ChaoZhang
Overview
This strategy is a high-frequency trading system that combines Bollinger Bands indicators with price breakout signals. The strategy monitors the relationship between price and Bollinger Bands, combined with previous high and low point breakout signals, to execute reversal trades during market overbought and oversold conditions. The system implements a 1:1 risk-reward ratio for profit and loss targets, and visualizes key price levels to help traders intuitively understand market trends.
Strategy Principles
The core logic of the strategy is based on two main conditions: a buy signal is triggered when the price breaks above the previous high and that high is below the lower Bollinger Band; a sell signal is triggered when the price breaks below the previous low and that low is above the upper Bollinger Band. The Bollinger Bands parameters use a 20-period moving average with 2 standard deviations to determine market volatility range and overbought/oversold areas. After triggering trading signals, the system automatically sets corresponding stop-loss and target levels, visualizing them through different line styles.
Strategy Advantages
- Combines both trend breakout and mean reversion trading approaches, maintaining stability across different market conditions
- Uses fixed risk-reward ratio for position management, beneficial for long-term profitable trading
- Visualizes entry, stop-loss, and target levels, improving strategy operability
- Utilizes Bollinger Bands to identify market overbought/oversold conditions, enhancing trading accuracy
- Simple and clear strategy logic, easy to understand and execute
Strategy Risks
- High-frequency trading may face higher transaction costs, requiring consideration of commission impacts
- May generate frequent false breakout signals in ranging markets
- Fixed risk-reward ratio might not fully capture strong trend movements
- Fixed Bollinger Bands parameters may not adapt to all market conditions
- Requires real-time market monitoring to ensure timely signal execution
Strategy Optimization Directions
- Incorporate volume indicators for signal confirmation, improving breakout reliability
- Dynamically adjust Bollinger Bands parameters based on market volatility
- Add trend filters to avoid frequent trading in ranging markets
- Consider adding time filters to avoid trading during inactive periods
- Develop adaptive risk-reward ratio setting mechanisms
Summary
This is a comprehensive trading system integrating multiple technical analysis concepts. Through the combination of Bollinger Bands indicators and price breakouts, the strategy can capture reversal opportunities in market overbought and oversold areas. While there is room for optimization, the system’s basic framework has good extensibility and practical value. Through proper risk management and parameter optimization, this strategy has the potential to achieve stable returns in actual trading.
/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-03 00:00:00
period: 2d
basePeriod: 2d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
strategy("Bollinger Band Scalping", overlay=true)
// Input for Bollinger Bands length and standard deviation
bbLength = input(20, title="Bollinger Bands Length")
stdDev = input(2.0, title="Bollinger Bands Std Dev")
// Calculate and plot the Bollinger Bands
basis = ta.sma(close, bbLength)
deviation = stdDev * ta.stdev(close, bbLength)
upperBB = basis + deviation
lowerBB = basis - deviation
// Get previous candle's values
prevHigh = high[1] // Previous candle high
prevLow = low[1] // Previous candle low
// Buy Signal Condition: Current high crossed above previous high and previous high is below the lower Bollinger Band
buyCondition = ta.crossover(high, prevHigh) and (prevHigh < lowerBB[1])
// Sell Signal Condition: Current low crossed below previous low and previous low is above the upper Bollinger Band
sellCondition = ta.crossunder(low, prevLow) and (prevLow > upperBB[1])
// Entry and exit for Buy signals
if (buyCondition)
strategy.entry("Buy", strategy.long)
// Calculate target and stop loss
stopLossPrice = prevLow
targetPrice = prevHigh + (prevHigh - stopLossPrice) // 1:1 RR target
// Set stop loss and target orders
strategy.exit("Sell", "Buy", limit=targetPrice, stop=stopLossPrice)
// // Plot entry line
// line.new(x1=bar_index, y1=prevHigh, x2=bar_index + 12, y2=prevHigh, color=color.green, width=2, style=line.style_solid)
// // Plot stop loss line
// line.new(x1=bar_index, y1=stopLossPrice, x2=bar_index + 12, y2=stopLossPrice, color=color.red, width=1, style=line.style_dashed)
// // Plot target line
// line.new(x1=bar_index, y1=targetPrice, x2=bar_index + 12, y2=targetPrice, color=color.blue, width=2, style=line.style_solid)
// Entry and exit for Sell signals
if (sellCondition)
strategy.entry("Sell", strategy.short)
// Calculate target and stop loss
stopLossPriceSell = prevHigh
targetPriceSell = prevLow - (stopLossPriceSell - prevLow) // 1:1 RR target
// Set stop loss and target orders
strategy.exit("Cover", "Sell", limit=targetPriceSell, stop=stopLossPriceSell)
// // Plot entry line
// line.new(x1=bar_index, y1=prevLow, x2=bar_index + 12, y2=prevLow, color=color.red, width=2, style=line.style_solid)
// // Plot stop loss line
// line.new(x1=bar_index, y1=stopLossPriceSell, x2=bar_index + 12, y2=stopLossPriceSell, color=color.green, width=1, style=line.style_dashed)
// // Plot target line
// line.new(x1=bar_index, y1=targetPriceSell, x2=bar_index + 12, y2=targetPriceSell, color=color.blue, width=2, style=line.style_solid)
// Plotting Bollinger Bands with 70% transparency
plot(upperBB, color=color.red, title="Upper Bollinger Band", transp=70)
plot(lowerBB, color=color.green, title="Lower Bollinger Band", transp=70)
plot(basis, color=color.blue, title="Middle Band", transp=70)