This strategy utilizes the Stochastic Oscillator to identify overbought and oversold market conditions, triggering trades with predefined risk and reward parameters to capitalize on price fluctuations within a volatile trading range. The main idea behind this strategy is to buy at the low end of the trading range and sell at the high end, while strictly controlling risk.
The volatility range trading strategy based on the Stochastic Oscillator attempts to capitalize on the oscillator’s overbought and oversold signals within a predefined trading range. The strategy controls risk through strict risk management and trade intervals. While the strategy has certain advantages, its success largely depends on correctly identifying the trading range. Future optimization directions include combining other technical indicators, introducing dynamic stop-loss and take-profit levels, using more advanced range identification techniques, and adding a trend filter. When applying the strategy in practice, be sure to adjust the parameters and risk management rules according to personal preferences and risk tolerance.
/*backtest start: 2023-06-11 00:00:00 end: 2024-06-16 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 strategy("Range Trading with Stochastic", overlay=true) // Input Parameters overboughtLevel = input.int(80, title="Overbought Level", minval=1, maxval=100) oversoldLevel = input.int(20, title="Oversold Level", minval=1, maxval=100) stochLength = input.int(14, title="Stochastic Length", minval=1) riskPerTrade = input.float(0.01, title="Risk per Trade (%)", minval=0.01, maxval=100, step=0.01) barsBetweenTrades = input.int(20, title="Bars Between Trades", minval=1) // Calculate Stochastic Oscillator k = ta.sma(ta.stoch(close, high, low, stochLength), 3) d = ta.sma(k, 3) // Variables to Track Time Since Last Trade var lastTradeBar = 0 barsSinceLastTrade = bar_index - lastTradeBar // Risk Management atr = ta.atr(14) stopLoss = 2 * atr takeProfit = 2 * atr riskAmount = strategy.equity * riskPerTrade / 100 positionSize = 1 // Entry Conditions longCondition = k < oversoldLevel and strategy.position_size == 0 and barsSinceLastTrade >= barsBetweenTrades shortCondition = k > overboughtLevel and strategy.position_size == 0 and barsSinceLastTrade >= barsBetweenTrades // Entry/Exit Orders if longCondition strategy.entry("Long", strategy.long, qty=positionSize) strategy.exit("Long Exit", "Long", stop=close - stopLoss, limit=close + takeProfit) lastTradeBar := bar_index // Update last trade bar if shortCondition strategy.entry("Short", strategy.short, qty=positionSize) strategy.exit("Short Exit", "Short", stop=close + stopLoss, limit=close - takeProfit) lastTradeBar := bar_index // Update last trade bar // Plot Stochastic plot(k, color=color.blue, title="%K") plot(d, color=color.orange, title="%D") hline(overboughtLevel, color=color.red, title="Overbought") hline(oversoldLevel, color=color.green, title="Oversold")template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6