This strategy combines technical analysis tools such as Moving Averages (MA), Relative Strength Index (RSI), and Average True Range (ATR) to capture trending opportunities in the market. The strategy uses dual moving average crossovers to determine the trend direction and employs the RSI indicator for momentum filtering of trading signals. It also utilizes ATR as a basis for stop-loss to manage risk.
The core of this strategy is to use the crossover of two moving averages with different periods (fast and slow) to identify market trends. When the fast MA crosses above the slow MA, it indicates an uptrend, and the strategy will generate a long signal. Conversely, when the fast MA crosses below the slow MA, it indicates a downtrend, and the strategy will generate a short signal.
To improve the reliability of trading signals, the strategy introduces the RSI indicator as a momentum filter. Long positions are only allowed when the RSI is above a certain threshold (e.g., 50), and short positions are only allowed when the RSI is below that threshold. This helps avoid trading during sideways markets or when momentum is lacking, thus improving signal quality.
Furthermore, the strategy uses ATR as a basis for stop-loss, dynamically adjusting the stop-loss level according to the price volatility over a recent period. This adaptive stop-loss approach allows for quick stops during unclear trends to control drawdowns, while providing more room for profits during strong trends to enhance strategy returns.
This strategy effectively combines trend-following and momentum filtering to capture trending opportunities in the market while managing risk. The strategy logic is clear and easy to implement and optimize. However, in practical application, attention should be paid to whipsaw risk and parameter risk. The strategy should be flexibly adjusted and optimized based on market characteristics and individual needs. Overall, this is a balanced strategy that considers both trend capturing and risk control, worthy of further exploration and practice.
/*backtest start: 2023-05-28 00:00:00 end: 2024-06-02 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 strategy("Trend-Following Strategy with MACD and RSI Filter", overlay=true) // Input variables fastLength = input(12, title="Fast MA Length") slowLength = input(26, title="Slow MA Length") signalLength = input(9, title="Signal Line Length") stopLossPct = input(1.0, title="Stop Loss %") / 100 rsiLength = input(14, title="RSI Length") rsiThreshold = input(50, title="RSI Threshold") // Moving averages fastMA = ta.sma(close, fastLength) slowMA = ta.sma(close, slowLength) // MACD [macdLine, signalLine, _] = ta.macd(close, fastLength, slowLength, signalLength) // RSI rsi = ta.rsi(close, rsiLength) // Entry conditions with RSI filter bullishSignal = ta.crossover(macdLine, signalLine) and rsi > rsiThreshold bearishSignal = ta.crossunder(macdLine, signalLine) and rsi < rsiThreshold // Calculate stop loss levels longStopLoss = ta.highest(close, 10)[1] * (1 - stopLossPct) shortStopLoss = ta.lowest(close, 10)[1] * (1 + stopLossPct) // Execute trades strategy.entry("Long", strategy.long, when=bullishSignal) strategy.entry("Short", strategy.short, when=bearishSignal) strategy.exit("Exit Long", "Long", stop=longStopLoss) strategy.exit("Exit Short", "Short", stop=shortStopLoss) // Plotting signals plotshape(bullishSignal, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Bullish Signal") plotshape(bearishSignal, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Bearish Signal") // Plot MACD plot(macdLine, color=color.blue, title="MACD Line") plot(signalLine, color=color.orange, title="Signal Line") // Plot RSI hline(rsiThreshold, "RSI Threshold", color=color.gray) plot(rsi, color=color.purple, title="RSI")template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6