Mean Reversion Cloud (Ornstein-Uhlenbeck) // AlgoFyreThe Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator detects mean-reversion opportunities by applying the Ornstein-Uhlenbeck process. It calculates a dynamic mean using an Exponential Weighted Moving Average, surrounded by volatility bands, signaling potential buy/sell points when prices deviate.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Adaptive Mean Calculation
🔸Volatility-Based Cloud
🔸Speed of Reversion (θ)
🔶 FUNCTIONALITY
🔸Dynamic Mean and Volatility Bands
🞘 How it works
🞘 How to calculate
🞘 Code extract
🔸Visualization via Table and Plotshapes
🞘 Table Overview
🞘 Plotshapes Explanation
🞘 Code extract
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
🞘 Understanding What to Look For on the Chart
🞘 Possible Entry Signals
🞘 Possible Take Profit Strategies
🞘 Possible Stop-Loss Levels
🞘 Additional Tips
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) is a unique indicator that applies the Ornstein-Uhlenbeck stochastic process to identify mean-reverting behavior in asset prices. Unlike traditional moving average-based indicators, this model uses an Exponentially Weighted Moving Average (EWMA) to calculate the long-term mean, dynamically adjusting to recent price movements while still considering all historical data. It also incorporates volatility bands, providing a "cloud" that visually highlights overbought or oversold conditions. By calculating the speed of mean reversion (θ) through the autocorrelation of log returns, this indicator offers traders a more nuanced and mathematically robust tool for identifying mean-reversion opportunities. These innovations make it especially useful for markets that exhibit range-bound characteristics, offering timely buy and sell signals based on statistical deviations from the mean.
🔸Adaptive Mean Calculation Traditional MA indicators use fixed lengths, which can lead to lagging signals or over-sensitivity in volatile markets. The Mean Reversion Cloud uses an Exponentially Weighted Moving Average (EWMA), which adapts to price movements by dynamically adjusting its calculation, offering a more responsive mean.
🔸Volatility-Based Cloud Unlike simple moving averages that only plot a single line, the Mean Reversion Cloud surrounds the dynamic mean with volatility bands. These bands, based on standard deviations, provide traders with a visual cue of when prices are statistically likely to revert, highlighting potential reversal zones.
🔸Speed of Reversion (θ) The indicator goes beyond price averages by calculating the speed at which the price reverts to the mean (θ), using the autocorrelation of log returns. This gives traders an additional tool for estimating the likelihood and timing of mean reversion, making the signals more reliable in practice.
🔶 FUNCTIONALITY The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator is designed to detect potential mean-reversion opportunities in asset prices by applying the Ornstein-Uhlenbeck stochastic process. It calculates a dynamic mean through the Exponentially Weighted Moving Average (EWMA) and plots volatility bands based on the standard deviation of the asset's price over a specified period. These bands create a "cloud" that represents expected price fluctuations, helping traders to identify overbought or oversold conditions. By calculating the speed of reversion (θ) from the autocorrelation of log returns, the indicator offers a more refined way of assessing how quickly prices may revert to the mean. Additionally, the inclusion of volatility provides a comprehensive view of market conditions, allowing for more accurate buy and sell signals.
Let's dive into the details:
🔸Dynamic Mean and Volatility Bands The dynamic mean (μ) is calculated using the EWMA, giving more weight to recent prices but considering all historical data. This process closely resembles the Ornstein-Uhlenbeck (OU) process, which models the tendency of a stochastic variable (such as price) to revert to its mean over time. Volatility bands are plotted around the mean using standard deviation, forming the "cloud" that signals overbought or oversold conditions. The cloud adapts dynamically to price fluctuations and market volatility, making it a versatile tool for mean-reversion strategies. 🞘 How it works Step one: Calculate the dynamic mean (μ) The Ornstein-Uhlenbeck process describes how a variable, such as an asset's price, tends to revert to a long-term mean while subject to random fluctuations. In this indicator, the EWMA is used to compute the dynamic mean (μ), mimicking the mean-reverting behavior of the OU process. Use the EWMA formula to compute a weighted mean that adjusts to recent price movements. Assign exponentially decreasing weights to older data while giving more emphasis to current prices. Step two: Plot volatility bands Calculate the standard deviation of the price over a user-defined period to determine market volatility. Position the upper and lower bands around the mean by adding and subtracting a multiple of the standard deviation. 🞘 How to calculate Exponential Weighted Moving Average (EWMA)
The EWMA dynamically adjusts to recent price movements:
mu_t = lambda * mu_{t-1} + (1 - lambda) * P_t
Where mu_t is the mean at time t, lambda is the decay factor, and P_t is the price at time t. The higher the decay factor, the more weight is given to recent data.
Autocorrelation (ρ) and Standard Deviation (σ)
To measure mean reversion speed and volatility: rho = correlation(log(close), log(close ), length) Where rho is the autocorrelation of log returns over a specified period.
To calculate volatility:
sigma = stdev(close, length)
Where sigma is the standard deviation of the asset's closing price over a specified length.
Upper and Lower Bands
The upper and lower bands are calculated as follows:
upper_band = mu + (threshold * sigma)
lower_band = mu - (threshold * sigma)
Where threshold is a multiplier for the standard deviation, usually set to 2. These bands represent the range within which the price is expected to fluctuate, based on current volatility and the mean.
🞘 Code extract // Calculate Returns
returns = math.log(close / close )
// Calculate Long-Term Mean (μ) using EWMA over the entire dataset
var float ewma_mu = na // Initialize ewma_mu as 'na'
ewma_mu := na(ewma_mu ) ? close : decay_factor * ewma_mu + (1 - decay_factor) * close
mu = ewma_mu
// Calculate Autocorrelation at Lag 1
rho1 = ta.correlation(returns, returns , corr_length)
// Ensure rho1 is within valid range to avoid errors
rho1 := na(rho1) or rho1 <= 0 ? 0.0001 : rho1
// Calculate Speed of Mean Reversion (θ)
theta = -math.log(rho1)
// Calculate Volatility (σ)
sigma = ta.stdev(close, corr_length)
// Calculate Upper and Lower Bands
upper_band = mu + threshold * sigma
lower_band = mu - threshold * sigma
🔸Visualization via Table and Plotshapes
The table shows key statistics such as the current value of the dynamic mean (μ), the number of times the price has crossed the upper or lower bands, and the consecutive number of bars that the price has remained in an overbought or oversold state.
Plotshapes (diamonds) are used to signal buy and sell opportunities. A green diamond below the price suggests a buy signal when the price crosses below the lower band, and a red diamond above the price indicates a sell signal when the price crosses above the upper band.
The table and plotshapes provide a comprehensive visualization, combining both statistical and actionable information to aid decision-making.
🞘 Code extract // Reset consecutive_bars when price crosses the mean
var consecutive_bars = 0
if (close < mu and close >= mu) or (close > mu and close <= mu)
consecutive_bars := 0
else if math.abs(deviation) > 0
consecutive_bars := math.min(consecutive_bars + 1, dev_length)
transparency = math.max(0, math.min(100, 100 - (consecutive_bars * 100 / dev_length)))
🔶 INSTRUCTIONS
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator can be set up by adding it to your TradingView chart and configuring parameters such as the decay factor, autocorrelation length, and volatility threshold to suit current market conditions. Look for price crossovers and deviations from the calculated mean for potential entry signals. Use the upper and lower bands as dynamic support/resistance levels for setting take profit and stop-loss orders. Combining this indicator with additional trend-following or momentum-based indicators can improve signal accuracy. Adjust settings for better mean-reversion detection and risk management.
🔸Step-by-Step Guidelines
🞘 Setting Up the Indicator
Adding the Indicator to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "Mean Reversion Cloud (Ornstein-Uhlenbeck)" in the indicators list.
Click on the indicator to add it to your chart.
Configuring the Indicator:
Open the indicator settings by clicking on the gear icon next to its name on the chart.
Decay Factor: Adjust the decay factor (λ) to control the responsiveness of the mean calculation. A higher value prioritizes recent data.
Autocorrelation Length: Set the autocorrelation length (θ) for calculating the speed of mean reversion. Longer lengths consider more historical data.
Threshold: Define the number of standard deviations for the upper and lower bands to determine how far price must deviate to trigger a signal.
Chart Setup:
Select the appropriate timeframe (e.g., 1-hour, daily) based on your trading strategy.
Consider using other indicators such as RSI or MACD to confirm buy and sell signals.
🞘 Understanding What to Look For on the Chart
Indicator Behavior:
Observe how the price interacts with the dynamic mean and volatility bands. The price staying within the bands suggests mean-reverting behavior, while crossing the bands signals potential entry points.
The indicator calculates overbought/oversold conditions based on deviation from the mean, highlighted by color-coded cloud areas on the chart.
Crossovers and Deviation:
Look for crossovers between the price and the mean (μ) or the bands. A bullish crossover occurs when the price crosses below the lower band, signaling a potential buying opportunity.
A bearish crossover occurs when the price crosses above the upper band, suggesting a potential sell signal.
Deviations from the mean indicate market extremes. A large deviation indicates that the price is far from the mean, suggesting a potential reversal.
Slope and Direction:
Pay attention to the slope of the mean (μ). A rising slope suggests bullish market conditions, while a declining slope signals a bearish market.
The steepness of the slope can indicate the strength of the mean-reversion trend.
🞘 Possible Entry Signals
Bullish Entry:
Crossover Entry: Enter a long position when the price crosses below the lower band with a positive deviation from the mean.
Confirmation Entry: Use additional indicators like RSI (above 50) or increasing volume to confirm the bullish signal.
Bearish Entry:
Crossover Entry: Enter a short position when the price crosses above the upper band with a negative deviation from the mean.
Confirmation Entry: Look for RSI (below 50) or decreasing volume to confirm the bearish signal.
Deviation Confirmation:
Enter trades when the deviation from the mean is significant, indicating that the price has strayed far from its expected value and is likely to revert.
🞘 Possible Take Profit Strategies
Static Take Profit Levels:
Set predefined take profit levels based on historical volatility, using the upper and lower bands as guides.
Place take profit orders near recent support/resistance levels, ensuring you're capitalizing on the mean-reversion behavior.
Trailing Stop Loss:
Use a trailing stop based on a percentage of the price deviation from the mean to lock in profits as the trend progresses.
Adjust the trailing stop dynamically along the calculated bands to protect profits as the price returns to the mean.
Deviation-Based Exits:
Exit when the deviation from the mean starts to decrease, signaling that the price is returning to its equilibrium.
🞘 Possible Stop-Loss Levels
Initial Stop Loss:
Place an initial stop loss outside the lower band (for long positions) or above the upper band (for short positions) to protect against excessive deviations.
Use a volatility-based buffer to avoid getting stopped out during normal price fluctuations.
Dynamic Stop Loss:
Move the stop loss closer to the mean as the price converges back towards equilibrium, reducing risk.
Adjust the stop loss dynamically along the bands to account for sudden market movements.
🞘 Additional Tips
Combine with Other Indicators:
Enhance your strategy by combining the Mean Reversion Cloud with momentum indicators like MACD, RSI, or Bollinger Bands to confirm market conditions.
Backtesting and Practice:
Backtest the indicator on historical data to understand how it performs in various market environments.
Practice using the indicator on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The indicator reacts to price data and might not account for news-driven events that can cause large deviations.
🔸Customize settings 🞘 Decay Factor (λ): Defines the weight assigned to recent price data in the calculation of the mean. A value closer to 1 places more emphasis on recent prices, while lower values create a smoother, more lagging mean.
🞘 Autocorrelation Length (θ): Sets the period for calculating the speed of mean reversion and volatility. Longer lengths capture more historical data, providing smoother calculations, while shorter lengths make the indicator more responsive.
🞘 Threshold (σ): Specifies the number of standard deviations used to create the upper and lower bands. Higher thresholds widen the bands, producing fewer signals, while lower thresholds tighten the bands for more frequent signals.
🞘 Max Gradient Length (γ): Determines the maximum number of consecutive bars for calculating the deviation gradient. This setting impacts the transparency of the plotted bands based on the length of deviation from the mean.
🔶 CONCLUSION
The Mean Reversion Cloud (Ornstein-Uhlenbeck) indicator offers a sophisticated approach to identifying mean-reversion opportunities by applying the Ornstein-Uhlenbeck stochastic process. This dynamic indicator calculates a responsive mean using an Exponentially Weighted Moving Average (EWMA) and plots volatility-based bands to highlight overbought and oversold conditions. By incorporating advanced statistical measures like autocorrelation and standard deviation, traders can better assess market extremes and potential reversals. The indicator’s ability to adapt to price behavior makes it a versatile tool for traders focused on both short-term price deviations and longer-term mean-reversion strategies. With its unique blend of statistical rigor and visual clarity, the Mean Reversion Cloud provides an invaluable tool for understanding and capitalizing on market inefficiencies.
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Ichimoku Crosses_RSI_AITIchimoku Crosser_RSI_AIT
Overview
The "Ichimoku Cloud Crosses_AIT" strategy is a technical trading strategy that combines the Ichimoku Cloud components with the Relative Strength Index (RSI) to generate trade signals. This strategy leverages the crossovers of the Tenkan-sen and Kijun-sen lines of the Ichimoku Cloud, along with RSI levels, to identify potential entry and exit points for long and short trades. This guide explains the strategy components, conditions, and how to use it effectively in your trading.
1. Strategy Parameters
User Inputs
Tenkan-sen Period (tenkanLength): Default value is 21. This is the period used to calculate the Tenkan-sen line (conversion line) of the Ichimoku Cloud.
Kijun-sen Period (kijunLength): Default value is 120. This is the period used to calculate the Kijun-sen line (base line) of the Ichimoku Cloud.
Senkou Span B Period (senkouBLength): Default value is 52. This is the period used to calculate the Senkou Span B line (leading span B) of the Ichimoku Cloud.
RSI Period (rsiLength): Default value is 14. This period is used to calculate the Relative Strength Index (RSI).
RSI Long Entry Level (rsiLongLevel): Default value is 60. This level indicates the minimum RSI value for a long entry signal.
RSI Short Entry Level (rsiShortLevel): Default value is 40. This level indicates the maximum RSI value for a short entry signal.
2. Strategy Components
Ichimoku Cloud
Tenkan-sen: A short-term trend indicator calculated as the simple moving average (SMA) of the highest high and the lowest low over the Tenkan-sen period.
Kijun-sen: A medium-term trend indicator calculated as the SMA of the highest high and the lowest low over the Kijun-sen period.
Senkou Span A: Calculated as the average of the Tenkan-sen and Kijun-sen, plotted 26 periods ahead.
Senkou Span B: Calculated as the SMA of the highest high and lowest low over the Senkou Span B period, plotted 26 periods ahead.
Chikou Span: The closing price plotted 26 periods behind.
Relative Strength Index (RSI)
RSI: A momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is used to identify overbought or oversold conditions.
3. Entry and Exit Conditions
Entry Conditions
Long Entry:
The Tenkan-sen crosses above the Kijun-sen (bullish crossover).
The RSI value is greater than or equal to the rsiLongLevel.
Short Entry:
The Tenkan-sen crosses below the Kijun-sen (bearish crossover).
The RSI value is less than or equal to the rsiShortLevel.
Exit Conditions
Exit Long Position: The Tenkan-sen crosses below the Kijun-sen.
Exit Short Position: The Tenkan-sen crosses above the Kijun-sen.
4. Visual Representation
Tenkan-sen Line: Plotted on the chart. The color changes based on its relation to the Kijun-sen (green if above, red if below) and is displayed with a line width of 2.
Kijun-sen Line: Plotted as a white line with a line width of 1.
Entry Arrows:
Long Entry: Displayed as a yellow triangle below the bar.
Short Entry: Displayed as a fuchsia triangle above the bar.
5. How to Use
Apply the Strategy: Apply the "Ichimoku Cloud Crosses_AIT" strategy to your chart in TradingView.
Configure Parameters: Adjust the strategy parameters (Tenkan-sen, Kijun-sen, Senkou Span B, and RSI settings) according to your trading preferences.
Interpret the Signals:
Long Entry: A yellow triangle appears below the bar when a long entry signal is generated.
Short Entry: A fuchsia triangle appears above the bar when a short entry signal is generated.
Monitor Open Positions: The strategy automatically exits positions based on the defined conditions.
Backtesting and Live Trading: Use the strategy for backtesting and live trading. Adjust risk management settings in the strategy properties as needed.
Conclusion
The "Ichimoku Cloud Crosses_AIT" strategy uses Ichimoku Cloud crossovers and RSI to generate trading signals. This strategy aims to capture market trends and potential reversals, providing a structured way to enter and exit trades. Make sure to backtest and optimize the strategy parameters to suit your trading style and market conditions before using it in a live trading environment.
TRADINGLibrary "TRADING"
This library is a client script for making a webhook signal formatted string to PoABOT server.
entry_message(password, percent, leverage, margin_mode, kis_number)
Create a entry message for POABOT
Parameters:
password (string) : (string) The password of your bot.
percent (float) : (float) The percent for entry based on your wallet balance.
leverage (int) : (int) The leverage of entry. If not set, your levereage doesn't change.
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
kis_number (int) : (int) The number of koreainvestment account. Default 1
Returns: (string) A json formatted string for webhook message.
order_message(password, percent, leverage, margin_mode, kis_number)
Create a order message for POABOT
Parameters:
password (string) : (string) The password of your bot.
percent (float) : (float) The percent for entry based on your wallet balance.
leverage (int) : (int) The leverage of entry. If not set, your levereage doesn't change.
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
kis_number (int) : (int) The number of koreainvestment account. Default 1
Returns: (string) A json formatted string for webhook message.
close_message(password, percent, margin_mode, kis_number)
Create a close message for POABOT
Parameters:
password (string) : (string) The password of your bot.
percent (float) : (float) The percent for close based on your wallet balance.
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
kis_number (int) : (int) The number of koreainvestment account. Default 1
Returns: (string) A json formatted string for webhook message.
exit_message(password, percent, margin_mode, kis_number)
Create a exit message for POABOT
Parameters:
password (string) : (string) The password of your bot.
percent (float) : (float) The percent for exit based on your wallet balance.
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
kis_number (int) : (int) The number of koreainvestment account. Default 1
Returns: (string) A json formatted string for webhook message.
manual_message(password, exchange, base, quote, side, qty, price, percent, leverage, margin_mode, kis_number, order_name)
Create a manual message for POABOT
Parameters:
password (string) : (string) The password of your bot.
exchange (string) : (string) The exchange
base (string) : (string) The base
quote (string) : (string) The quote of order message
side (string) : (string) The side of order messsage
qty (float) : (float) The qty of order message
price (float) : (float) The price of order message
percent (float) : (float) The percent for order based on your wallet balance.
leverage (int) : (int) The leverage of entry. If not set, your levereage doesn't change.
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
kis_number (int) : (int) The number of koreainvestment account.
order_name (string) : (string) The name of order message
Returns: (string) A json formatted string for webhook message.
in_trade(start_time, end_time, hide_trade_line)
Create a trade start line
Parameters:
start_time (int) : (int) The start of time.
end_time (int) : (int) The end of time.
hide_trade_line (bool) : (bool) if true, hide trade line. Default false.
Returns: (bool) Get bool for trade based on time range.
real_qty(qty, precision, leverage, contract_size, default_qty_type, default_qty_value)
Get exchange specific real qty
Parameters:
qty (float) : (float) qty
precision (float) : (float) precision
leverage (int) : (int) leverage
contract_size (float) : (float) contract_size
default_qty_type (string)
default_qty_value (float)
Returns: (float) exchange specific qty.
method set(this, password, start_time, end_time, leverage, initial_capital, default_qty_type, default_qty_value, margin_mode, contract_size, kis_number, entry_percent, close_percent, exit_percent, fixed_qty, fixed_cash, real, auto_alert_message, hide_trade_line)
Set bot object.
Namespace types: bot
Parameters:
this (bot)
password (string) : (string) password for poabot.
start_time (int) : (int) start_time timestamp.
end_time (int) : (int) end_time timestamp.
leverage (int) : (int) leverage.
initial_capital (float)
default_qty_type (string)
default_qty_value (float)
margin_mode (string) : (string) The margin mode for trade(only for OKX). "cross" or "isolated"
contract_size (float)
kis_number (int) : (int) kis_number for poabot.
entry_percent (float) : (float) entry_percent for poabot.
close_percent (float) : (float) close_percent for poabot.
exit_percent (float) : (float) exit_percent for poabot.
fixed_qty (float) : (float) fixed qty.
fixed_cash (float) : (float) fixed cash.
real (bool) : (bool) convert qty for exchange specific.
auto_alert_message (bool) : (bool) convert alert_message for exchange specific.
hide_trade_line (bool) : (bool) if true, Hide trade line. Default false.
Returns: (void)
method print(this, message)
Print message using log table.
Namespace types: bot
Parameters:
this (bot)
message (string)
Returns: (void)
method start_trade(this)
start trade using start_time and end_time
Namespace types: bot
Parameters:
this (bot)
Returns: (void)
method entry(this, id, direction, qty, limit, stop, oca_name, oca_type, comment, alert_message, when)
It is a command to enter market position. If an order with the same ID is already pending, it is possible to modify the order. If there is no order with the specified ID, a new order is placed. To deactivate an entry order, the command strategy.cancel or strategy.cancel_all should be used. In comparison to the function strategy.order, the function strategy.entry is affected by pyramiding and it can reverse market position correctly. If both 'limit' and 'stop' parameters are 'NaN', the order type is market order.
Namespace types: bot
Parameters:
this (bot)
id (string) : (string) A required parameter. The order identifier. It is possible to cancel or modify an order by referencing its identifier.
direction (string) : (string) A required parameter. Market position direction: 'strategy.long' is for long, 'strategy.short' is for short.
qty (float) : (float) An optional parameter. Number of contracts/shares/lots/units to trade. The default value is 'NaN'.
limit (float) : (float) An optional parameter. Limit price of the order. If it is specified, the order type is either 'limit', or 'stop-limit'. 'NaN' should be specified for any other order type.
stop (float) : (float) An optional parameter. Stop price of the order. If it is specified, the order type is either 'stop', or 'stop-limit'. 'NaN' should be specified for any other order type.
oca_name (string) : (string) An optional parameter. Name of the OCA group the order belongs to. If the order should not belong to any particular OCA group, there should be an empty string.
oca_type (string) : (string) An optional parameter. Type of the OCA group. The allowed values are: "strategy.oca.none" - the order should not belong to any particular OCA group; "strategy.oca.cancel" - the order should belong to an OCA group, where as soon as an order is filled, all other orders of the same group are cancelled; "strategy.oca.reduce" - the order should belong to an OCA group, where if X number of contracts of an order is filled, number of contracts for each other order of the same OCA group is decreased by X.
comment (string) : (string) An optional parameter. Additional notes on the order.
alert_message (string) : (string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
method order(this, id, direction, qty, limit, stop, oca_name, oca_type, comment, alert_message, when)
It is a command to place order. If an order with the same ID is already pending, it is possible to modify the order. If there is no order with the specified ID, a new order is placed. To deactivate order, the command strategy.cancel or strategy.cancel_all should be used. In comparison to the function strategy.entry, the function strategy.order is not affected by pyramiding. If both 'limit' and 'stop' parameters are 'NaN', the order type is market order.
Namespace types: bot
Parameters:
this (bot)
id (string) : (string) A required parameter. The order identifier. It is possible to cancel or modify an order by referencing its identifier.
direction (string) : (string) A required parameter. Market position direction: 'strategy.long' is for long, 'strategy.short' is for short.
qty (float) : (float) An optional parameter. Number of contracts/shares/lots/units to trade. The default value is 'NaN'.
limit (float) : (float) An optional parameter. Limit price of the order. If it is specified, the order type is either 'limit', or 'stop-limit'. 'NaN' should be specified for any other order type.
stop (float) : (float) An optional parameter. Stop price of the order. If it is specified, the order type is either 'stop', or 'stop-limit'. 'NaN' should be specified for any other order type.
oca_name (string) : (string) An optional parameter. Name of the OCA group the order belongs to. If the order should not belong to any particular OCA group, there should be an empty string.
oca_type (string) : (string) An optional parameter. Type of the OCA group. The allowed values are: "strategy.oca.none" - the order should not belong to any particular OCA group; "strategy.oca.cancel" - the order should belong to an OCA group, where as soon as an order is filled, all other orders of the same group are cancelled; "strategy.oca.reduce" - the order should belong to an OCA group, where if X number of contracts of an order is filled, number of contracts for each other order of the same OCA group is decreased by X.
comment (string) : (string) An optional parameter. Additional notes on the order.
alert_message (string) : (string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
method close_all(this, comment, alert_message, immediately, when)
Exits the current market position, making it flat.
Namespace types: bot
Parameters:
this (bot)
comment (string) : (string) An optional parameter. Additional notes on the order.
alert_message (string) : (string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
immediately (bool) : (bool) An optional parameter. If true, the closing order will be executed on the tick where it has been placed, ignoring the strategy parameters that restrict the order execution to the open of the next bar. The default is false.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
method cancel(this, id, when)
It is a command to cancel/deactivate pending orders by referencing their names, which were generated by the functions: strategy.order, strategy.entry and strategy.exit.
Namespace types: bot
Parameters:
this (bot)
id (string) : (string) A required parameter. The order identifier. It is possible to cancel an order by referencing its identifier.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
method cancel_all(this, when)
It is a command to cancel/deactivate all pending orders, which were generated by the functions: strategy.order, strategy.entry and strategy.exit.
Namespace types: bot
Parameters:
this (bot)
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
method close(this, id, comment, qty, qty_percent, alert_message, immediately, when)
It is a command to exit from the entry with the specified ID. If there were multiple entry orders with the same ID, all of them are exited at once. If there are no open entries with the specified ID by the moment the command is triggered, the command will not come into effect. The command uses market order. Every entry is closed by a separate market order.
Namespace types: bot
Parameters:
this (bot)
id (string) : (string) A required parameter. The order identifier. It is possible to close an order by referencing its identifier.
comment (string) : (string) An optional parameter. Additional notes on the order.
qty (float) : (float) An optional parameter. Number of contracts/shares/lots/units to exit a trade with. The default value is 'NaN'.
qty_percent (float) : (float) Defines the percentage (0-100) of the position to close. Its priority is lower than that of the 'qty' parameter. Optional. The default is 100.
alert_message (string) : (string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
immediately (bool) : (bool) An optional parameter. If true, the closing order will be executed on the tick where it has been placed, ignoring the strategy parameters that restrict the order execution to the open of the next bar. The default is false.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
ticks_to_price(ticks, from)
Converts ticks to a price offset from the supplied price or the average entry price.
Parameters:
ticks (float) : (float) Ticks to convert to a price.
from (float) : (float) A price that can be used to calculate from. Optional. The default value is `strategy.position_avg_price`.
Returns: (float) A price level that has a distance from the entry price equal to the specified number of ticks.
method exit(this, id, from_entry, qty, qty_percent, profit, limit, loss, stop, trail_price, trail_points, trail_offset, oca_name, comment, comment_profit, comment_loss, comment_trailing, alert_message, alert_profit, alert_loss, alert_trailing, when)
It is a command to exit either a specific entry, or whole market position. If an order with the same ID is already pending, it is possible to modify the order. If an entry order was not filled, but an exit order is generated, the exit order will wait till entry order is filled and then the exit order is placed. To deactivate an exit order, the command strategy.cancel or strategy.cancel_all should be used. If the function strategy.exit is called once, it exits a position only once. If you want to exit multiple times, the command strategy.exit should be called multiple times. If you use a stop loss and a trailing stop, their order type is 'stop', so only one of them is placed (the one that is supposed to be filled first). If all the following parameters 'profit', 'limit', 'loss', 'stop', 'trail_points', 'trail_offset' are 'NaN', the command will fail. To use market order to exit, the command strategy.close or strategy.close_all should be used.
Namespace types: bot
Parameters:
this (bot)
id (string) : (string) A required parameter. The order identifier. It is possible to cancel or modify an order by referencing its identifier.
from_entry (string) : (string) An optional parameter. The identifier of a specific entry order to exit from it. To exit all entries an empty string should be used. The default values is empty string.
qty (float) : (float) An optional parameter. Number of contracts/shares/lots/units to exit a trade with. The default value is 'NaN'.
qty_percent (float) : (float) Defines the percentage of (0-100) the position to close. Its priority is lower than that of the 'qty' parameter. Optional. The default is 100.
profit (float) : (float) An optional parameter. Profit target (specified in ticks). If it is specified, a limit order is placed to exit market position when the specified amount of profit (in ticks) is reached. The default value is 'NaN'.
limit (float) : (float) An optional parameter. Profit target (requires a specific price). If it is specified, a limit order is placed to exit market position at the specified price (or better). Priority of the parameter 'limit' is higher than priority of the parameter 'profit' ('limit' is used instead of 'profit', if its value is not 'NaN'). The default value is 'NaN'.
loss (float) : (float) An optional parameter. Stop loss (specified in ticks). If it is specified, a stop order is placed to exit market position when the specified amount of loss (in ticks) is reached. The default value is 'NaN'.
stop (float) : (float) An optional parameter. Stop loss (requires a specific price). If it is specified, a stop order is placed to exit market position at the specified price (or worse). Priority of the parameter 'stop' is higher than priority of the parameter 'loss' ('stop' is used instead of 'loss', if its value is not 'NaN'). The default value is 'NaN'.
trail_price (float) : (float) An optional parameter. Trailing stop activation level (requires a specific price). If it is specified, a trailing stop order will be placed when the specified price level is reached. The offset (in ticks) to determine initial price of the trailing stop order is specified in the 'trail_offset' parameter: X ticks lower than activation level to exit long position; X ticks higher than activation level to exit short position. The default value is 'NaN'.
trail_points (float) : (float) An optional parameter. Trailing stop activation level (profit specified in ticks). If it is specified, a trailing stop order will be placed when the calculated price level (specified amount of profit) is reached. The offset (in ticks) to determine initial price of the trailing stop order is specified in the 'trail_offset' parameter: X ticks lower than activation level to exit long position; X ticks higher than activation level to exit short position. The default value is 'NaN'.
trail_offset (float) : (float) An optional parameter. Trailing stop price (specified in ticks). The offset in ticks to determine initial price of the trailing stop order: X ticks lower than 'trail_price' or 'trail_points' to exit long position; X ticks higher than 'trail_price' or 'trail_points' to exit short position. The default value is 'NaN'.
oca_name (string) : (string) An optional parameter. Name of the OCA group (oca_type = strategy.oca.reduce) the profit target, the stop loss / the trailing stop orders belong to. If the name is not specified, it will be generated automatically.
comment (string) : (string) Additional notes on the order. If specified, displays near the order marker on the chart. Optional. The default is na.
comment_profit (string) : (string) Additional notes on the order if the exit was triggered by crossing `profit` or `limit` specifically. If specified, supercedes the `comment` parameter and displays near the order marker on the chart. Optional. The default is na.
comment_loss (string) : (string) Additional notes on the order if the exit was triggered by crossing `stop` or `loss` specifically. If specified, supercedes the `comment` parameter and displays near the order marker on the chart. Optional. The default is na.
comment_trailing (string) : (string) Additional notes on the order if the exit was triggered by crossing `trail_offset` specifically. If specified, supercedes the `comment` parameter and displays near the order marker on the chart. Optional. The default is na.
alert_message (string) : (string) Text that will replace the '{{strategy.order.alert_message}}' placeholder when one is used in the "Message" field of the "Create Alert" dialog. Optional. The default is na.
alert_profit (string) : (string) Text that will replace the '{{strategy.order.alert_message}}' placeholder when one is used in the "Message" field of the "Create Alert" dialog. Only replaces the text if the exit was triggered by crossing `profit` or `limit` specifically. Optional. The default is na.
alert_loss (string) : (string) Text that will replace the '{{strategy.order.alert_message}}' placeholder when one is used in the "Message" field of the "Create Alert" dialog. Only replaces the text if the exit was triggered by crossing `stop` or `loss` specifically. Optional. The default is na.
alert_trailing (string) : (string) Text that will replace the '{{strategy.order.alert_message}}' placeholder when one is used in the "Message" field of the "Create Alert" dialog. Only replaces the text if the exit was triggered by crossing `trail_offset` specifically. Optional. The default is na.
when (bool) : (bool) An optional parmeter. Condition, deprecated.
Returns: (void)
percent_to_ticks(percent, from)
Converts a percentage of the supplied price or the average entry price to ticks.
Parameters:
percent (float) : (float) The percentage of supplied price to convert to ticks. 50 is 50% of the entry price.
from (float) : (float) A price that can be used to calculate from. Optional. The default value is `strategy.position_avg_price`.
Returns: (float) A value in ticks.
percent_to_price(percent, from)
Converts a percentage of the supplied price or the average entry price to a price.
Parameters:
percent (float) : (float) The percentage of the supplied price to convert to price. 50 is 50% of the supplied price.
from (float) : (float) A price that can be used to calculate from. Optional. The default value is `strategy.position_avg_price`.
Returns: (float) A value in the symbol's quote currency (USD for BTCUSD).
bot
Fields:
password (series__string)
start_time (series__integer)
end_time (series__integer)
leverage (series__integer)
initial_capital (series__float)
default_qty_type (series__string)
default_qty_value (series__float)
margin_mode (series__string)
contract_size (series__float)
kis_number (series__integer)
entry_percent (series__float)
close_percent (series__float)
exit_percent (series__float)
log_table (series__table)
fixed_qty (series__float)
fixed_cash (series__float)
real (series__bool)
auto_alert_message (series__bool)
hide_trade_line (series__bool)
Price Pivots for NASDQ 100 StocksPrice Pivots for NASDQ 100 Stocks
What is this Indicator?
• This indicator calculates the price range a Stock can move in a Day.
Advantages of this Indicator
• This is a Leading indicator, not Dynamic or Repaint.
• Helps to identify the tight range of price movement.
• Can easily identify the Options strike price.
• Develops a discipline in placing Targets.
Disadvantages of this Indicator
• The indicator is specifically made for NASDQ 100 stocks. The levels won't work for other stocks.
• The indicator shows nothing for other indexes and stocks other than above mentioned.
• The data need to be entered manually.
Who to use?
Highly beneficial for Day Traders, it can be used for Swing and Positions as well.
What timeframe to use?
• Any timeframe.
• The highlighted levels in Red and Green will not show correct levels in 1 minute timeframe.
• 5min is recommended for Day Traders.
When to use?
• Wait for proper swing to form.
• Recommended to avoid 1st 1 hour or market open, that is 9.15am to 10.15 or 10.30am.
• Within this time a proper swing will be formed.
What are the Lines?
• The concept is the price will move from one pivot to another.
• Entry and Exit can be these levels as Reversal or Retracement.
Gray Lines:
• Every lines with price labels are the Strike Prices in the Option Chain.
• Price moves from 1 Strike Price level to another.
• The dashed lines are average levels of 2 Strike Prices.
Red & Green Lines:
• The Red and Green Lines will appear only after the first 1 hour.
• The levels are calculated based on the 1st 1 hour.
• Red Lines are important Resistance levels, these are strong Bearish reversal points. It is also a breakout level, this need to be figured out from the past levels, trend, percentage change and consolidation.
• Green Lines are important Support levels, these are strong Bullish reversal points. It is also a breakdown level, this need to be figured out from the past levels, trend, percentage change and consolidation.
What are the Labels?
• First Number: Price of that level.
• Numbers in (): Percentage change and Change of price from LTP (Last Traded Price) to that Level.
How to use?
Entry:
• Enter when price is closer to the Red or Green lines.
• Enter after considering previous Swing and Trend.
• Note the 50% of previous Swing.
• Enter Short when price reverse from each level.
• If 50% of swing and the pivot level is closer it can be a good entry.
Exit:
• Use the logic of Entry, each level can be a target.
• Exit when price is closer to the Red or Green lines.
Indicator Menu
Source
• Custom: Enter the price manually after choosing the Source as Custom to show the Pivots at that price.
• LTP: Pivot is calculated based on Last Traded Price.
• Day Open: Pivot is calculated based on current day opening price.
• PD Close: Pivot is calculated based on previous day closing price.
• PD HL2: Pivot is calculated based on previous day average of High and Low.
• PD HLC3: Pivot is calculated based on previous day average of High, Low and Close.
"Time (Vertical Lines)"
• This is a marker of every 1 hour.
• Usually major price movement happen between previous day last 1 hour to today first 1 hour.
• Two swings can happen between first 2 hour of current day.
• At the end of the day last 1 hour another important movement will happen.
• Usually rest of the time won't show any interesting movement.
To the Users
• Certain symbols may show the levels as a single line. For such symbols choose a different Source or Timeframe from the indicator menu.
• Please inform if any of the Symbol's price levels don't react to the pivots , include the Symbol a well.
• Also inform if you notice any wrong values, errors or abnormal behavior in the indicator.
• Feel free to suggest or adding new features and options.
General Tips
• It is good if Stock trend is same as that of Index trend.
• Lots of indicators creates lots of confusion.
• Keep the chart simple and clean.
• Buy Low and Sell High.
• Master averages or 50%.
• Previous Swing High and Swing Low are crucial.
Important Note
• Currently the levels are in testing stage.
• Eventually the levels of certain symbols will be corrected after each update and test.
Price Pivots for NSE Index & F&O StocksPrice Pivots for NSE Index & F&O Stocks
What is this Indicator?
• This indicator calculates the price range a Stock or Index can move in a Day, Week or Month.
Advantages of this Indicator
• This is a Leading indicator, not Dynamic or Repaint.
• Helps to identify the tight range of price movement.
• Can easily identify the Options strike price.
• The levels are more reliable and authentic than Gann Square of 9 Levels.
• Develops a discipline in placing Targets.
Disadvantages of this Indicator
• The indicator is specifically made for National Stock Exchange of India (NSE) listed index and stocks.
• The indicator is calculated only for index NIFTY, BANKNIFTY, FINNIFTY, MIDCPNIFTY and Stocks listed in Futures and Options.
• The indicator shows nothing for other indexes and stocks other than above mentioned.
• The data need to be entered manually.
• The data need to be updated manually when the F&O listed stocks are updated.
Who to use?
Highly beneficial for Day Traders, it can be used for Swing and Positions as well.
What timeframe to use?
• Any timeframe.
• The highlighted levels in Red and Green will not show correct levels in 1 minute timeframe.
• 5min is recommended for Day Traders.
When to use?
• Wait for proper swing to form.
• Recommended to avoid 1st 1 hour or market open, that is 9.15am to 10.15 or 10.30am.
• Within this time a proper swing will be formed.
How to use?
Entry
• Enter when the Price reach closer to the Blue line.
• Enter Long when the Price takes a pullback or breakout at the Red lines.
Exit
• Exit position when the Price reach closer to the Red lines in Long positions.
What are the Lines?
Gray Lines:
• Every lines with price labels are the Strike Prices in the Option Chain from NSE website.
• Price moves from 1 Strike Price level to another.
• The dashed lines are average levels of 2 Strike Prices.
Red & Green Lines:
• The Red and Green Lines will appear only after the first 1 hour.
• The levels are calculated based on the 1st 1 hour.
• Red Lines are important Resistance levels, these are strong Bearish reversal points. It is also a breakout level, this need to be figured out from the past levels, trend, percentage change and consolidation.
• Green Lines are important Support levels, these are strong Bullish reversal points. It is also a breakdown level, this need to be figured out from the past levels, trend, percentage change and consolidation.
What are the Labels?
• First Number: Price of that level.
• Numbers in (): Percentage change and Change of price from LTP(Last Traded Price) to that Level.
How to use?
Entry:
• Enter when price is closer to the Red or Green lines.
• Enter after considering previous Swing and Trend.
• Note the 50% of previous Swing.
• Enter Short when price reverse from each level.
• If 50% of swing and the pivot level is closer it can be a good entry.
Exit:
• Use the logic of Entry, each level can be a target.
• Exit when price is closer to the Red or Green lines.
Indicator Menu
Source
• Custom: Enter the price manually after choosing the Source as Custom to show the Pivots at that price.
• LTP: Pivot is calculated based on Last Traded Price.
• Day Open: Pivot is calculated based on current day opening price.
• PD Close: Pivot is calculated based on previous day closing price.
• PD HL2: Pivot is calculated based on previous day average of High and Low.
• PD HLC3: Pivot is calculated based on previous day average of High, Low and Close.
"Time (IST) (Vertical)"
• This is a marker of every 1 hour.
• Usually major price movement happen between previous day last 1 hour (2:15 pm) to today first 1 hour (10:15 pm).
• Two swings can happen between first 2 hour of current day.
• At the end of the day last 1 hour from 2.15 pm another important movement will happen.
• Usually rest of the time won't show any interesting movement.
To the Users
• Certain symbols may show the levels as a single line. For such symbols choose a different Source or Timeframe from the indicator menu.
• Please inform if any of the Symbol's price levels don't react to the pivots, include the Symbol a well.
• Also inform if you notice any wrong values, errors or abnormal behavior in the indicator.
• Feel free to suggest or adding new features and options.
General Tips
• It is good if Stock trend is same as that of NIFTY trend.
• Lots of indicators creates lots of confusion.
• Keep the chart simple and clean.
• Buy Low and Sell High.
• Master averages or 50%.
• Previous Swing High and Swing Low are crucial.
ColorSchemeLibrary "ColorScheme"
A color scheme generator.
init() Initiate the array data registry that will hold the color profile. Returns: tuple with 2 arrays (string array, color array)
check_registry_integrity(key_registry, color_registry) Checks the integrity of the registers.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data holder array.
Returns: void.
add(key_registry, color_registry, key, value) Add new (key, color) entry to the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
key : string, the unique key to reference the value.
value : color, the color value of the specified key.
Returns: void.
get_color(key_registry, color_registry, key) Get a (key, color) entry from the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
key : string, the unique key to reference the value.
Returns: void.
edit_key(key_registry, color_registry, key, new_key) Edit a (key, color) entry in the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
key : string, the unique key to reference the value.
new_key : string, the unique key to reference the value.
Returns: void.
edit_color(key_registry, color_registry, key, new_value) Edit a (key, color) entry in the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
key : string, the unique key to reference the value.
new_value : color, the color value of the specified key.
Returns: void.
delete(key_registry, color_registry, key) Delete a (key, color) entry from the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
key : string, the unique key to reference the value.
Returns: void.
delete_all(key_registry, color_registry) Delete all (key, color) entrys from the registry.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
Returns: void.
model(index) Enumerate models available to profile colors.
Parameters:
index : int, index of model. (1:'monochromatic', 2:'analog', 3:'triadic', 4:'tetradic', 5:'square', anything else:'monochromatic')
Returns: string.
generate_scheme(key_registry, color_registry, primary, model) Generate a multi color scheme.
Parameters:
key_registry : string array, key data holder array.
color_registry : color array, color value data array.
primary : color, the origin color to base the profile.
model : string, default='monochromatic', options=('monochromatic', 'triadic near', 'triadic far', 'tetradic')
Returns: void.
CCI-RSI MR Indicators:
Bollinger Bands (20 period, 2σ)
RSI (14 period) and Simple moving average of RSI (5 period)
CCI (20 period)
SMA (5 period)
Entry Conditions:
Buy when:
Swing low (5) should be lower than the highest of lower BB (3 periods)
Both RSI crossover RSI_5 and CCI crossover -100 should have happened within last 3 candles (including the current candle)
Once all the above conditions are met, the close should be higher than SMA (5) within the next 3 candles
After condition 3 is satisfied, we enter the trade at next candle’s open
Stop loss will be at 1 tick lower than previous swing low
Sell when:
Swing high (5) should be higher than the lowest of upper BB (3 periods)
Both RSI crossunder RSI_5 and CCI crossunder 100 should have happened within last 3 candles (including the current candle)
Once all the above conditions are met, the close should be lower than SMA (5) within the next 3 candles
After condition 3 is satisfied, we enter the trade at next candle’s open
Stop loss will be at 1 tick higher than previous swing high
Exit Conditions:
Since it’s mean reversion strategy we’ll be having only 2 target exits with a trailing stop loss after target price 1 is achieved.
Target exit price 1 & 2 are decided based on the risk ‘R’ for each trade
Depending on the instrument and time frame a trailing stop loss of 0.5R or 1R has opted.
A stop limit is placed @Entry_price +- 2*ATR(20) to offset the risk of losing significantly more than 1xR in a trade
Ichimoku + RSI + MACD Strategy1. Relative Strength Index (RSI)
Overview:
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions in a market.
How to Use with Ichimoku:
Long Entry: Look for RSI to be above 30 (indicating it is not oversold) when the price is above the Ichimoku Cloud.
Short Entry: Look for RSI to be below 70 (indicating it is not overbought) when the price is below the Ichimoku Cloud.
2. Moving Average Convergence Divergence (MACD)
Overview:
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. It consists of the MACD line, signal line, and histogram.
How to Use with Ichimoku:
Long Entry: Enter a long position when the MACD line crosses above the signal line while the price is above the Ichimoku Cloud.
Short Entry: Enter a short position when the MACD line crosses below the signal line while the price is below the Ichimoku Cloud.
Combined Strategy Example
Here’s a brief outline of how to structure a trading strategy using Ichimoku, RSI, and MACD:
Long Entry Conditions:
Price is above the Ichimoku Cloud.
RSI is above 30.
MACD line crosses above the signal line.
Short Entry Conditions:
Price is below the Ichimoku Cloud.
RSI is below 70.
MACD line crosses below the signal line.
Exit Conditions:
Exit long when MACD line crosses below the signal line.
Exit short when MACD line crosses above the signal line.
Monthly Day Long Strategy with VIX and Risk ManagementThis trading strategy is designed to open long positions on a specific day of the month, with the conditions for entry and exit based on the VIX index and additional risk management techniques. The strategy includes stop-loss and take-profit features to manage risk and lock in profits.
Inputs:
Entry Day of the Month (entry_day): Specifies which day of the month to consider for initiating a trade. The default value is the 27th.
Hold Duration (Days) (hold_duration_days): Defines how many days to hold the position after opening. The default value is 4 days.
VIX Threshold (vix_threshold): Sets the maximum acceptable value for the VIX index to consider an entry. If the VIX is below this threshold, it signals a potential trade. The default value is 20.0.
Stop Loss (%) (stop_loss_percentage): Determines the percentage below the entry price where the stop-loss will be triggered. The default value is 2.0%.
Take Profit (%) (take_profit_percentage): Sets the percentage above the entry price where the take-profit will be triggered. The default value is 5.0%.
Functions:
next_weekday(date): Adjusts the entry date to the next Monday if it falls on a weekend (Saturday or Sunday). This ensures trades do not occur on non-trading days.
Logic:
Entry Conditions:
Date Check: Opens a long position if the current date matches the adjusted entry date (the 27th or the next Monday if the 27th falls on a weekend).
VIX Filter: The VIX index value must be below the specified threshold (e.g., 20.0) to consider an entry.
Exit Conditions:
Time-Based Exit: Closes the position after the hold duration of 4 days.
Stop-Loss: Automatically closes the position if the price drops to a level that is a specified percentage below the entry price (e.g., 2.0%).
Take-Profit: Closes the position if the price rises to a level that is a specified percentage above the entry price (e.g., 5.0%).
Plots:
VIX Plot: Displays the VIX index on the chart for visual reference.
VIX Threshold Line: A horizontal line representing the VIX threshold value.
Summary:
The strategy aims to take advantage of specific entry days while filtering trades based on VIX levels to ensure market conditions are favorable. Risk management is enhanced through stop-loss and take-profit settings, which help in controlling potential losses and securing profits. The strategy ensures trades are only made on trading days and not on weekends, adjusting automatically to the next Monday if needed.
ChatGPT kann Fehler machen. Überprüfe wichtige Informationen.
Triple MA HTF strategy - Dynamic SmoothingThe triple MA strategy is a simple but effective method to trade the trend. The advantage of this script over the existing triple MA strategies is that the user can open a lower time frame chart and select higher time frame inputs for different MA types mainting the visibility on the chart. The dynamic smoothing code makes sure the HTF trendlines are not jagged, but a fluid line visiable on the lower time frame chart. The script comes with a MA crossover and crossunder strategy explained below.
Moving Averages (MA) Crossover for Entry:
Long Entry: A long entry signal is triggered when the moving average line 1 crosses above the moving average line 2. This crossover indicates a potential shift in market sentiment towards the upside. However, to validate this signal, the strategy checks if the moving average 3 on a higher time frame (eg. 4 hour) is in an upward trend. This additional filter ensures that the trade aligns with the prevailing trend on a broader time scale, increasing the probability of success.
Short Entry: Conversely, a short entry signal occurs when the moving average line 1 crosses below the moving average line 2. This crossover suggests a possible downturn in market momentum. However, for a short trade to be confirmed, the strategy verifies that the moving average 3 on the higher time frame is in a downward trend. This confirmation ensures that the trade is in harmony with the overarching market direction.
Exit from Long Position: The strategy triggers an exit signal from a long position when the moving average line 1 crosses below the moving average line 2. This crossover indicates a potential reversal in the market trend, prompting the trader to close their long position and take profits or minimize losses.
Exit from Short Position: Similarly, an exit signal from a short position occurs when the moving average line 1 crosses above the moving average line 2. This crossover suggests a potential shift in market sentiment towards the upside, prompting the trader to exit their short position and manage their risk accordingly.
Features of the script
This Triple MA Strategy is basically the HTF Trend Filter displayed 3 times on the chart. For more infomation on how the MA with dynamic smoothing is calculated I recommend reading the following script:
For risk management I included a simple script to opt for % of eauity or # of contracts of in the instrument. For explanation on how the risk management settings work I refer to my ealier published script:
The strategy is a simplified example for setting up an entry and exit logic based on multiple moving avarages. Hence the script is meant for educational purposes only.
ORB Algo | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ORB Algo indicator! ORB stands for "Opening Range Breakout" which is a common trading strategy. The indicator can analyze the market trend in the current session and give "Buy / Sell", "Take Profit" and "Stop Loss" signals. For more information about the analyzing process of the indicator, you can read "How Does It Work ?" section of the description.
Features of the new ORB Algo indicator :
Buy & Sell Signals
Up To 3 Take Profit Signals
Stop-Loss Signals
Alerts for Buy / Sell, Take-Profit and Stop-Loss
Customizable Algoritm
Session Dashboard
Backtesting Dashboard
📌 HOW DOES IT WORK ?
This indicator works best in 1-minute timeframe. The idea is that the trend of the current session can be forecasted by analyzing the market for a while after the session starts. However, each market has it's own dynamics and the algorithm will need fine-tuning to get the best performance possible. So, we've implemented a "Backtesting Dashboard" that shows the past performance of the algorithm in the current ticker with your current settings. Always keep in mind that past performance does not guarantee future results.
Here are the steps of the algorithm explained briefly :
1. The algorithm follows and analyzes the first 30 minutes (can be adjusted) of the session.
2. Then, algorithm checks for breakouts of the opening range's high or low.
3. If a breakout happens in a bullish or a bearish direction, the algorithm will now check for retests of the breakout. Depending on the sensitivity setting, there must be 0 / 1 / 2 / 3 failed retests for the breakout to be considered as reliable.
4. If the breakout is reliable, the algorithm will give an entry signal.
5. After the position entry, algorithm will now wait for Take-Profit or Stop-Loss zones and signal if any of them occur.
If you wonder how does the indicator find Take-Profit & Stop-Loss zones, you can check the "Settings" section of the description.
🚩UNIQUENESS
While there are indicators that show the opening range of the session, they come short with features like indicating breakouts, entries, and Take-Profit & Stop-Loss zones. We are also aware of that different stock markets have different dynamics, and tuning the algorithm for different markets is really important for better results, so we decided to make the algorithm fully customizable. Besides all that, our indicator contains a detailed backtesting dashboard, so you can see past performance of the algorithm in the current ticker. While past performance does not yield any guarantee for future results, we believe that a backtesting dashboard is necessary for tuning the algorithm. Another strength of this indicator is that there are multiple options for detection of Take-Profit and Stop-Loss zones, which the trader can select one of their liking.
⚙️SETTINGS
Keep in mind that best chart timeframe for this indicator to work is the 1-minute timeframe.
TP = Take-Profit
SL = Stop-Loss
EMA = Exponential Moving Average
OR = Opening Range
ATR = Average True Range
1. Algorithm
ORB Timeframe -> This setting determines the timeframe that the algorithm will analyze the market after a new session begins before giving any signals. It's important to experiment with this setting and find the best option that suits the current ticker for the best performance. More volatile stocks will often require this setting to be larger, while more stabilized stocks may have this setting shorter.
Sensitivity -> This setting determines how much failed retests are needed to take a position entry. Higher senstivity means that less retests are needed to consider the breakout as reliable. If you think that the current ticker makes strong movements in a bullish & bearish direction after a breakout, you should set this setting higher. If you think the opposite, meaning that the ticker does not decide the trend right after a breakout, this setting show be lower.
(High = 0 Retests, Medium = 1 Retest, Low = 2 Retests, Lowest = 3 Retests)
Breakout Condition -> The condition for the algorithm to detect breakouts.
Close = Bar needs to close higher than the OR High Line in a bullish breakout, or lower than the OR Low Line in a bearish breakout. EMA = The EMA of the bar must be higher / lower than OR Lines instead of the close price.
TP Method -> The method for the algorithm to use when determining TP zones.
Dynamic = This TP method essentially tries to find the bar that price starts declining the current trend and going to the other direction, and puts a TP zone there. To achieve this, it uses an EMA line, and when the close price of a bar crosses the EMA line, It's a TP spot.
ATR = In this TP method, instead of a dynamic approach the TP zones are pre-determined using the ATR of the entry bar. This option is generally for traders who just want to know their TP spots beforehand while trading. Selecting this option will also show TP zones at the ORB Dashboard.
"Dynamic" option generally performs better, while the "ATR" method is safer to use.
EMA Length -> This setting determines the length of the EMA line used in "Dynamic TP method" and "EMA Breakout Condition". This is completely up to the trader's choice, though the default option should generally perform well. You might want to experiment with this setting and find the optimal length for the current ticker.
Stop-Loss -> Algorithm will place the Stop-Loss zone using setting.
Safer = The SL zone will be placed closer to the OR High for a bullish entry, and closer to the OR Low for a bearish entry.
Balanced = The SL zone will be placed in the center of OR High & OR Low
Risky = The SL zone will be placed closer to the OR Low for a bullish entry, and closer to the OR High for a bearish entry.
Adaptive SL -> This option only takes effect if the first TP zone is hit.
Enabled = After the 1st TP zone is hit, the SL zone will be moved to the entry price, essentially making the position risk-free.
Disabled = The SL zone will never change.
2. ORB Dashboard
ORB Dashboard shows the information about the current session.
3. ORB Backtesting
ORB Backtesting Dashboard allows you to see past performance of the algorithm in the current ticker with current settings.
Total amount of days that can be backtested depends on your TV subscription.
Backtesting Exit Ratios -> You can select how much of percent your entry will be closed at any TP zone while backtesting. For example, %90, %5, %5 means that %90 of the position will be closed at the first TP zone, %5 of it will be closed at the 2nd TP zone, and %5 of it will be closed at the last TP zone.
PlurexSignalStrategyLibrary "PlurexSignalStrategy"
Provides functions that wrap the built in TradingView strategy functions so you can seemlessly integrate with Plurex Signal automation.
NOTE: Be sure to:
- set your strategy default_qty_value to the default entry percentage of your signal
- set your strategy default_qty_type to strategy.percent_of_equity
- set your strategy pyramiding to some value greater than 1 or something appropriate to your strategy in order to have multiple entries.
long(secret, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
longAndFixedStopLoss(secret, stop, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal stop loss for full open position
Parameters:
secret : The secret for your Signal on plurex
stop : The trigger price for the stop loss. See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
longAndTrailingStopLoss(secret, trail_offset, trail_price, trail_points, budgetPercentage, priceLimit, marketOverride)
Open a new long entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal trailing stop loss for full open position. You must set one of trail_price or trail_points.
Parameters:
secret : The secret for your Signal on plurex
trail_offset : See strategy.exit documentation
trail_price : See strategy.exit documentation
trail_points : See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
short(secret, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
shortAndFixedStopLoss(secret, stop, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal stop loss for full open position
Parameters:
secret : The secret for your Signal on plurex
stop : The trigger price for the stop loss. See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
shortAndTrailingStopLoss(secret, trail_offset, trail_price, trail_points, budgetPercentage, priceLimit, marketOverride)
Open a new short entry. Wraps strategy function and sends plurex message as an alert. Also sets a gobal trailing stop loss for full open position. You must set one of trail_price or trail_points.
Parameters:
secret : The secret for your Signal on plurex
trail_offset : See strategy.exit documentation
trail_price : See strategy.exit documentation
trail_points : See strategy.exit documentation
budgetPercentage : Optional, The percentage of budget to use in the entry.
priceLimit : Optional, The worst price to accept for the entry.
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeAll(secret, marketOverride)
Close all positions. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLongs(secret, marketOverride)
close all longs. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeShorts(secret, marketOverride)
close all shorts. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastLong(secret, marketOverride)
Close last long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeLastShort(secret, marketOverride)
Close last short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstLong(secret, marketOverride)
Close first long entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
closeFirstShort(secret, marketOverride)
Close first short entry. Wraps strategy function and sends plurex message as an alert.
Parameters:
secret : The secret for your Signal on plurex
marketOverride : Optional, defaults to the syminfo for the ticker. Use the `plurexMarket` function to build your own.
Simple and Profitable Scalping Strategy (ForexSignals TV)Strategy is based on the "SIMPLE and PROFITABLE Forex Scalping Strategy" taken from YouTube channel ForexSignals TV.
See video for a detailed explaination of the whole strategy.
I'm not entirely happy with the performance of this strategy yet however I do believe it has potential as the concept makes a lot of sense.
I'm open to any ideas people have on how it could be improved.
Strategy incorporates the following features:
Risk management:
Configurable X% loss per stop (default to 1%)
Configurable R:R ratio
Trade entry:
Based on stratgey conditions outlined below
Trade exit:
Based on stratgey conditions outlined below
Backtesting:
Configurable backtesting range by date
Trade drawings:
Each entry condition indicator can be turned on and off
TP/SL boxes drawn for all trades. Can be turned on and off
Trade exit information labels. Can be turned on and off
NOTE: Trade drawings will only be applicable when using overlay strategies
Debugging:
Includes section with useful debugging techniques
Strategy conditions
Trade entry:
LONG
C1: On higher timeframe trend EMAs, Fast EMA must be above Slow EMA
C2: On higher timeframe trend EMAs, price must be above Fast EMA
C3: On current timeframe entry EMAs, Fast EMA must be above Medium EMA and Medium EMA must be above Slow EMA
C4: On current timeframe entry EMAs, all 3 EMA lines must have fanned out in upward direction for previous X candles (configurable)
C5: On current timeframe entry EMAs, previous candle must have closed above and not touched any EMA lines
C6: On current timeframe entry EMAs, current candle must have pulled back to touch the EMA line(s)
C7: Price must break through the high of the last X candles (plus price buffer) to trigger entry (stop order entry)
SHORT
C1: On higher timeframe trend EMAs, Fast EMA must be below Slow EMA
C2: On higher timeframe trend EMAs, price must be below Fast EMA
C3: On current timeframe entry EMAs, Fast EMA must be below Medium EMA and Medium EMA must be below Slow EMA
C4: On current timeframe entry EMAs, all 3 EMA lines must have fanned out in downward direction for previous X candles (configurable)
C5: On current timeframe entry EMAs, previous candle must have closed above and not touched any EMA lines
C6: On current timeframe entry EMAs, current candle must have pulled back to touch the EMA line(s)
C7: Price must break through the low of the last X candles (plus price buffer) to trigger entry (stop order entry)
Trade entry:
Calculated position size based on risk tolerance
Entry price is a stop order set just above (buffer configurable) the recent swing high/low (long/short)
Trade exit:
Stop Loss is set just below (buffer configurable) trigger candle's low/high (long/short)
Take Profit calculated from Stop Loss using R:R ratio
Credits
"SIMPLE and PROFITABLE Forex Scalping Strategy" taken from YouTube channel ForexSignals TV
[MT Trader] Backtest template w/ Supertrend Strategy---EN: In this strategy template you will find some functions already pre-programmed to be used in your strategies to speed up the programming process, among them we can highlight the default stop loss and take profit functions, which will help to set easily and quickly, defining the price range in which we want to prevent large losses or protect our profits from unexpected market movements.
🔴 Stop Loss: Among the functions of the stop loss are the 4 most known, first we have the fixed percentage range (%) and price ($), when the price reaches this fixed price will limit the losses of the operation avoiding larger losses, then we have the average true range (ATR), a moving average of true range and X period that can give us good reference points to place our stop loss, finally the last point higher or lower is the most used by traders to place their stop loss.
In addition, the price range between the entry and stop loss can be converted into a trailing stop loss.
🟢 Take Profit: We have 3 options for take profit, just like stop loss, the fixed range of percentage(%) and price($), are available, in addition to this we have the 1:# ratio option, which multiplies by X number the range between the entry and stop loss to use it as take profit, perfect for strategies that use ATR or last high/low point for their strategy.
📈 Heikin Ashi Entrys: The heikin ashi entries are trades that are calculated based on heikin ashi candles but their price is executed in Japanese candles, thus avoiding the false results that occur in heikin candlestick charts, making that in certain cases better results are obtained in the strategies that are executed with this option compared to Japanese candlesticks.
📊 Dashboard: A more visual and organized way to see the results and data needed for our strategy.
Feel free to use this template to program your own strategies, if you find bugs or want to request a new feature let me know in the comments or through my telegram @hvert_mt
__________________________________________________________________________________________________________________________________________________
---ES: En esta plantilla de estrategia podrás encontrar algunas funciones ya pre-programadas para ser usadas en tus estrategias para acelerar procesos de programación, entre ellas podemos destacar las funciones por defecto de stop loss y take profit, que ayudaran a establecer de manera fácil y rápida, definiendo los rango de precio en los que queremos prevenirnos de perdidas grandes o proteger nuestras ganancias de movimientos inesperados del mercado.
🔴 Stop Loss: Entre las funciones del stop loss están las 4 más conocidas, en primer lugar tenemos el rango de porcentaje fijo(%) y el precio($), cuando el precio alcance este precio fijo se limitaran las perdidas de la operación evitando perdidas mas grandes, después tenemos el promedio de rango verdadero(ATR), una media móvil del rango verdadero y X periodo que nos puede dar buenos puntos de referencia para colocar nuestro stop loss, por ultimo el ultimo punto mas alto o mas bajo es de los mas usados por los traders para colocar su stop loss.
Adicional a esto, el rango de precio entre la entrada y el stop loss se puede convertir en un trailing stop loss.
🟢 Take Profit: Tenemos 3 opciones para take profit, al igual que en el stop loss, el rango fijo de porcentaje(%) y precio($) se encuentran disponibles, adicional a esto tenemos la opción de ratio 1:#, que multiplica por X numero el rango entre la entrada y el stop loss para usarlo como take profit, perfecto para estrategias que usen ATR o ultimo punto alto/bajo.
📈 Entradas Heikin Ashi: Las entradas Heikin Ashi son trades que son calculados en base a las velas Aeikin Ashi pero su precio esta ejecutado a velas japonesas, evitando así los falsos resultados que se producen en graficas de velas Heikin, esto haciendo que en ciertos casos se obtengan mejores resultados en las estrategias que son ejecutadas con esta opción en comparación con las velas japonesas.
📊 Panel de Control: Una manera mas visual y organizada de ver los resultados y datos necesarios de nuestra estrategia.
Siéntete libre de usar esta plantilla para programar tus propias estrategias, si encuentras errores o quieres solicitar una nueva función házmelo saber en los comentarios o a través de mi Telegram: @hvert_mt
Rainbow Oscillator The Rainbow Oscillator is a technical indicator that shows prices in overbought or oversold areas. That allows you to catch the price reversal point.
---------------
FEATURES
---------------
.:: Dynamic levels ::.
The indicator levels are divided into several zones, which have a fibonacci ratio. Zones determine the overbought/oversold level. Blue and green level zones are better for buying, red and orange for selling. Dynamic levels are used as replacements for classic levels such as -100 and 100 for the CCI indicator or 30 and 70 for the RSI indicator. Dynamic levels work much better than static levels, as they are more adaptive to the current market situation.
.:: Composite oscillator (3 in 1) ::.
The main signal line of the indicator includes all three oscillators RSI, CCI, Stoch in different ratios. In the settings, you can change the proportions or completely remove one of the oscillators by setting its weight to 0
.:: CCI + RSI + Stoch ratio setting ::.
Each of the oscillators has its own weight in the calculation formula: w2 * cci ( + w1 * ( rsi - 50) + (1 - w2 - w1) * ( stoch - 50), this allows you to create the resulting oscillator from all indicators, depending on the weight of each of them. Each weight value must be between 0 and 1 so that the sum of all weights does not exceed 1.
.:: Smoothing levels and lines of the oscillator ::.
Smoothing the oscillator readings allows you to filter out the noise and get more accurate data. Level offset allows you to customize the support for inputs.
.:: Market Flat ::.
Dynamic creation of levels allows you to find in the price reversal zone, even when the price is in a flat
.:: Sources ::.
You can change the data source for the indicator to the number of longs and shorts for the selected asset. For example, BTCUSDLONGS / BTCUSDSHORTS is perfect for Bitcoin, then the oscillator will work on this data and will not use the quote price.
.:: Trend Detection ::.
The main line of the oscillator has 2 colors - green and red. Red means downtrend, green means uptrend. Trend reversal points are most often found in overbought and oversold zones.
.:: Alerts ::.
Alerts inside for next events: Buy (blue point) Sell (red point) and TrendReversal (change line color)
----------------
TRADING
—-------------
There are several possible entry points for the indicator, let's consider them all.
1) Trend reversal.
Long entry: The indicator line is in the green zone below 0 (oversold), while the line changes color from red (downward) to green (upward)
Short entry: The indicator line is in the red zone above the 0 (overbought) mark, while the line changes color from green to red.
2) Red and blue dots.
Long entry: Blue dot
Short Entry: Red Dot
I prefer to use the first trading method.
----------------
SETTINGS
----------------
.:: Trend Filter (checkbox) ::.
Use trend confirmation for red/blue dots. When enabled, the blue dot requires an uptrend, red dot requires downtrend confirmation before appearing.
.:: Use long/shorts (checkbox) ::.
Change formula to use longs and shorts positions as data source (instead of quote price)
.:: RSI weight / CCI weight / Stoch weight ::.
Weight control coefficients for RSI and CCI indicators, respectively. When you set RSI Weight = 0, equalize the combo of CCI and Stoch , when RSI Weight is zero and CCI Weight is equal to the oscillator value will be plotted
only from Stoch . Intermediate values have a high degree of measurement of each of the three oscillators in percentage terms from 0 to 100. The calculation uses the formula: w2 * cci ( + w1 * ( rsi - 50) + (1 - w2 - w1) * ( stoch - 50),
where w1 is RSI Weight and w2 is CCI Weight, Stoch weight is calculated on the fly as (1 - w2 - w1), so the sum of w1 + w2 should not exceed 1, in this case Stoch will work as opposed to CCI and RSI .
.:: Oscillograph fast and slow periods ::.
The fast period is the period for the moving average used to smooth CCI, RSI and Stoch. The slow period is the same. The fast period must always be less than the slow period.
.:: Oscillograph samples period::.
The period of smoothing the total values of indicators - creates a fast and slow main lines of the oscillator.
.:: Oscillograph samples count::.
How many times smoothing applied to source data.
.:: Oscillator samples type ::.
Smoothing line type e.g. EMA, SMA, RMA …
.:: Level period ::.
Periodically moving averages used to form the levels (zone) of the Rainbow Oscillator indicator
.:: Level offset ::.
Additional setting for shifting levels from zero points. Can be useful for absorbing levels and filtering input signals. The default is 0.
.:: Level redundant ::.
It characterizes the severity of the state at each iteration of the level of the disease. If set to 1 - the levels will not decrease when the oscillator values fall. If it has a value of 0.99 - the levels are reduced by 0.01
each has an oscillator in 1% of cases and is pressed to 0 by more aggressive ones.
.:: Level smooth samples ::.
setting allows you to set the number of strokes per level. Measuring the number of averages with the definition of the type of moving averages
.:: Level MA Type ::.
Type of moving average, average for the formation of a smoothing overbought and oversold zone
Trending Bar SRTrending Bar SR is a simple script define a Bar called "Trending Bar".
Depend on direction of Trending Bar, if Trending Bar is UpTrend then this indicator plot Bar's Low Price as Support and if Trending Bar is DownTrend then it plot Bar's High Price as Resistance.
Beside, this indicaor also plot 4 levels retracement of Trending Bar for trading.
1. Define Trending Bar
1.1 Uptrend Bar
+ Close Price higher than previous High Price
+ Body greater than sum of shadows (up and down)
+ Color: A green dot is plotted at bottom chart.
1.2 Downtrend Bar
+ Close Price lower than previous Low Price
+ Body greater than sum of shadows (up and down)
+ Color: A red dot is plotted at bottom chart.
2. Retracement Level
+ Trending Bar Retracement 0.5 is called Equerium.
+ Trending Bar Retracement 0.618 is called Perfect Entry.
+ Trending Bar Retracement 0.705 is called Optimal Entry.
+ Trending Bar Retracement 0.79 is called Max Entry.
3. Trading
+ When Price crossed Equerium, consider open position at Perfect Entry, Optimal Entry with stoploss place at Max Entry.
+ If place order at Max Entry, stoploss can place at Support or Resistance.
Double SupertrendThis strategy is based on a custom indicator that was created based on the Supertrend indicator. At its core, there are always 2 super trend indicators with different factors to reduce market noise (false signals).
The strategy/indicator has some parameters to improve the signals and filters.
TECHNICAL ANALYSIS
☑ Show Indicators
This option will enable/disable the Supertrend indicators on the chart.
☑ Length
The length will be used on the Supertrend Indicator to calculate its values.
☑ Dev Fast
The fast deviation or factor from one of the super trend indicators. This will be the leading indicator for entry signals, as well as for the exit signals.
☑ Dev Slow
The slow deviation or factor from one of the super trend indicators. This will be the confirmation indicator for entry and exit signals.
☑ Exit Type
It's possible to select from 4 options for the exit signals. Exit signals always take profit target.
☑ ⥹ Reversals
This option will make the strategy/indicator calculate the exit signals based on the difference between the given period's highest and lowest candle value (see Period on this list). It's displayed on the chart with the cross. As it's possible to verify in the image below, there are multiple exit spots for every entry.
☑ ⥹ ATR
Using ATR as a base indicator for exit signals will make the strategy/indicator place limit/stop orders. Candle High + ATR for longs, Candle Low - ATR for shorts. The strategy will show the ATR level for take profit and stick with it until the next signal. This way, the take profit value remains based on the candle of the entry signal.
☑ ⥹ Fast Supertrend
With this option selected, the exit signals will be based on the Fast Supertsignal value, mirrored to make a profit.
☑ ⥹ Slow Supertrend
With this option selected, the exit signals will be based on the Slow Supertsignal value, which is mirrored to take profit.
☑ Period
This will represent the number of candles used on the exit signals when Reversals is selected as Exit Type. It's also used to calculate the gradient used on the Fills and Supertrend signals.
☑ Multiplier
It's used on the take profit when the ATR option is selected on the Exit Type.
STRATEGY
☑ Use The Strategy
This will enable/disable the strategy to show the trades calculations.
☑ Show Use Long/Short Entries
Option to make the strategy show/use Long or Short signals. Available only if Use The Strategy is enabled
☑ Show Use Exit Long/Short
Option to make the strategy show/use Exit Long or Short signals (valid when Reversals option is selected on the Exit Type). Available only if Use The Strategy is enabled
☑ Show Use Add Long/Short
Option to make the strategy show/use Add Long or Short signals. With this option enabled, the strategy will place multiple trades in the same direction, almost the same concept as a pyramiding parameter. It's based on the Fast Supersignal when the candle fails to cross and reverses. Available only if Use The Strategy is enabled
☑ Trades Date Start/End
The date range that the strategy will check the market data and make the trades
HOW TO USE
It's very straightforward. A long signal will appear as a green arrow with a text Long below it. A short signal will appear as a red arrow with a text Short above it. It's ideal to wait for the candle to finish to validate the signal.
The exit signals are optional but give a good idea of the configuration used when backtesting. Each market and timeframe will have its own configuration for the best results. On average, sticking to ATR as an exit signal will have less risk than the other options.
☑ Entry Signals
Follow the arrows with Long/Short texts on them. Wait for the signal candle to close to validate the entry.
☑ Exit Signals
Use them to close your position or to trail stop your orders and maximize profits. Select the exit type suitable for each timeframe and market
☑ Add Entries
It's possible to increase the position following the add margin/contracts based on the Add signals. Not mandatory, but may work as reentries or late entries using the same signal.
☑ What about Stop Loss?
The stop-loss levels were not included as a separated signal because it's already in the chart. There are some possible ideas for the stop loss:
☑⥹ Candle High/Low (2nd recommend option)
When it's a Long signal from the entry signal candle, the stop loss can be the Low value of the same candle. Very tight stop loss in some cases, depending on the candle range
☑⥹ Local Top/Bottom
Selecting the local top/bottom as stop loss will give the strategy more room for false breakouts or reversals, keeping the trade open and minimizing noises. Increases the risk
☑⥹ Fast Supertrend (1st recommend option)
The fast supertrend can be used as stop-loss as well. making it a moving level and working close to trail stop management
☑⥹ Fixed Percentage
It's possible to use a fixed risk percentage for the trades, making the risk easier to control and project. Since the market volatility is not fixed, this may affect the accuracy of the trades
☑⥹ Based on the ATR (3rd recommend option)
When the exit type option ATR is selected, it will display the take profit level for that entry. Just mirror that value and put it as stop-loss, or multiply that amount by 1.5 to have more room for market noise.
EXAMPLE CONFIGURATIONS
Here are some configuration ideas for some markets (all of them are from crypto, especially futures markets)
BTCUSDT 15min - Default configuration
BTCUSDT 1h - Length 10 | Dev Fast 3 | Dev Slow 4 | Exit Type ATR | Period 50 | Multiplier 1
BTCUSDT 4h - Length 10 | Dev Fast 2 | Dev Slow 4 | Exit Type ATR | Period 50 | Multiplier 1
ETHUSDT 15min - Length 20 | Dev Fast 1 | Dev Slow 3 | Exit Type Fast Supertrend | Period 50 | Multiplier 1
IOTAUSDT 15min - Length 10 | Dev Fast 1 | Dev Slow 2 | Exit Type Slow Supertrend | Period 50 | Multiplier 1
OMGUSDT 15min - Length 10 | Dev Fast 1 | Dev Slow 4 | Exit Type Slow Supertrend | Period 50 | Multiplier 1
VETUSDT 15min - Length 10 | Dev Fast 3 | Dev Slow 4 | Exit Type Slow Supertrend | Period 50 | Multiplier 1
HOW TO FIND OTHER CONFIGURATIONS
Here are some steps to find suitable configurations
select a market and time frame
enable the Use This Strategy option on the strategy
open the strategy tester panel and select the performance summary
open the strategy configuration and go to properties
change the balance to the same price of the symbol (example: BTCUSDT 60.000, use 60.000 as balance)
go back to the inputs tab and keep changing the parameters until you see the net profit be positive and bigger than the absolute value of the drawdown
in case you can't find a suitable configuration, try other timeframes
Since the tester reflects what happened in the past candles, it's not guaranteed to give the same results. However, this indicator/Strategy can be used with other indicators as a leading signal or confirmation signal.
Altered True Strength Indicator (TSI) Reupload-
Altered TSI provides a slightly more volatile signal that demonstrates extremities in price action with greater success than standard TSI. In addition, I added bull/bear cross indicators (green/red) to make it easier to notice the crosses to save time when the market is moving fast (I couldn't find a regular TSI script with this addition). Finally, the signal also has overextension parameters (red and green lines)
I think this is best used on Intraday time frames as the signals respond to volatility very well and using Heikin Ashi candles, trend is more visual. In this particular example, I am showing SPY on the 3m time chart (my favorite short time frame) and the signal alone provided many opportunities for trades when using simple divergences and countering overextension direction when short term (blue) signal crosses either
In the first example (purple lines), SPY ramps but it was a dull signal given the signal strength flatlining- we would be looking for a short entry. When the signal fires, it provides a clean $1.50 move down in spy.
In the second example (orange), the blue signal provides a nice V shape (rebound signal) in which we are looking for a long entry. 390.50 is a strong SPY support in confluence with 2nd std dev VWAP extension, but disregarding that bull signal fires resulting in a 2 dollar move upwards. Exit is provided when blue line crosses green overextension.
In the third example (white), we are searching for a short entry at 392.5 resistance in confluence with divergently higher highs. Bear cross signal when fired and a significant cross is visible provides a $2.50 move to the downside with a potential exit provided when blue line crosses red overextension line in confluence with previous LOD area.
In the fourth example (green), we watch as the blue line provides a V pattern, we are searching for a long entry. If you didn't take a riskier long at 2nd std dev VWAP overextension with V recovery on blue line at red overextension for a ride to vwap, then you are looking for a secondary entry long as you wouldn't take the trade at resistance (vwap). Bullishly divergent lows provide this entry and the signal does not bear cross at all (but looking for significant crosses is more important even if the signal were to make a minor bear cross). Bullishly divergent double bottom provides a long entry to end of day with a nice clean signal for a $5.00 move until eod or when signal crosses overextension range.
Ideally, close to the money options or SPY/SPXS/SPXL are best used in the intraday time frame.
Again, this is not a standalone indicator but it's best used in conjunction with other indicators/trading strategies
Any questions feel free to comment
EMA + RSI Strategy with Labels for SL and TPThis strategy combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), and Average True Range (ATR) to create an efficient trading system designed for the 1-hour timeframe. It includes dynamic stop-loss and optional take-profit levels for risk management.
Key Components
1. Indicators Used
Exponential Moving Averages (EMAs):
Short EMA (default 9-period): Tracks recent price trends.
Long EMA (default 21-period): Tracks longer-term trends.
Condition: A bullish trend is identified when the Short EMA is above the Long EMA, and a bearish trend is identified when the Short EMA is below the Long EMA.
Relative Strength Index (RSI):
Measures momentum and identifies overbought/oversold conditions.
Default Settings:
Overbought Level: 70
Oversold Level: 30
Condition:
Long trades are triggered when the RSI crosses above the oversold level (30).
Short trades are triggered when the RSI crosses below the overbought level (70).
Average True Range (ATR):
Measures market volatility.
Used to dynamically calculate stop-loss and take-profit levels.
Entry Rules
Long Entry:
RSI crosses above the oversold level (30).
Short EMA is above the Long EMA (bullish trend).
A buy signal is plotted on the chart.
Short Entry:
RSI crosses below the overbought level (70).
Short EMA is below the Long EMA (bearish trend).
A sell signal is plotted on the chart.
Exit Rules
Dynamic Stop Loss:
Calculated as 1.5x ATR from the entry price.
Adjusts based on market volatility to prevent premature exits.
Optional Take Profit:
Calculated as 2x ATR from the entry price (configurable).
Can be enabled or disabled in the settings.
Automatic Exit:
If the price hits the stop-loss or take-profit levels, the position is exited.
Features
Dynamic Risk Management:
ATR-based stop-loss ensures that risk adapts to market volatility.
Reduces losses during highly volatile periods.
Take-Profit Flexibility:
Take profit can be toggled on or off.
The default multiplier is 2x ATR, which provides a balance between risk and reward.
Signal Visualizations:
Clear buy/sell signals are plotted on the chart using labels.
Stop-loss and take-profit levels are displayed as dynamic lines.
Labels for SL (Stop Loss) and TP (Take Profit) appear at entry to provide quick reference points.
Trend and Momentum Filtering:
EMAs ensure trades align with the prevailing trend.
RSI ensures entries occur during momentum shifts.
Strengths of This Strategy
Trend-Following: Ensures trades are made in the direction of the prevailing market trend.
Momentum-Based Entries: RSI adds precision to the entry points, capturing reversals in momentum.
Volatility Protection: ATR-based stop-loss prevents exiting trades too early during volatile market conditions.
Scalability: Works effectively on the 1-hour timeframe but can be tested on other timeframes with appropriate adjustments.
Best Use Cases
Intraday Trading: Ideal for 1-hour timeframe trading with minimal monitoring.
Volatile Markets: Adapts well to markets with varying volatility, thanks to ATR-based calculations.
Forex, Stocks, or Cryptos: Versatile strategy that can be applied across different asset classes.
Customization Options
Adjust EMA lengths for faster or slower trend detection.
Change RSI levels to suit different asset classes or trading styles.
Fine-tune ATR multipliers to balance stop-loss and take-profit distances.
Predictive Ranges, SMA, RSI strategyThis strategy combines three powerful technical indicators: Predictive Ranges, Simple Moving Average (SMA), and Relative Strength Index (RSI), to help identify potential market entry and exit points.
Key Features:
Predictive Ranges: The strategy utilizes predictive price levels (such as support and resistance levels) to anticipate potential price movements and possible breakouts. These levels act as critical points for making trading decisions.
SMA (Simple Moving Average): A 200-period SMA is incorporated to determine the overall market trend. The strategy trades in alignment with the direction of the SMA, taking long positions when the price is bellow the SMA and short positions when it is above. This helps ensure the strategy follows the prevailing market trend.
RSI (Relative Strength Index): The strategy uses the RSI (14-period) to gauge whether the market is overbought or oversold. A value above 70 signals that the asset may be overbought, while a value below 30 indicates that it might be oversold. These conditions are used to refine entry and exit points.
Entry & Exit Logic:
Long Entry: The strategy enters a long position when the price crosses above the predictive resistance level (UpLevel1/UpLevel2), and RSI is in the oversold region (below 30), signaling potential upward movement.
Short Entry: The strategy enters a short position when the price crosses below the predictive support level (LowLevel1/LowLevel2), and RSI is in the overbought region (above 70), signaling potential downward movement.
Exit Strategy: The exit levels are determined based on the predictive range levels (e.g., UpLevel1, UpLevel2, LowLevel1, LowLevel2), ensuring that trades are closed at optimal levels. A stop loss and take profit are also applied, based on a user-defined percentage, allowing for automated risk management.
Strategy Advantages:
Trend Following: By using SMA and predictive ranges, this strategy adapts to the prevailing market trend, enhancing its effectiveness in trending conditions.
RSI Filtering: The RSI helps avoid trades in overbought/oversold conditions, refining entry signals and improving the likelihood of success.
Customizable: Traders can adjust parameters such as stop loss, take profit, and predictive range levels, allowing them to tailor the strategy to their preferred risk tolerance and market conditions.
This strategy is designed for traders who prefer a combination of trend-following and mean-reversion techniques, with a focus on predictive market levels and essential momentum indicators to improve trade accuracy.
Adaptive MFI Divergence IndicatorKey Features:
Pivot-Based Divergence Detection:
The script identifies bullish and bearish divergences using MFI EMA and price pivots:
Bullish Divergence: Price forms a lower low, while the MFI EMA forms a higher low.
Bearish Divergence: Price forms a higher high, while the MFI EMA forms a lower high.
Pivots are determined using configurable left and right bars for fine-tuned divergence detection.
Dynamic Entry Conditions:
For bullish divergences, the script:
Records the pivot high formed between the two pivot lows.
Triggers a buy signal only when the price closes above the recorded pivot high.
Ensures that the divergence aligns with a positive trend and occurs under favorable volatility conditions.
For bearish divergences, the script:
Records the pivot low formed between the two pivot highs.
Triggers a sell signal only when the price closes below the recorded pivot low.
Confirms the divergence aligns with a negative trend and sufficient volatility.
Trend and Volatility Filtering:
Confirms trend alignment using EMA crossovers:
Bullish Trend: EMA (25) > EMA (50).
Bearish Trend: EMA (25) < EMA (50).
Filters signals using Historical Volatility (HV):
Signals are valid only if HV exceeds its 50-period SMA benchmark, ensuring active market conditions.
Enhanced Money Flow Index (MFI):
The MFI calculation is enhanced by:
Adjusting for volume weight using a logarithmic scale based on the ratio of current to average volume.
Normalizing weights to stay within a stable range (0.5–1.5).
Offers the option to toggle between standard and adjusted MFI using the “Use adjusted MFI” input.
Clear Visual and Alert System:
Signals are marked directly on the chart:
Green "BUY" labels appear below the bars for bullish signals.
Red "SELL" labels appear above the bars for bearish signals.
Alerts for both bullish and bearish divergences enable real-time notifications.
Entry Conditions:
Bullish Entry:
Divergence Confirmation:
Price forms a lower low.
MFI EMA forms a higher low.
Pivot low is confirmed.
Pivot High Recording:
The script records the pivot high formed between the two pivot lows.
Entry Trigger:
A buy alert is triggered only when the price closes above the recorded pivot high.
Additional checks:
Trend Confirmation: EMA (25) > EMA (50).
Volatility Validation: HV exceeds its benchmark (50-period SMA).
MFI EMA Threshold: MFI EMA > 61.8.
Bearish Entry:
Divergence Confirmation:
Price forms a higher high.
MFI EMA forms a lower high.
Pivot high is confirmed.
Pivot Low Recording:
The script records the pivot low formed between the two pivot highs.
Entry Trigger:
A sell alert is triggered only when the price closes below the recorded pivot low.
Additional checks:
Trend Confirmation: EMA (25) < EMA (50).
Volatility Validation: HV exceeds its benchmark (50-period SMA).
MFI EMA Threshold: MFI EMA < 38.2.
Practical Applications:
Divergence-Based Reversals:
Ideal for detecting potential trend reversals using divergence signals confirmed by pivot breakouts.
Trend-Filtered Signals:
Eliminates false signals by requiring trend alignment via EMA crossovers.
Volatility-Aware Trading:
Ensures signals occur during active market conditions, reducing noise and enhancing signal reliability.
Why Choose This Indicator?
The Custom MFI Divergence Alerts script combines:
Accurate divergence detection using pivots on price and MFI EMA.
Dynamic entry conditions that align with trend and market volatility.
Volume-weighted MFI adjustments for more reliable oscillator signals
BullBear with Volume-Percentile TP - Strategy [presentTrading] Happy New Year, everyone! I hope we have a fantastic year ahead.
It's been a while since I published an open script, but it's time to return.
This strategy introduces an indicator called Bull Bear Power, combined with an advanced take-profit system, which is the main innovative and educational aspect of this script. I hope all of you find some useful insights here. Welcome to engage in meaningful exchanges. This is a versatile tool suitable for both novice and experienced traders.
█ Introduction and How it is Different
Unlike traditional strategies that rely solely on price or volume indicators, this approach combines Bull Bear Power (BBP) with volume percentile analysis to identify optimal entry and exit points. It features a dynamic take-profit mechanism based on ATR (Average True Range) multipliers adjusted by volume and percentile factors, ensuring adaptability to diverse market conditions. This multifaceted strategy not only improves signal accuracy but also optimizes risk management, distinguishing it from conventional trading methods.
BTCUSD 6hr performance
Disable the visualization of Bull Bear Power (BBP) to clearly view the Z-Score.
█ Strategy, How it Works: Detailed Explanation
The BBP Strategy with Volume-Percentile TP utilizes several interconnected components to analyze market data and generate trading signals. Here's an overview with essential equations:
🔶 Core Indicators and Calculations
1. Exponential Moving Average (EMA):
- **Purpose:** Smoothens price data to identify trends.
- **Formula:**
EMA_t = (Close_t * (2 / (lengthInput + 1))) + (EMA_(t-1) * (1 - (2 / (lengthInput + 1))))
- Usage: Baseline for Bull and Bear Power.
2. Bull and Bear Power:
- Bull Power: `BullPower = High_t - EMA_t`
- Bear Power: `BearPower = Low_t - EMA_t`
- BBP:** `BBP = BullPower + BearPower`
- Interpretation: Positive BBP indicates bullish strength, negative indicates bearish.
3. Z-Score Calculation:
- Purpose: Normalizes BBP to assess deviation from the mean.
- Formula:
Z-Score = (BBP_t - bbp_mean) / bbp_std
- Components:
- `bbp_mean` = SMA of BBP over `zLength` periods.
- `bbp_std` = Standard deviation of BBP over `zLength` periods.
- Usage: Identifies overbought or oversold conditions based on thresholds.
🔶 Volume Analysis
1. Volume Moving Average (`vol_sma`):
vol_sma = (Volume_1 + Volume_2 + ... + Volume_vol_period) / vol_period
2. Volume Multiplier (`vol_mult`):
vol_mult = Current Volume / vol_sma
- Thresholds:
- High Volume: `vol_mult > 2.0`
- Medium Volume: `1.5 < vol_mult ≤ 2.0`
- Low Volume: `1.0 < vol_mult ≤ 1.5`
🔶 Percentile Analysis
1. Percentile Calculation (`calcPercentile`):
Percentile = (Number of values ≤ Current Value / perc_period) * 100
2. Thresholds:
- High Percentile: >90%
- Medium Percentile: >80%
- Low Percentile: >70%
🔶 Dynamic Take-Profit Mechanism
1. ATR-Based Targets:
TP1 Price = Entry Price ± (ATR * atrMult1 * TP_Factor)
TP2 Price = Entry Price ± (ATR * atrMult2 * TP_Factor)
TP3 Price = Entry Price ± (ATR * atrMult3 * TP_Factor)
- ATR Calculation:
ATR_t = (True Range_1 + True Range_2 + ... + True Range_baseAtrLength) / baseAtrLength
2. Adjustment Factors:
TP_Factor = (vol_score + price_score) / 2
- **vol_score** and **price_score** are based on current volume and price percentiles.
Local performance
🔶 Entry and Exit Logic
1. Long Entry: If Z-Score crosses above 1.618, then Enter Long.
2. Short Entry: If Z-Score crosses below -1.618, then Enter Short.
3. Exiting Positions:
If Long and Z-Score crosses below 0:
Exit Long
If Short and Z-Score crosses above 0:
Exit Short
4. Take-Profit Execution:
- Set multiple exit orders at dynamically calculated TP levels based on ATR and adjusted by `TP_Factor`.
█ Trade Direction
The strategy determines trade direction using the Z-Score from the BBP indicator:
- Long Positions:
- Condition: Z-Score crosses above 1.618.
- Short Positions:
- Condition: Z-Score crosses below -1.618.
- Exiting Trades:
- Long Exit: Z-Score drops below 0.
- Short Exit: Z-Score rises above 0.
This approach aligns trades with prevailing market trends, increasing the likelihood of successful outcomes.
█ Usage
Implementing the BBP Strategy with Volume-Percentile TP in TradingView involves:
1. Adding the Strategy:
- Copy the Pine Script code.
- Paste it into TradingView's Pine Editor.
- Save and apply the strategy to your chart.
2. Configuring Settings:
- Adjust parameters like EMA length, Z-Score thresholds, ATR multipliers, volume periods, and percentile settings to match your trading preferences and asset behavior.
3. Backtesting:
- Use TradingView’s backtesting tools to evaluate historical performance.
- Analyze metrics such as profit factor, drawdown, and win rate.
4. Optimization:
- Fine-tune parameters based on backtesting results.
- Test across different assets and timeframes to enhance adaptability.
5. Deployment:
- Apply the strategy in a live trading environment.
- Continuously monitor and adjust settings as market conditions change.
█ Default Settings
The BBP Strategy with Volume-Percentile TP includes default parameters designed for balanced performance across various markets. Understanding these settings and their impact is essential for optimizing strategy performance:
Bull Bear Power Settings:
- EMA Length (`lengthInput`): 21
- **Effect:** Balances sensitivity and trend identification; shorter lengths respond quicker but may generate false signals.
- Z-Score Length (`zLength`): 252
- **Effect:** Long period for stable mean and standard deviation, reducing false signals but less responsive to recent changes.
- Z-Score Threshold (`zThreshold`): 1.618
- **Effect:** Higher threshold filters out weaker signals, focusing on significant market moves.
Take Profit Settings:
- Use Take Profit (`useTP`): Enabled (`true`)
- **Effect:** Activates dynamic profit-taking, enhancing profitability and risk management.
- ATR Period (`baseAtrLength`): 20
- **Effect:** Shorter period for sensitive volatility measurement, allowing tighter profit targets.
- ATR Multipliers:
- **Effect:** Define conservative to aggressive profit targets based on volatility.
- Position Sizes:
- **Effect:** Diversifies profit-taking across multiple levels, balancing risk and reward.
Volume Analysis Settings:
- Volume MA Period (`vol_period`): 100
- **Effect:** Longer period for stable volume average, reducing the impact of short-term spikes.
- Volume Multipliers:
- **Effect:** Determines volume conditions affecting take-profit adjustments.
- Volume Factors:
- **Effect:** Adjusts ATR multipliers based on volume strength.
Percentile Analysis Settings:
- Percentile Period (`perc_period`): 100
- **Effect:** Balances historical context with responsiveness to recent data.
- Percentile Thresholds:
- **Effect:** Defines price and volume percentile levels influencing take-profit adjustments.
- Percentile Factors:
- **Effect:** Modulates ATR multipliers based on price percentile strength.
Impact on Performance:
- EMA Length: Shorter EMAs increase sensitivity but may cause more false signals; longer EMAs provide stability but react slower to market changes.
- Z-Score Parameters:*Longer Z-Score periods create more stable signals, while higher thresholds reduce trade frequency but increase signal reliability.
- ATR Multipliers and Position Sizes: Higher multipliers allow for larger profit targets with increased risk, while diversified position sizes help in securing profits at multiple levels.
- Volume and Percentile Settings: These adjustments ensure that take-profit targets adapt to current market conditions, enhancing flexibility and performance across different volatility environments.
- Commission and Slippage: Accurate settings prevent overestimation of profitability and ensure the strategy remains viable after accounting for trading costs.
Conclusion
The BBP Strategy with Volume-Percentile TP offers a robust framework by combining BBP indicators with volume and percentile analyses. Its dynamic take-profit mechanism, tailored through ATR adjustments, ensures that traders can effectively capture profits while managing risks in varying market conditions.
BBSS+This Pine Script implements a custom indicator overlaying Bollinger Bands with additional features for trend analysis using Exponential Moving Averages (EMAs). Here's a breakdown of its functionality:
Bollinger Bands:
The script calculates the Bollinger Bands using a 20-period Simple Moving Average (SMA) as the basis and a multiplier of 2 for the standard deviation.
It plots the Upper Band and Lower Band in red.
EMA Calculations:
Three EMAs are calculated for the close price with periods of 5, 10, and 40.
The EMAs are plotted in green (5-period), cyan (10-period), and orange (40-period) to distinguish between them.
Trend Detection:
The script determines bullish or bearish EMA alignments:
Bullish Order: EMA 5 > EMA 10 > EMA 40.
Bearish Order: EMA 5 < EMA 10 < EMA 40.
Entry Signals:
Long Entry: Triggered when:
The close price crosses above the Upper Bollinger Band.
The Upper Band is above its 5-period SMA (indicating momentum).
The EMAs are in a bullish order.
Short Entry: Triggered when:
The close price crosses below the Lower Bollinger Band.
The Lower Band is below its 5-period SMA.
The EMAs are in a bearish order.
Trend State Tracking:
A variable tracks whether the market is in a Long or Short trend based on conditions:
A Long trend continues unless conditions for a Short Entry are met or the Upper Band dips below its average.
A Short trend continues unless conditions for a Long Entry are met or the Lower Band rises above its average.
Visual Aids:
Signal Shapes:
Triangle-up shapes indicate Long Entry points below the bar.
Triangle-down shapes indicate Short Entry points above the bar.
Bar Colors:
Green bars indicate a Long trend.
Red bars indicate a Short trend.
This script combines Bollinger Bands with EMA crossovers to generate entry signals and visualize market trends, making it a versatile tool for identifying momentum and trend reversals.
