MACD with 1D Stochastic Confirmation Reversal StrategyOverview
The MACD with 1D Stochastic Confirmation Reversal Strategy utilizes MACD indicator in conjunction with 1 day timeframe Stochastic indicators to obtain the high probability short-term trend reversal signals. The main idea is to wait until MACD line crosses up it’s signal line, at the same time Stochastic indicator on 1D time frame shall show the uptrend (will be discussed in methodology) and not to be in the oversold territory. Strategy works on time frames from 30 min to 4 hours and opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Higher time frame confirmation: Strategy utilizes 1D Stochastic to establish the major trend and confirm the local reversals with the higher probability.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
MACD line of MACD indicator shall cross over the signal line of MACD indicator.
1D time frame Stochastic’s K line shall be above the D line.
1D time frame Stochastic’s K line value shall be below 80 (not overbought)
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 3.25, value multiplied by ATR to be subtracted from position entry price to setup stop loss)
ATR Trailing Profit Activation Level (by default = 4.25, value multiplied by ATR to be added to position entry price to setup trailing profit activation level)
Trailing EMA Length (by default = 20, period for EMA, when price reached trailing profit activation level EMA will stop out of position if price closes below it)
User can choose the optimal parameters during backtesting on certain price chart, in our example we use default settings.
Justification of Methodology
This strategy leverages 2 time frames analysis to have the high probability reversal setups on lower time frame in the direction of the 1D time frame trend. That’s why it’s recommended to use this strategy on 30 min – 4 hours time frames.
To have an approximation of 1D time frame trend strategy utilizes classical Stochastic indicator. The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
Strategy logic assumes that on 1D time frame it’s uptrend in %K line is above the %D line. Moreover, we can consider long trade only in %K line is below 80. It means that in overbought state the long trade will not be opened due to higher probability of pullback or even major trend reversal. If these conditions are met we are going to our working (lower) time frame.
On the chosen time frame, we remind you that for correct work of this strategy you shall use 30min – 4h time frames, MACD line shall cross over it’s signal line. The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a stock's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line=12-period EMA−26-period
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
In our script we are interested in only MACD and signal lines. When MACD line crosses signal line there is a high chance that short-term trend reversed to the upside. We use this strategy on 45 min time frame.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -4.79%
Maximum Single Profit: +20.14%
Net Profit: +2361.33 USDT (+44.72%)
Total Trades: 123 (44.72% win rate)
Profit Factor: 1.623
Maximum Accumulated Loss: 695.80 USDT (-5.48%)
Average Profit per Trade: 19.20 USDT (+0.59%)
Average Trade Duration: 30 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe between 30 min and 4 hours and chart (optimal performance observed on 45 min BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
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Quatro SMA Strategy [4h]Hello, I would like to present to you The "Quatro SMA" strategy
Strategy is based on four simple moving averages of different lengths and monitoring trading volume. The key idea is to identify strong market trends by comparing short-term moving averages with the long-term SMA. The strategy generates buy signals when all short-term SMAs are above the SMA(200) and the volume confirms the strength of the move. Similarly, sell signals are generated when all short-term SMAs are below the SMA(200), and the volume is sufficiently high.
The strategy manages risk by applying a stop loss and three different Take Profit levels (TP1, TP2, TP3), with varying percentages of the position closed at each level.
Each Take Profit level is triggered at a specific percentage gain, with the position being closed gradually depending on the achieved targets. The percentage of the position closed at each TP level is also defined by the user.
Indicators and Parameters:
Simple Moving Averages (SMA):
The script utilizes four simple moving averages with different lengths (4, 16, 32, 200). The first three SMAs (SMA1, SMA2, SMA3) are used to determine the trend direction, while the fourth SMA (with a length of 200) serves as a support/resistance line.
Volume:
The script monitors trading volume and checks if the current volume exceeds 2.5 times the average volume of the last 40 candles. High volume is considered as confirmation of trend strength.
Entry Conditions:
- Long Position: Triggered when SMA1 > SMA2 > SMA3, the closing price is above SMA(200), and the volume condition is met.
- Short Position: Triggered when SMA1 < SMA2 < SMA3, the closing price is below SMA(200), and the volume condition is met.
Exit Conditions:
- Long Position: Closed when SMA1 < SMA2 < SMA3 and the closing price is above SMA(200).
- Short Position: Closed when SMA1 > SMA2 > SMA3 and the closing price is below SMA(200).
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
;)
Double CCI Confirmed Hull Moving Average Reversal StrategyOverview
The Double CCI Confirmed Hull Moving Average Strategy utilizes hull moving average (HMA) in conjunction with two commodity channel index (CCI) indicators: the slow and fast to increase the probability of entering when the short and mid-term uptrend confirmed. The main idea is to wait until the price breaks the HMA while both CCI are showing that the uptrend has likely been already started. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Double trade setup confirmation: Strategy utilizes two different period CCI indicators to confirm the breakouts of HMA.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Short-term period CCI indicator shall be above 0.
Long-term period CCI indicator shall be above 0.
Price shall cross the HMA and candle close above it with the same candle
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 25, used for calculation short term period CCI
CCI Slow Length (by default = 50, used for calculation long term period CCI)
Hull MA Length (by default = 34, period of HMA, which shall be broken to open trade)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI and HMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator used in trading to measure a security's price relative to its average price over a given period. Developed by Donald Lambert in 1980, the CCI is primarily used to identify cyclical trends in a security, helping traders to spot potential buying or selling opportunities.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Hull Moving Average (HMA) is a type of moving average that was developed by Alan Hull to improve upon the traditional moving averages by reducing lag while maintaining smoothness. The goal of the HMA is to create an indicator that is both quick to respond to price changes and less prone to whipsaws (false signals).
How the Hull Moving Average is Calculated?
The Hull Moving Average is calculated using the following steps:
Weighted Moving Average (WMA): The HMA starts by calculating the Weighted Moving Average (WMA) of the price data over a period square root of n (sqrt(n))
Speed Adjustment: A WMA is then calculated for half of the period n/2, and this is multiplied by 2 to give more weight to recent prices.
Lag Reduction: The WMA of the full period n is subtracted from the doubled n/2 WMA.
Final Smoothing: To smooth the result and reduce noise, a WMA is calculated for the square root of the period n.
The formula can be represented as:
HMA(n) = WMA(WMA(n/2) × 2 − WMA(n), sqrt(n))
The Weighted Moving Average (WMA) is a type of moving average that gives more weight to recent data points, making it more responsive to recent price changes than a Simple Moving Average (SMA). In a WMA, each data point within the selected period is multiplied by a weight, with the most recent data receiving the highest weight. The sum of these weighted values is then divided by the sum of the weights to produce the WMA.
This strategy leverages HMA of user given period as a critical level which shall be broken to say that probability of trend change to the upside increased. HMA reacts faster than EMA or SMA to the price change, that’s why it increases chances to enter new trade earlier. Long-term period CCI helps to have an approximation of mid-term trend. If it’s above 0 the probability of uptrend increases. Short-period CCI allows to have an approximation of short-term trend reversal from down to uptrend. This approach increases chances to have a long trade setup in the direction of mid-term trend when the short-term trend starts to reverse.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses HMA to enter the trade, but for trailing it leverages EMA. It’s used because EMA has no such fast reaction to price move which increases probability not to be stopped out from any significant uptrend move.
Backtest Results
Operating window: Date range of backtests is 2022.07.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 100%
Maximum Single Position Loss: -4.67%
Maximum Single Profit: +19.66%
Net Profit: +14897.94 USDT (+148.98%)
Total Trades: 104 (36.54% win rate)
Profit Factor: 2.312
Maximum Accumulated Loss: 1302.66 USDT (-9.58%)
Average Profit per Trade: 143.25 USDT (+0.96%)
Average Trade Duration: 34 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Power Hour Money StrategyDescription of the Pine Script Code: "Power Hour Money Strategy"
This Pine Script strategy, "Power Hour Money Strategy," is designed to trade based on the alignment of multiple time frames (month, week, day, and hour). The strategy aims to enter long or short positions depending on whether all selected time frames are in sync (all green for long positions, all red for short positions). Additionally, the script includes configurations for trading during specific sessions and automatically closing positions at the end of the trading day.
Core Features:
1. Time Frame Sync Check:
- The strategy evaluates whether the current price is higher than the opening price for the month, week, day, and hour to determine if each time frame is "green" (bullish) or "red" (bearish).
2. Session Control:
- The user can select between different trading sessions:
- "NY Session 9:30-11:30"
- "Extended NY Session 8-4"
- "All Sessions"
- Trades are only executed if the current time falls within the selected session.
3. Trailing Stop Mechanism:
- The strategy includes an optional trailing stop mechanism for both long and short positions.
- The trailing stop is configured with a percentage loss from the current price to protect gains.
4. End-of-Day Position Management:
- An option is provided to automatically close all positions at the end of the trading day (5:45 PM Eastern Time).
Detailed Code Breakdown:
1. Input Settings:
- **Session Selection**: Allows the user to choose the trading session.
- **End-of-Day Close**: Option to automatically close positions at the end of the day.
- **Trailing Stop Loss**: Enables or disables the trailing stop loss feature and sets the percentage for long and short positions.
2. Time Frame Calculations:
- The script uses `request.security` to get the opening prices for higher time frames (monthly, weekly, daily, and hourly).
- It compares the current close price to these opening prices to determine if each time frame is green or red.
3. Session Time Definitions:
- Defines the start and end times for the NY session (9:30-11:30 AM) and the extended session (8:00 AM - 4:00 PM).
4. Trade Execution:
- The strategy checks if all selected time frames are in sync and if the current time falls within the trading session.
- If all conditions are met, it enters a long or short position.
5. Trailing Stop Loss Implementation:
- Adjusts the stop price based on the trailing percentage and the current position's size.
- Automatically exits positions if the trailing stop condition is met.
6. End-of-Day Close Implementation:
- Uses a timestamp to check if the current time is 5:45 PM Eastern Time.
- Closes all positions if the end-of-day condition is met.
7. Plotting and Logging:
- Plots indicators to visualize the green/red status of each time frame.
- Logs information about the status of each time frame for debugging and analysis.
Example Usage:
Entering a Long Position: If the month, week, day, and hour are all green and the current time is within the selected session, a long position is entered.
Entering a Short Position: If the month, week, day, and hour are all red and the current time is within the selected session, a short position is entered.
Trailing Stop: Protects gains by exiting the position if the price moves against the set trailing stop percentage.
End-of-Day Close: Automatically closes all open positions at 5:45 PM Eastern Time if enabled.
This strategy is particularly useful for traders who want to ensure that multiple time frames are in alignment before entering a trade and who wish to manage positions effectively throughout the trading day with specific session controls and trailing stops.
Ultimate Trading StrategyDescription:
In this TradingView Pine Script publication, we introduce a powerful tool designed to enhance your trading strategies by combining the Exponential Moving Average (EMA) and the Relative Strength Index (RSI). This strategy is specifically tailored for the EGLD/USDT.P pair on Binance, using a 5-minute interval to capture timely trading opportunities in a volatile market.
Key Features:
Combining EMA and RSI for Robust Signals
This script combines the EMA, which helps identify the overall trend direction, with the RSI, which measures the speed and change of price movements to identify overbought and oversold conditions.
The combination ensures that you get high-probability signals by leveraging both trend-following and momentum-based indicators.
Multiple Timeframe Analysis
Analyze the EMA and RSI across different timeframes to gain a comprehensive view of market conditions and make more informed trading decisions.
Reversing and Extending Signals
Reverse signals generated by indicators to adapt to various market conditions.
Extend signals by specifying conditions such as "RSI cross AND EMA cross WITHIN 2 bars" to capture more nuanced trading opportunities.
Backtesting and Risk Management
Evaluate the performance of your strategies by feeding the results into a backtesting engine.
The strategy risks a maximum of 10% of the account on a single trade to maintain sustainable risk levels.
Available Indicators:
EMA (Exponential Moving Average)
Helps identify the overall trend direction.
Signals:
Long Entry: When the price closes above the EMA.
Short Entry: When the price closes below the EMA.
RSI (Relative Strength Index)
Measures the speed and change of price movements.
Signals:
Long Entry: When RSI is below the oversold level (30).
Short Entry: When RSI is above the overbought level (70).
How It Works:
Long Entry: A buy signal is generated when the price closes above the EMA and the RSI is below the oversold level (30). This indicates that the price is in an upward trend and temporarily oversold, presenting a potential buying opportunity.
Short Entry: A sell signal is generated when the price closes below the EMA and the RSI is above the overbought level (70). This indicates that the price is in a downward trend and temporarily overbought, presenting a potential selling opportunity.
Close Long Position: The script closes long positions when the conditions for a short entry are met.
Close Short Position: The script closes short positions when the conditions for a long entry are met.
Parameters:
EMA Length: 20 (default)
RSI Length: 14 (default)
RSI Overbought Level: 70 (default)
RSI Oversold Level: 30 (default)
Initial Capital: 10,000 USDT (default) – Realistic starting capital for an average trader.
Commission: 0.1% (default) – Reflects typical trading commissions.
Slippage: 0.5 ticks (default) – Accounts for market conditions and potential price slippage during order execution.
Backtesting:
Trading Range: – Ensure that the dataset used covers a significant period to generate a sufficient number of trades.
Dataset Limitation: Due to TradingView Premium's limitation of backtesting only 20,000 candles, it may not be possible to generate more than 100 trades. This limitation affects the statistical relevance of the backtesting results, but the strategy has been tested to provide meaningful insights within these constraints.
Use Case:
This strategy combines the EMA and RSI to identify potential trading opportunities by detecting trend direction and overbought/oversold conditions. It is particularly effective in volatile markets where quick trend reversals are common.
How to Use:
Set the parameters according to your preference or use the default values.
Run the script on the EGLD/USDT.P pair with a 5-minute interval.
Monitor the signals and adjust your trades accordingly.
BabyShark VWAP Strategy What the code does:
This Pine Script implements a trading strategy based on two indicators: Volume Weighted Average Price (VWAP) and On Balance Volume (OBV) Relative Strength Index (RSI). The strategy aims to identify potential buy and sell signals based on deviations from VWAP and OBV RSI crossing certain threshold levels.
How it does it:
**VWAP Calculation**: The script calculates the VWAP using either standard deviation or average deviation over a specified length. It then plots the VWAP and its upper and lower deviation bands.
**OBV RSI Calculation**: It computes the OBV and then calculates the RSI using the cumulative changes in OBV. The RSI is plotted and compared against predefined levels.
**Table Visibility and Occurrence Counting**: It allows the user to display a table showing the number of occurrences where the price is above Upper Dev 2, below Lower Dev 2, crosses above a higher RSI level, or crosses below a lower RSI level.
**Entries**: Long and short entry conditions are defined based on the position of the price relative to the VWAP deviation bands and the color of the OBV RSI. Entries are made when specific conditions are met, and there hasn't been a recent entry.
**Exit Conditions**: The script includes stop-loss and take-profit mechanisms. It exits positions based on price crossing the VWAP or a certain percentage, and it prevents further trading after a certain number of consecutive losses.
What traders can use it for:
**Trend Identification**: Traders can use the VWAP and its deviation bands to identify potential trend reversals or continuations.
**Volume Confirmation**: The inclusion of OBV RSI provides confirmation of price movements based on volume changes.
**Entry and Exit Signals**: The script generates buy and sell signals based on the specified conditions, allowing traders to enter and exit positions with defined stop-loss and take-profit levels.
**Statistical Analysis**: The visibility of occurrence counts in the table allows traders to perform statistical analysis on the frequency of price movements relative to the VWAP and OBV RSI levels.
PS January Barometer BacktesterPS January Barometer Backtester (PS JBB)
The PS January Barometer Backtester (PS JBB) is a simple strategy designed to test the "January Effect" hypothesis in financial markets. This effect theorizes that stock market performance in January can predict the trend for the rest of the year. The script operates on a monthly timeframe, focusing on capturing and analyzing the price movements in January and their subsequent influence on the market until the end of each year.
User Input:
January Trifecta Selectors
These are user-selectable options allowing traders to incorporate additional criteria into their market analysis.
The Santa Claus Rally refers to a stock market increase typically seen in the last week of December through the first two trading days in January.
The First Five Days Indicator assesses market performance during the initial five days of the year.
Script Operation:
The script automatically detects the start of each year, tracks January's high, and signals entry and exit points for trades based on the strategy's logic. It's an excellent tool for traders and investors looking to explore the January Effect's validity and its potential impact on their trading decisions.
In essence, the "PS January Barometer Backtester" is designed to exploit specific seasonal market trends, particularly focusing on the early part of the year, by analyzing and acting upon defined market movements. This strategy is ideal for traders who focus on yearly cyclical patterns and seek to incorporate historical trends into their trading decisions.
Note: This script is intended for educational and research purposes and should not be construed as financial advice. Always conduct your own due diligence before making trading/investment decisions.
LuxAlgo - Backtester (OSC)The OSC Backtester is an innovative strategy script that allows users to create a wide variety of strategies using various unique oscillators.
By utilizing our 'Step' and 'Match' algorithms, users can create custom and complex strategy entries from each of the supported oscillators and included conditions, as well as any external sources, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each conditions will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Entries From Various Oscillators And Conditions
We allow the users to set entries using our unique HyperWave, Smart Money Flow, and their derived conditions as entries.
The Hyper Wave is a normalized adaptive oscillator aiming to reflect price trends without returning a high amount of noise.
The Smart Money Flow aims to detect trends based on market activity, by doing a comparative analysis between current volume and historical volume. A Smart Money Flow above 50 suggest market participants are bullish, else bearish. Derived from this oscillator we have Overflow indications, this indicator detects when market is overbought or oversold based on participants activity.
Other entries include proprietary reversal signals, real-time divergence detection, oscillator confluence (indicating how aligned each oscillator is), as well as entries using external sources.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create a wide variety of strategies from this script, whether they are trend-following or contrarian traders.
Let's see a contrarian (revesal-based) strategy example using the following entry conditions:
Long: Hyperwave bullish divergence and oversold Hyperwave (lower than 20).
Short: Hyperwave bearish divergence and overbought Hyperwave (greater than 20).
We can also introduce take-profit and stop-loss exit conditions based on external indicators, allowing more control over exits in our strategy. For example:
Long: Hyperwave crossing over 50 while money flow is bearish.
Short: Hyperwave crossing under 50 while money flow is bullish.
Exit Long on a profit (long exit tp): Hyperwave crossing 80.
Exit Short on a profit (short exit tp): Hyperwave crossing 20.
While this strategy script can be used as a standalone, we recommend using other indicators creatively to assist with entries and exits as well as TP/SLs.
Our Step & Match algorithm can magnify interoperability, allowing for way more complete strategies through complex conditions, let's demonstrate this using the following entries:
Long: Any bullish reversal occurring after the price crosses over the lowest upper reversal zone of the Signals & Overlays™.
Short: Any bearish reversal occurring after the price crosses under the highest lower reversal zone of the Signals & Overlays™.
Long TP/SL: 5 ATR's away from the entry price.
Short TP/SL: 5 ATR's away from the entry price.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 3 tick
Stop Loss: 0.02 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from the strategies built are realistic.
🔶 How To Access
You can see the Author's Instructions below to learn how to get access.
LuxAlgo - Backtester (PAC)The PAC Backtester is an innovative strategy script that allows users to create a wide variety of strategies derived from price action-related concepts for a data-driven approach to discretionary trading strategies.
Thanks to our 'Step' and 'Match' algorithm, users can create custom and complex strategy entries and exits from features such as market structure, order blocks, imbalances, as well as any external indicators, allowing users to create entries from a sequence of conditions and/or multiple matching conditions.
We included a complete alert system that will send a notification for each action taken by the strategy and we also allow users to set custom messages for each action taken by a strategy.
🔶 Features
🔹 Step & Match Algorithm
More complex entry rules can be created by using multiple conditions together, this is done thanks to the Step dropdown setting on the right of each condition.
The Step setting is directly related to the Step & Match algorithm and works in two ways:
When two or more conditions have the same step number, both conditions are evaluated. Used to test matching conditions.
When two or more conditions have different step numbers, each condition will be evaluated in order, testing for the first step and switching to the next step once the previous one is true. When the final step is true the strategy will open a market order. Used to create a sequence of conditions.
This operation is complementary, as you can create a sequence of conditions with one step consisting of two or more matching conditions as long as they have the same step number.
🔹 Fully Customizable Price Action Concepts As Entries
We allow the users to use market structures, order blocks, imbalances, and external sources together to set their custom entry and exit conditions.
Market structures are commonly used to determine trend direction by indicating when prices break prior swing points. Their occurrence can be used as entry conditions.
Order blocks highlight areas where institutional market participants open positions, one can use order blocks to determine confirmation entries or potential targets as we can expect there is a large amount of liquidity at these order blocks. Price entering, being within, or mitigating an order block can be used as an entry condition.
Market imbalances highlight areas where there is a disparity between supply and demand. Price entering, being within, or mitigating an imbalance can be used as an entry condition.
This system also allows the use of external sources to create entry and exit conditions, such as moving averages, bands, trailing stops...etc.
🔹 Complete Alert System
Users can get alerted for any action executed by a strategy, from opening positions to closing them.
The message field in the Alert Messages setting section allows for the strategy to send a custom alert message depending on the action taken by the strategy, if no messages are set the strategy will send default messages.
🔶 Usage
Users can create complete price action strategies from this script, let's see an example using the following entry conditions:
Long: Mitigated bearish order block occurring during the New York session after a mitigated bearish imbalance.
Short: Mitigated bullish order block occurring during the New York session after a mitigated bullish imbalance.
Take Profit: 2 points away from the entry price.
Stop Loss: 1 point away from the entry price.
We can also use features from Price Action Concepts™ to construct custom exit conditions, leading to the following strategy conditions:
Long: Bullish CHoCH and price mitigates bearish FVG.
Short: Bearish CHoCH and price mitigates bullish FVG.
Exit Long: Price mitigates bearish order block.
Exit Short: Price mitigates bullish order block.
Users can achieve a wide variety of results by using external indicators as an input source for entries and exits, combining the best from price action and technical indicators. We might for example be interested in exiting a position when the RSI oscillator is overbought or oversold.
🔶 Strategy Properties (Important)
This script backtest is done on daily EURGBP, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Comission: 3.4 pips (average spread for EURGBP)
Slippage: 1 tick
Stop Loss: 0.01 points away from entry price
We use these properties to ensure a realistic preview of the backtesting system, do note that default properties can be different for various reasons described below:
Order Size: 1 contract by default, this is to allow the strategy to run properly on most instruments such as futures.
Comission: Comission can vary depending on the market and instrument, there is no default value that might return realistic results.
We strongly recommend all users to ensure they adjust the Properties within the script settings to be in line with their accounts & trading platforms of choice to ensure results from strategies built are realistic.
🔶 How to access
You can see the Author's Instructions below to learn how to get access.
Linear Cross Trading StrategyLinear Cross Trading Strategy
The Linear Cross trading strategy is a technical analysis strategy that uses linear regression to predict the future price of a stock. The strategy is based on the following principles:
The price of a stock tends to follow a linear trend over time.
The slope of the linear trend can be used to predict the future price of the stock.
The strategy enters a long position when the predicted price crosses above the current price, and exits the position when the predicted price crosses below the current price.
The Linear Cross trading strategy is implemented in the TradingView Pine script below. The script first calculates the linear regression of the stock price over a specified period of time. The script then plots the predicted price and the current price on the chart. The script also defines two signals:
Long signal: The long signal is triggered when the predicted price crosses above the current price.
Short signal: The short signal is triggered when the predicted price crosses below the current price.
The script enters a long position when the long signal is triggered and exits the position when the short signal is triggered.
Here is a more detailed explanation of the steps involved in the Linear Cross trading strategy:
Calculate the linear regression of the stock price over a specified period of time.
Plot the predicted price and the current price on the chart.
Define two signals: the long signal and the short signal.
Enter a long position when the long signal is triggered.
Exit the long position when the short signal is triggered.
The Linear Cross trading strategy is a simple and effective way to trade stocks. However, it is important to note that no trading strategy is guaranteed to be profitable. It is always important to do your own research and backtest the strategy before using it to trade real money.
Here are some additional things to keep in mind when using the Linear Cross trading strategy:
The length of the linear regression period is a key parameter that affects the performance of the strategy. A longer period will smooth out the noise in the price data, but it will also make the strategy less responsive to changes in the price.
The strategy is more likely to generate profitable trades when the stock price is trending. However, the strategy can also generate profitable trades in ranging markets.
The strategy is not immune to losses. It is important to use risk management techniques to protect your capital when using the strategy.
I hope this blog post helps you understand the Linear Cross trading strategy better. Booost and share with your friend, if you like.
TASC 2023.09 The Weekly Factor█ OVERVIEW
TASC's September 2023 edition of Traders' Tips features an article written by Andrea Unger titled “The Weekly Factor", discussing the application of price patterns as filters for trade entries. This script implements a sample trading strategy presented in the article for demonstration purposes only. It explores how the strategy's equity curve might benefit from filtering trade entries using a specific price pattern.
█ CONCEPTS
Pattern filters represent valuable tools that assess current market conditions based on price movements and determine when those conditions become more favorable for trade entries.
The filter used and tested in this article is a metric called the "weekly factor", which measures the price range over the last five trading days and compares it to the open of the session five days ago and the close of the session one day ago (i.e., the "body" of the five-day period). When the five-day body is small compared to the five-day range, this could indicate "indecision" or "compression", potentially followed by a price expansion. Thus, the weekly factor metric can help identify areas in the market where a period of compression might signal a potential breakout.
This script demonstrates the use of the weekly factor for a sample intraday trading strategy (intended for educational and exploratory purposes only). In this strategy, the entry signal is triggered when a 15-minute bar breaks out of the previous day's high-low range, and the position is closed at the end of the day.
█ CALCULATIONS
The script uses two timeframes:
• The strategy entries are processed on the 15-minute timeframe.
• The weekly factor is obtained from the daily timeframe using the request.security function and the following formula:
math.abs(open - close ) < RangeFilter * (ta.highest(5) - ta.lowest(5) )
Here, RangeFilter is an input that can be optimized to find the favorable ratio between the five-day body and the five-day range. Smaller RangeFilter values will lead to fewer trade entries. A RangeFilter value of 1 is equivalent to turning off the filtering altogether.
PercentX Trend Follower [Trendoscope]"Trendoscope" was born from our trading journey, where we first delved into the world of trend-following methods. Over time, we discovered the captivating allure of pattern analysis and the exciting challenges it presented, drawing us into exploring new horizons. However, our dedication to trend-following methodologies remains steadfast and continues to be an integral part of our core philosophy.
Here we are, introducing another effective trend-following methodology, employing straightforward yet powerful techniques.
🎲 Concepts
Introducing the innovative PercentX Oscillator , a representation of Bollinger PercentB and Keltner Percent K. This powerful tool offers users the flexibility to customize their PercentK oscillator, including options for the type of moving average and length.
The Oscillator Range is derived dynamically, utilizing two lengths - inner and outer. The inner length initiates the calculation of the oscillator's highest and lowest range, while the outer length is used for further calculations, involving either a moving average or the opposite side of the highest/lowest range, to obtain the oscillator ranges.
Next, the Oscillator Boundaries are derived by applying another round of high/low or moving average calculations on the oscillator range values.
Breakouts occur when the close price crosses above the upper boundary or below the lower boundary, signaling potential trading opportunities.
🎲 How to trade a breakout?
To reduce false signals, we employ a simple yet effective approach. Instead of executing market trades, we use stop orders on both sides at a certain distance from the current close price.
In case of an upper side breakout, a long stop order is placed at 1XATR above the close, and a short stop order is placed at 2XATR below the close. Conversely, for a lower side breakout, a short stop order is placed at 1XATR below the close, and a long stop order is placed at 2XATR above the ATR. As a trend following method, our first inclination is to trade on the side of breakout and not to find the reversals. Hence, higher multiplier is used for the direction opposite to the breakout.
The script provides users with the option to specify ATR multipliers for both sides.
Once a trade is initiated, the opposite side of the trade is converted into a stop-loss order. In the event of a breakout, the script will either place new long and short stop orders (if no existing trade is present) or update the stop-loss orders if a trade is currently running.
As a trend-following strategy, this script does not rely on specific targets or target levels. The objective is to run the trade as long as possible to generate profits. The trade is only stopped when the stop-loss is triggered, which is updated with every breakout to secure potential gains and minimize risks.
🎲 Default trade parameters
Script uses 10% equity per trade and up to 4 pyramid orders. Hence, the maximum invested amount at a time is 40% of the equity. Due to this, the comparison between buy and hold does not show a clear picture for the trade.
Feel free to explore and optimize the parameters further for your favorite symbols.
🎲 Visual representation
The blue line represents the PercentX Oscillator, orange and lime colored lines represent oscillator ranges. And red/green lines represent oscillator boundaries. Oscillator spikes upon breakout are highlighted with color fills.
Buy Only Strategy with Dynamic Re-Entry and ExitThe strategy aims to create a simple buy-only trading system based on moving average crossovers and the Weekly Commodity Channel Index (CCI) or Weekly Average Directional Index (ADX). It generates buy signals when the fast-moving average crosses above the slow-moving average and when the Weekly CCI and or Weekly ADX meet the specified conditions.
The strategy also allows for dynamic re-entry, which means it can open new long positions if the price goes above the three moving averages after an exit. However, the strategy will exit the long position if the price closes below the third moving average.
ENTRY CONDITIONS
The script defines the conditions for generating buy signals. It checks for two conditions for a valid buy signal:
• If the fast-moving average crosses above the slow-moving average -THERE IS Dynamic Re-Entry also
• If the user chooses HE OR SHE CAN FILTER TRADES BY USING CCI OR ADX
Dynamic Re-Entry:
the script allows for dynamic re-entry. If there is no active long position and the price is above all three moving averages a new long position is opened.
Exit Conditions
The script defines the exit condition for closing a long position. If the price closes below the third moving average, the script closes the long position.
IMPORTANT NOTICE
ONLY DAILY TIME FRAME
THERE WOULD BE WHIPSAW USE YOUR OWN ACCUMEN TO MINIMISE THEM
ITS ONLY BUY STRATEGY
EXIT CAN BE STRATEGY BASED OR SET PROFIT AND TARGETS AS PER RISK APETITE /RISK MANAGEMENT
DONT TRADE OPTIONS ON THIS
SUITABLE FOR STOCKS OF USA AND INDIAN MARKETS
ALWAYS REMEMBER TO DO YOUR OWN RESEARCH BEFORE TRADING AND INVESTING
Risk to Reward - FIXED SL BacktesterDon't know how to code? No problem! TradingView is an excellent platform for you. ✅ ✅
If you have an indicator that you want to backtest using a risk-to-reward ratio or fixed take profit/stop loss levels, then the Risk to Reward - FIXED SL Backtester script is the perfect solution for you.
introducing Risk to Reward - FIXED SL Backtester Script which will allow you to test any indicator / Signal with RR or Fixed SL system
How does it work ?!
Once you connect the script to your indicator, it will analyze your entry points and perform calculations based on them. It will then open trades for you according to the specified inputs in the script settings.
HOW TO CONNECT IT to your indicator?
simply open your indicator code and add the below line of code to it
plot(Signal ? 100 : 0,"Signal",display = display.data_window)
Replace Signal with the long condition from your own indicator. You can also modify the value 100 to any number you prefer. After that, open the settings.
Once the script is connected to your indicator, you can choose from two options:
Risk To Reward Ratio System
Fixed TP/ SL System
🔸if you select the Risk to Reward System ⤵️
The Risk-to-Reward System requires the calculation of a stop loss. That's why I have included three different types of stop-loss calculations for you to choose from:
ATR Based SL
Pivot Low SL
VWAP Based SL
Your stop loss and take profit levels will be automatically calculated based on the selected stop loss method and your risk-to-reward ratio.
You can also adjust their values to match your desired risk level. The trades will be displayed on the chart.
with the ability to change their values to match your risk.
once this is done, trades will be displayed on the chart
🔸if you select the Fixed system ⤵️
You have 2 inputs, which are FIXED TP & Fixed SL
input the values you want, and trades will be on your chart...
I have also added a Breakeven feature for you.
with this Breakeven feature the trade will not just move SL to Entry ?! NO NO, it will place it above entry by a % you input yourself, so you always win! 🚀
Here is an example
Enjoy, and have fun, if you have any questions do not hesitate to ask
Williams %R Cross Strategy with 200 MA Filter
1. The script is a trading strategy based on the Williams %R indicator and a 200-period moving average (MA) filter.
2. The user can input the length of the Williams %R indicator (`wrLength`), the threshold for %R crossing (`crossPips`), the take profit level in pips (`takeProfitPips`), and the stop loss level in pips (`stopLossPips`).
3. The script calculates the Williams %R using the `ta.highest` and `ta.lowest` functions to find the highest high and lowest low over the specified length (`wrLength`).
4. It also calculates a 200-period simple moving average (`ma200`) using the `ta.sma` function.
5. The entry conditions are defined as follows:
- For a long entry, it checks if the Williams %R crosses above the -50 line by a threshold of `crossPips` and if the close price is above the 200-period MA.
- For a short entry, it checks if the Williams %R crosses below the -50 line by a threshold of `crossPips` and if the close price is below the 200-period MA.
6. The exit conditions are defined as follows:
- For a long position, it checks if the close price reaches the take profit level (defined as the average entry price plus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price minus `stopLossPips` in pips).
- For a short position, it checks if the close price reaches the take profit level (defined as the average entry price minus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price plus `stopLossPips` in pips).
7. The script uses the `strategy.entry` function to place long and short orders when the respective entry conditions are met.
8. It uses the `strategy.close` function to close the long and short positions when the respective exit conditions are met.
The script allows you to customize the parameters such as the length of Williams %R, the crossing threshold, take profit and stop loss levels, and the moving average period to suit your trading preferences.
HK Percentile Interpolation One
This script is designed to execute a trading strategy based on Heikin Ashi candlesticks, moving averages, and percentile levels.
Please note that you should keep your original chart in normal candlestick mode and not switch it to Heikin Ashi mode. The script itself calculates Heikin Ashi values from regular candlesticks. If your chart is already in Heikin Ashi mode, the script would be calculating Heikin Ashi values based on Heikin Ashi values, which would produce incorrect results.
The strategy begins trading from a start date that you can specify by modifying the `startDate` parameter. The format of the date is "YYYY MM DD". So, for example, to start the strategy from January 1, 2022, you would set `startDate = timestamp("2022 01 01")`.
The script uses Heikin Ashi candlesticks, which are plotted in the chart. This approach can be useful for spotting trends and reversals more easily than with regular candlestick charts. This is particularly useful when backtesting in TradingView's "Rewind" mode, as you can see how the Heikin Ashi candles behaved at each step of the strategy.
Buy and sell signals are generated based on two factors:
1. The crossing over or under of the Heikin Ashi close price and the 75th percentile price level.
2. The Heikin Ashi close price being above certain moving averages.
You have the flexibility to adjust several parameters in the script, including:
1. The stop loss and trailing stop percentages (`stopLossPercentage` and `trailStopPercentage`). These parameters allow the strategy to exit trades if the price moves against you by a certain percentage.
2. The lookback period (`lookback`) used to calculate percentile levels. This determines the range of past bars used in the percentile calculation.
3. The lengths of the two moving averages (`yellowLine_length` and `purplLine_length`). These determine how sensitive the moving averages are to recent price changes.
4. The minimum holding period (`holdPeriod`). This sets the minimum number of bars that a trade must be kept open before it can be closed.
Please adjust these parameters according to your trading preferences and risk tolerance. Happy trading!
Lorentzian Classification Strategy Based in the model of Machine learning: Lorentzian Classification by @jdehorty, you will be able to get into trending moves and get interesting entries in the market with this strategy. I also put some new features for better backtesting results!
Backtesting context: 2022-07-19 to 2023-04-14 of US500 1H by PEPPERSTONE. Commissions: 0.03% for each entry, 0.03% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 3 indicators are used:
Machine learning: Lorentzian Classification by @jdehorty
One Ema of 200 periods for identifying the trend
Supertrend indicator as a filter for some exits
Atr stop loss from Gatherio
Trade conditions:
For longs:
Close price is above 200 Ema
Lorentzian Classification indicates a buying signal
This gives us our long signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 1:1 and take profit of 3:1 where half position will be closed. This will be showed as buy.
The other half will be closed when the model indicates a selling signal or Supertrend indicator gives a bearish signal. This will be showed as cl buy.
For shorts:
Close price is under 200 Ema
Lorentzian Classification indicates a selling signal
This gives us our short signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 1:1 and take profit of 3:1 where half position will be closed. This will be showed as sell.
The other half will be closed when the model indicates a buying signal or Supertrend indicator gives a bullish signal. This will be showed as cl sell.
Risk management
To calculate the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss or last swing for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss or last swing is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
> In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
> You can also choose a fixed amount, so you will have to activate fixed amount in risk management for trades and set the fixed amount for backtesting.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, a table of some stats from backtesting, etc.
You will find the settings for risk management at the end of the script if you want to change something or trying new values for other assets for backtesting.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital
I also added a function for backtesting if you had added or withdrawn money frequently:
Adding money: You can choose how often you want to add money (Monthly, yearly, daily or weekly). Then a fixed amount of money and activate or deactivate this function
Withdraw money: You can choose if you want to withdraw a fixed amount or a percentage of earnings. Then you can choose a fixed amount of money, the period of time and activate or deactivate this function. Also, the percentage of earnings if you choosed this option.
Some other assets where strategy has worked
BTCUSD 4H, 1D
ETHUSD 4H, 1D
BNBUSD 4H
SPX 1D
BANKNIFTY 4H, 15 min
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!. If you have problems loading the script reduce max bars back number in general settings
Strategies for trending markets use to have more looses than wins and it takes a long time to get profits, so do not forget to be patient and consistent !
Please, visit the post from @jdehorty called Machine Learning: Lorentzian Classification for a better understanding of his script!
Any support and boosts will be well received. If you have any question, do not doubt to ask!
I11L - Better Buy Low Volatility or High Volatility?This Pine Script code defines a TradingView strategy called "I11L - Better Buy Low Volatility or High Volatility?". The strategy aims to study the difference between buying when an asset's volatility is low and when it is high. It allows the user to select whether to buy during low or high volatility periods by changing the input variable mode.
Here's a brief explanation of the System:
The strategy is initialized with relevant settings such as overlay, pyramiding, default quantity type, initial capital, and others.
The mode input allows the user to choose between "Buy low Volatility" and "Buy high Volatility" options.
volatilityTargetRatio is the user-defined threshold to be used for making buy decisions. A value of 1 equals the average ATR (Average True Range) for the security. A lower value indicates lower volatility.
atrLength is the number of periods to calculate the ATR.
sellAfterNBarsLength sets the number of bars to hold the position before selling it.
The script calculates the ATR using the ta.atr() function, and then divides it by the closing price to normalize the value. It also calculates the simple moving average (SMA) of the normalized ATR over a period of 5 times the ATR length, and then computes the ratio between the normalized ATR and its average.
The script keeps track of the number of holding bars using the variable holdingBarsCounter. When there are open trades, the holding bars counter is incremented.
The decision to buy is made based on the selected mode and whether the computed ratio is above or below the user-defined threshold.
When the holding bars counter exceeds the user-defined limit, the position is closed.
The script plots the computed ratio with different colors based on the buy and close conditions. The ratio is plotted in green when a buy signal is triggered, red when a close signal is triggered, and white in all other cases. The value of 1 (the reference for the average ATR) is also plotted on the chart in white color.
This strategy helps traders study the difference between buying during low and high volatility periods and compare the performance of these conditions. It can be useful for analyzing the effectiveness of volatility-based trading strategies, such as entering positions when the market is calm or during periods of strong price movement.
Donchian Trend V1The Donchian Trend strategy is a trend-following approach that uses the Donchian Channels indicator to identify potential entry and exit points in a security. The Donchian Channels are formed by taking the highest high and the lowest low prices over a specified period and plotting them as upper and lower channels around the current price. The width of the channels indicates the level of volatility in the market.
In this strategy, the Donchian Channels are used as a trend filter to determine the direction of the market. When the price is above the upper channel, it suggests an uptrend, and when the price is below the lower channel, it indicates a downtrend. The length of the Donchian Channels is a key parameter in the strategy, as it determines the look-back period for identifying the high and low prices.
Additional Logic: To further refine the entry and exit signals, The script uses two moving averages, a fast one (MA5) and a slow one (MA45), to identify trends and generate trading signals. When the fast moving average crosses above the slow moving average, a buy signal is generated, indicating that the market is trending upwards. Conversely, when the fast moving average crosses below the slow moving average, a sell signal is generated, indicating that the market is trending downwards.
Evaluation: The script was backtested on historical price data for the pair. The backtest results showed that the script was able to generate a net profit of , with a profit factor of and a Sharpe ratio of . The script also includes metrics such as the number of winning and losing trades, the average trade, and the largest winning and losing trades.
The strategy is evaluated based on its net profit, gross profit, gross loss, max run-up, max drawdown, buy & hold return, Sharpe ratio, Sortino ratio, and profit factor. The parameters used in the backtest include a Donchian Channel length of 42, which corresponds to a weekly time with divide of 4h time frame, and a short-term MA of 5 and a long-term MA of 45 for more accurate entry and exit signals.
Disclaimer: This script is for educational and research purposes only and should not be used for trading with real money without further testing and validation. Past performance is not indicative of future results.
Quarterly Returns in Strategies vs Buy & HoldThis is a Quarterly Returns version of Monthly Returns in PineScript Strategies by QuantNomad
This script shows a table of Quarterly/Yearly performance of your strategy.
It also provides an option to compare with Buy & Hold.
The script can easily integrated to your strategy. All you need to do is copy the table part and paste it at the end of your script
Disclaimer
Please remember that past performance may not be indicative of future results.
This post and the script don’t provide any financial advice.
Band-Zigzag - TrendFollower Strategy [Trendoscope]Strategy Time!!!
Have built this on my earlier published indicator Band-Zigzag-Trend-Follower . This is just one possible implementation of strategy on Band-Based-Zigzag .
🎲 Notes
Experimental prototype. Not financial advise and strategy not guaranteed to make money despite backtest results
Not created or tested for any specific instrument or timeframe
Test and adopt with own risk
🎲 Strategy
This is trend following strategy built based on Bands and Zigzag. Traits of trend following strategies are
Lower win rate (Yes, thats right)
High risk reward (Compensates low win rate)
Higher drawdown
If market is choppy, trend following methods suffer.
The script implements few points to overcome the negatives such as lower win rate and higher drawdown by actively assessing pivots on the direction of trend along. This helps us take regular profits and exit on time during the end of trend. Most of the other concepts are defined and explained in indicator - Band-Zigzag-Trend-Follower and Band-Based-Zigzag
Defining a trend following method is simple. Basic rule of trend following is Buy High and Sell Low (Yes, you heard it right). To explain further - methodology involve finding an established trend which is flying high and join the trend with proper risk and optimal stop. Once you get into the trade, you will not exit unless there is change in the trend. Or in other words, the parameters which you used to define trend has reversed and the trend is not valid anymore.
🎯 Using bands
When price breaks out of upper bands (example, Bollinger Band , Keltener Channel, or Donchian Channel), with a pre determined length and multiplier, we can consider the trend to be bullish and similarly when price breaks down the lower band, we can consider the trend to be bearish .
🎯 Using Pivots
Simple logic using zigzag or pivot points is that when price starts making higher highs and higher lows, we can consider this as uptrend. And when price starts making lower highs and lower lows, we can consider this as downtrend. There are few supertrend implementations I have published in the past based on zigzags and pivot points .
Drawbacks of both of these methods is that there will be too many fluctuations in both cases unless we increase the reference length. And if we increase the reference length, we will have higher drawdown.
🎯 Band Based Zigzag Method
Here we use bands to define our pivot high and pivot low - this makes sure that we are identifying trend only on breakouts as pivots are only formed on breakouts
Our method also includes pivot ratio to cross over 1.0 to be able to consider it as trend. This means, we are waiting for price also to make new high high or lower low before making the decision on trend. But, this helps us ignore smaller pivot movements due to the usage of bands.
I have also implemented few tricks such as sticky bands (Bands will not contract unless there is breakout) and Adaptive Bands (Band will not expand unless price is moving in the direction of band). This makes the trend following method very robust.
To avoid fakeouts, we also use percentB of high/low in comparison with price retracement to define breakout.
🎲 Settings
Settings are fairly simpler and are explained as below. You will find most of the required information in tooltips.
[XRP][1h] Chanu Delta inspired — Breakeven StrategyHello, this is my first TV contribution. I usually don't publish anything but the script is a quick review of an other contributor (Chanu Delta V3 script )
I reverse engineered this indicator today as I wanted to test it on other contracts. The original version (which aims to be traded on BTC) has been ported to XRP (as btc and xrp prices are narrowly correlated) then modified with a couple of what I believe are improvements:
- No backtest bias even with `security` function.
- Extra backtest bias validation, always trading on next bar as Crossover/under bias is confirmed
- Backtest with 2 ajustable TP, ajustable equity and breakeven option
- The current version is not design to use pyramiding as it would require extra logic to monitor the lifecycle of the position in the context of a study.
- Commented alerts examples with variables available in script scope so you can use them in alerts (just replace strategy with indicator and remove backtest related code block).
- Trade filling assumption set to 10, fees to 0.02 as the are default bybit maker fees and I advice to enter with trailing orders using a max of 2 ticks as offset to lower fees rather than a market order!
- Backtest and Alerts happen on barclose.
- No repaint guaranteed.
There are a thousand ways to improve it (adx/bb based dynamic TP/SL, order lifecycle, pyramiding...) but it seems to be a cool starting point.
Don't forget to have fun!
BT-SAR Ema, Squeeze, Volatility
Esse script foi criado para estudo de Backtest.
Ele usa o SAR PARABÓLICO como indicador de sinal de entrada, você também pode combinar 3 indicadores para filtrar as entradas: Média Móvel, Squeeze Momentum e Volatility Oscilator .
Existe duas entradas, quando o SAR Parabólico vira ou pelo Breakout (usando o último preço) do SAR Parabólico antes dele virar.
As Os filtros podem ser usados de forma combinada ou individual.
O Script também pode ser usado com algum serviço de bot como 3commas.io, basta colocar as mensagens de entrada e saída para o bot.
This script was created for Backtest study.
It uses PARABOLIC SAR as input signal indicator, you can also combine 3 indicators to filter inputs: Moving Average, Squeeze Momentum and Volatility Oscillator .
There are two entries, when the Parabolic SAR turns or by Breakout (using the last price) of the Parabolic SAR before it turns.
The Filters can be used in combination or individually.
The Script can also be used with some bot service like 3commas.io, just put the input and output messages to the bot.
