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BOLL布林带定向策略 1. 策略原理 当收盘价上穿下轨，做多 当收盘价下穿上轨，做空 代码： seting = {'name': 'BBv3', 'symbol': 'BTCUSDT', 'kTime': '15m', 'bb_len': 7, 'buy_len': 44, 'buy_mult': 2.664, 'sell_len': 20, 'sell_mult': 2.54, 'buy': 1, 'buyZhiying': 12.704, 'buyZhisun': 7.525, 'sell': 1, 'sellZhiying': 6.112, 'sellZhisun': 1.52} """ 布林带升级版定向策略 """ def BBv3(r, df, seting): df['ma'] = SMA(r, seting['bb_len'], 'Close') df['upper'] = df['ma'] + seting['sell_mult'] * talib.STDDEV(df['Close'], timeperiod=seting['sell_len']) df['lower'] = df['ma'] - seting['buy_mult'] * talib.STDDEV(df['Close'], timeperiod=seting['buy_len']) c = len(df) for i in range(c): if i > seting['sell_len'] and i+1 < c: if df['Close'][i] > df['lower'][i] and df['Close'][i-1] < df['lower'][i-1]: # and df['Close'][i] > df['ma2'][i] df['side'].values[i] = 'BUY' if df['Close'][i] < df['upper'][i] and df['Close'][i-1] > df['upper'][i-1]: # and df['Close'][i] < df['ma2'][i] df['side'].values[i] = 'SELL' return df 2.回测结果 BTCUSDT 15m： -
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Boll布林带突破策略 1.策略原理 一个很简单的策略 突破上轨，且Rsi没有超卖时做多，价格回归中轨时平仓 代码： seting = {'name': 'BB', 'symbol': 'ETHUSDT', 'kTime': '15m', 'bb_len': 129, 'bb_mult': 2.259, 'rsi_len': 22, 'rsi_long_min': 15, 'rsi_long_max': 76, 'rsi_short_min': 12, 'rsi_short_max': 74, 'buy': 1, 'buyZhiying': 13.037, 'buyZhisun': 8.014, 'sell': 1, 'sellZhiying': 5.084, 'sellZhisun': 13.086} """ 布林带策略 """ def BB(r, df, seting): df['ma'] = SMA(r, seting['bb_len'], 'Close') df['mult'] = seting['bb_mult'] * talib.STDDEV(df['Close'].values, timeperiod=seting['bb_len']) df['upper'] = df['ma'] + df['mult'] df['lower'] = df['ma'] - df['mult'] df['rsi'] = talib.RSI(df['Close'].values, timeperiod=14) c = len(df) for i in range(c): if i > seting['bb_len'] and i+1 < c: if df['Close'][i] > df['upper'][i] and df['Close'][i-1] < df['upper'][i-1] and\ df['rsi'][i] >= seting['rsi_long_min'] and df['rsi'][i] <= seting['rsi_long_max']: df['side'].values[i] = 'BUY' if df['Close'][i] < df['ma'][i] and df['Close'][i-1] > df['ma'][i-1]: df['close'].values[i] = 'BUY' if df['Close'][i] < df['lower'][i] and df['Close'][i-1] > df['lower'][i-1] and\ df['rsi'][i] >= seting['rsi_short_min'] and df['rsi'][i] <= seting['rsi_short_max']: df['side'].values[i] = 'SELL' if df['Close'][i] > df['ma'][i] and df['Close'][i-1] < df['ma'][i-1]: df['close'].values[i] = 'SELL' return df 2.回测结果 -
DMI策略 1.策略原理 很简单的一个策略，只用了DMI一个指标 获得DMI两条线后相减，再把值做平滑处理 值 > 0 且大于上一个值 就做多 DMI指标的计算可以看我发过的ADX指标里面有 代码： """ DMI指标策略 """ def DMI(r, df, seting): a, b = DI(r, seting['dmi_len']) df['dmi'] = a-b if seting['ma_type'] == 'sma': df['dmi'] = SMA(df['dmi'].values, seting['ma_len']) if seting['ma_type'] == 'ema': df['dmi'] = talib.EMA(df['dmi'].values, seting['ma_len']) if seting['ma_type'] == 'rma': df['dmi'] = RMA(df['dmi'].values, seting['ma_len']) c = len(df) for i in range(c): if i > seting['ma_len'] and i+1 < c: if df['dmi'][i] > 0 and df['dmi'][i] > df['dmi'][i-1]: df['side'].values[i] = 'BUY' if df['dmi'][i] < 0 and df['dmi'][i] < df['dmi'][i-1]: df['side'].values[i] = 'SELL' return df 2.回测结果 15mk线 2021年： -
P-Signal 策略 1.策略原理 这是基于 p 信号构建交易策略的示例。 p 信号表示 Kolmogorov 概率空间中 交易对的 D 帧系统状态的熵。 TradingView完整源码： strategy("P-Signal Strategy:", precision = 3) // // Parameters and const of P-Signal. // nIntr = input(title = "Number of Bars", type = input.integer, defval = 9, minval = 4, maxval = 100, group = "Parameters of observation.") bSmooth = input(title = "Smoothing", type = input.bool, defval = true, group = "Parameters of observation.") // // Horner's method for the error (Gauss) & P-Signal functions. // fErf(x) => nT = 1.0/(1.0 + 0.5*abs(x)) nAns = 1.0 - nT*exp(-x*x - 1.26551223 + nT*( 1.00002368 + nT*( 0.37409196 + nT*( 0.09678418 + nT*(-0.18628806 + nT*( 0.27886807 + nT*(-1.13520398 + nT*( 1.48851587 + nT*(-0.82215223 + nT*( 0.17087277 )))))))))) x >= 0 ? nAns : -nAns fPSignal(ser, int) => nStDev = stdev(ser, int) nSma = sma(ser, int) fErf(nStDev > 0 ? nSma/nStDev/sqrt(2) : 1.0) // // Signals on Set of Frames. // nPSignal = fPSignal(change(ohlc4), nIntr) nPSignal := if (bSmooth) sma(nPSignal, nIntr) ndPSignal = sign(nPSignal[0] - nPSignal[1]) // // P-Signal plotting. // hline(+1.0, color = color.new(color.orange,70), linestyle = hline.style_dotted) hline(-1.0, color = color.new(color.orange,70), linestyle = hline.style_dotted) plot(nPSignal, color = nPSignal > nPSignal[1] ? color.green : color.red, style = plot.style_line) // // Strategy "A penny saved is a penny earnd." Caution with short! // strategy.entry("long", strategy.long, when = nPSignal < 0 and ndPSignal > 0) strategy.close("long", when = nPSignal > 0 and ndPSignal < 0) Python实现： 2. 回测结果 K线15m 手续费万4% MA周期60 止盈30% 止损6.6% 2021年:
