12H, 1D, 2D for example as we believe these to be the most consistent and predictable, and therefore the most profitable.
Trading on longer timeframes also reduces the overal cost of trading fee's as you'll be placing fewer trades over any given time period, whilst catching bigger swings and therefore earning a higher percentage per winning trade. Due to these bigger price swings you can de-leverage your trades too, making them inherintly safer and more controlled.
The final benefit to placing trades on longer timeframes is that you will not be tied down to your PC or laptop for hours on end waiting for a perfect entry or exit point, which increases the odds of placing bad/panic trades or even placing trades due to boredom! If you trade with Crypto Tipster v2 on a 1D timeframe, you will only ever have work to do once per day, at bar close; this is when trades are placed or exited, or stop losses/take profits are updated to new levels - easy!
Crypto Tipster v2 can help consistently catch tops and bottoms of trending markets whilst avoiding placing trades through choppy or ranging areas, this helps to not only maximise profits (what we're all after!) but also to minimise losses (equally important). We've tirelessly tested Crypto Tipster using literally thousands of variables across dozens of built-in algorithms over hundreds of trading pairs - lots of data to process!
The outcome is rather stunning and well worth checking out - we're rather proud of what we've achieved here, and we're pretty sure you're going to love it too!
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What's Included
- Chart Settings
The first section you'll come across, Chart Settings.
Here you'll find a few options regarding how your chosen market chart will look within TradingView and how Crypto Tipster will interact with this chart.
One of the most important Tick boxes is first on the list - "Show Backtest Results". This will change Crypto Tipster from displaying simple but easy-to-follow "Buy/Sell" labels into Strategy mode in which you can set up more complicated Stop Loss / Take profit settings as well as setting up Alerts for auto trading and other more complex functions (see How It Works for more info!
We've also included a "Trend Strength Bar Color" tick box which changes the color of the chart bars based on how strong Crypto Tipster is perceiving the current trend and in which direction.
- Trend Settings
"Trading Frequency" represents how often Crypto Tipster will be looking for a new trend / change in trend direction, and therefore how often it will be placing trades. By default this is set to "Normal" but can be changed to "Rapid" using the drop down menu.
"Entry Trend Strength" also determines how frequently trades are placed by selecting the strength of trend required before a trade is placed. The scale ranges from "1-5", with 1 being a low trend strength required, 5 being a very strong trend strength required.
Within the Trend Settings section you'll also find an "Avg Trend Strength over Bars" option. This allows you to average (mean) the current trend strength over a pre-determined amount (1-5) of previous chart bars - thus providing a potentially more consistent signal.
- Trade Settings
Trade Settings help Crypto Tipster determine what type of trades you're looking to place.
The overall "Trade Direction" will decide to either target only Long trades, only Short trades, or Both (default).
"Consecutive Trades in Same Direction" allows for pyramiding - whereby you can specify to allow for multiple trades of the same direction. Set to "1" as default allows for no extra pyramiding, max setting of "10".
- Trade Protection
Currently consisting of two functions, our Trade Protection section can help to achieve both the removal of false signals (whipsaws), and the extension of good trades without confusion during minor retracements.
"Chop Removal" can help to remove some whipsaw trades during ranging market conditions, therefore improving overal profitability by only targeting stronger trends. You have an option to choose from either "Weak" or "Strong" Chop Removal.
"Protection Filter" uses current trading criteria as defined by you, and uses it to check against a higher time frame than you're currently viewing. This can help to eliminate some bad trades at the expense of a potential lag on good trades.
- Stop Loss / Take Profit
Stop Losses should be a crucial aspect of everyone's trading system. They help prevent any trade from going too far in the wrong direction and limit losses.
Our "Stop Loss (%)" is quick and easy to set up, simply set the percentage offset from the entry price of trades and a fixed Stop Loss will be in place on all trades.
"Take Profit (%)" works in the same way as the Stop Loss mentioned above - simply set the percentage you'd like to exit a profitable trade at.
The "Trailing Stop (%)" is a little more complicated in that it will follow the trend of the trade a certain percentage away from the current market price - this is great for keeping yourself in a trade for as long as the trade is moving in the right direction.
- Extra Tools & Indicators
This is the section of Crypto Tipster that enables you to add some chart visuals to assist you with your preferred trading style.
"Potential Pivot Points" are not the same as actual pivot points - Potential pivot points will paint on the chart at bar close, giving you an immediate alert to potential tops/bottoms of market trends. You can choose to display only the strongest potential points, or include some of the weaker signals too.
"Actual Pivot Points" are inherintly more accurate than Potential pivot points, but do not paint on the chart until after a pre-determined amount of time has passed. These are great for placing stop losses/take profits or watching the market for breakouts or reversals.
"Support/Resistance Levels" plots up to 6 support and resistance horizontal lines based on recent price tops/bottoms. Use these to determine areas where price could rebound or break-through.
"Bollinger Band Breakout" - Bollinger bands are a tried and tested technical analysis tool, similar to pivot points and support/resistance lines, thee are another great tool to determine where price may retrace, consolidate or breakout.
- Ichimoku Cloud
Somewhat confusing and intimidating when you first come across this technical analysis indicator, the "Ichimoku Cloud" is one of our favorites. Assisting with the detection of Dynamic Support and Resistance levels, Momentum and Trend Direction all in one super indicator.
Although certain aspects of the Ichimoku Cloud are already present within Crypto Tipster v2 algorithms in order to offer you the best possible signals, we've also included a user-definable section of it's own so you can manually set up and use the cloud for your own trading needs, all cloud signals (and there are many) are available to set up as Alerts for your own needs or an Auto-Trading Bot.
- Custom Alerts for Any Signal
We've endeavoured to ensure that all signals, not just the Buy/Sell signals, are ready and available to create Alerts with; giving you the most opportunity to create a fully custom trading engine that suits your exact trading requirements.
This means you can set Alerts for any and all signals you can see on the chart when using Crypto Tipster v2, this includes Buy/Sell Signals, Trend Strength Signals, Choppy Market Signals, Stop Loss/Take Profit Signals, Pivot Points, S/R levels crossed above & below, Bollinger Band Breakout and several Ichimoku Cloud Signals.. the list goes on!
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We've tried to make Crypto Tipster as comprehensive and easy to understand as possible, we are however always in search of progression; we do really love to hear your feedback :)
For more information and a free 8-day trial please visit the link in our signature
Happy Trading Guys
rt maax EMA cross strategythis just sample of our strategies we published with open source, to learning our investor the way of trading and analysis, this strategy just for study and learning
in this strategy we use expontial moving avarage 20 , 50 , 200 and the we build this strategy when the price move up ema 200 and ema 20,50 cross up the 200 ema in this conditions the strargey will open long postion
and the oppisit it is true for short postion in this sitation the price should be under ema 200 and the ema 20 , 50 should cross under 200 ema then the strategy will open the short postion
we try this strategy on forex ,crypto and futures and it give us very good result ,, also we try this postion on multi time frame we find the stragey give us good result on 1 hour time frame .
in the end our advice for you before you use any stratgy you should have the knowledg of the indecators how it is work and also you should have information about the market you trade and the last news for this market beacuse it effect so much on the price moving .
so we hope this strategy give you brefing of the way we work and build our strategy
Catching the Bottom (by Coinrule)This script utilises the RSI and EMA indicators to enter and close the trade.
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
An 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 exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average (SMA), which applies an equal weight to all observations in the period.
The strategy enters and exits the trade based on the following conditions.
ENTRY
RSI has a decrease of 3.
RSI <40.
EMA100 has crossed above the EMA50.
EXIT
RSI is greater than 65.
EMA9 has crossed above EMA50.
This strategy is back tested from 1 April 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include ETH on the 5m timeframe, BNB on 5m timeframe, XRP on the 45m timeframe, MATIC on the 30m timeframe and MATIC on the 2H timeframe.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Crypto BTC Correlation Scalper Gaps StrategyThis strategy is based on the gaps theory.
In this case we have the BTC futures from CME, which acts in a way similar to stocks, and we can have gaps present between close/open session, and also sometimes between same candle due to huge movements intra candle.
At the same time I have combined this with a daily moving average, to help out a bit with the trend, since we are looking at small timeframe like 1-15/30min .
On top of that we have a reverse option, where long = short and viceversa, which can be used with against BTC pairs .
Rule are simple:
For long, we have a long gap and the close of the correlated candle is above daily sma
For short, we have a short gap and the close of the correlated candle is below daily sma
For exit:
For exit, we take the highest highest values for short entry TP, meaning we get the different from the HH and rest the current open candle distance, and use that distance as a TP.
At the same time for long entry, we take the lowest low value and rest current close of the candle to that value, and we get the TP.
Can also be applied this logic for SL aswell but from the test I have found out that exiting based on a reverse condition(when tp is not being hit), gives better results/dd overall.
If you have any questions, please let me know !
