Cette stratégie base les décisions de trading sur les caractéristiques dynamiques de l'indicateur MACD (Moving Average Convergence Divergence). L'approche de base se concentre sur l'observation des changements dans l'histogramme MACD pour prédire les croisements potentiels d'or et de mort, permettant l'établissement précoce de positions.
La stratégie utilise un système d'indicateur MACD modifié, incorporant la différence entre les moyennes mobiles rapides (EMA12) et lentes (EMA26), ainsi qu'une ligne de signal à 2 périodes.
Cette stratégie utilise de manière innovante les caractéristiques dynamiques de l'histogramme MACD pour améliorer les systèmes de trading traditionnels MACD. Le mécanisme prédictif fournit des signaux d'entrée plus tôt, tandis que des conditions de trading strictes et des mesures de contrôle des risques assurent la stabilité de la stratégie.
/*backtest start: 2019-12-23 08:00:00 end: 2024-11-25 08:00:00 period: 1d basePeriod: 1d exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 strategy(title="Demo GPT - Moving Average Convergence Divergence", shorttitle="MACD", commission_type=strategy.commission.percent, commission_value=0.1, slippage=3, default_qty_type=strategy.percent_of_equity, default_qty_value=100) // Getting inputs fast_length = input(title="Fast Length", defval=12) slow_length = input(title="Slow Length", defval=26) src = input(title="Source", defval=close) signal_length = input.int(title="Signal Smoothing", minval=1, maxval=50, defval=2) // Set smoothing line to 2 sma_source = input.string(title="Oscillator MA Type", defval="EMA", options=["SMA", "EMA"]) sma_signal = input.string(title="Signal Line MA Type", defval="EMA", options=["SMA", "EMA"]) // Date inputs start_date = input(title="Start Date", defval=timestamp("2018-01-01T00:00:00")) end_date = input(title="End Date", defval=timestamp("2069-12-31T23:59:59")) // Calculating fast_ma = sma_source == "SMA" ? ta.sma(src, fast_length) : ta.ema(src, fast_length) slow_ma = sma_source == "SMA" ? ta.sma(src, slow_length) : ta.ema(src, slow_length) macd = fast_ma - slow_ma signal = sma_signal == "SMA" ? ta.sma(macd, signal_length) : ta.ema(macd, signal_length) hist = macd - signal // Strategy logic isInDateRange = true // Calculate the rate of change of the histogram hist_change = hist - hist[1] // Anticipate a bullish crossover: histogram is negative, increasing, and approaching zero anticipate_long = isInDateRange and hist < 0 and hist_change > 0 and hist > hist[1] and hist > hist[2] // Anticipate an exit (bearish crossover): histogram is positive, decreasing, and approaching zero anticipate_exit = isInDateRange and hist > 0 and hist_change < 0 and hist < hist[1] and hist < hist[2] if anticipate_long strategy.entry("Long", strategy.long) if anticipate_exit strategy.close("Long") // Plotting hline(0, "Zero Line", color=color.new(#787B86, 50)) plot(hist, title="Histogram", style=plot.style_columns, color=(hist >= 0 ? (hist > hist[1] ? #26A69A : #B2DFDB) : (hist < hist[1] ? #FF5252 : #FFCDD2))) plot(macd, title="MACD", color=#2962FF) plot(signal, title="Signal", color=#FF6D00) // Plotting arrows when anticipating the crossover plotshape(anticipate_long, title="Long +1", location=location.belowbar, color=color.green, style=shape.arrowup, size=size.tiny, text="Long +1") plotshape(anticipate_exit, title="Short -1", location=location.abovebar, color=color.red, style=shape.arrowdown, size=size.tiny, text="Short -1")