多指标黄金摆动交易策略
该交易策略综合运用RSI、Stochastic、布林带和SuperTrend等多种指标,形成交易信号。
具体来说,它同时考虑RSI高于50表示多头市场和Stochastic中的K值高于D值为多头信号。价格低于SuperTrend代表处于上升趋势,并且SuperTrend位于布林带中轨之下才产生做多信号。
反之,RSI低于50和Stochastic中的K值低于D值为空头信号,价格高于SuperTrend代表下降趋势,并且SuperTrend高于布林带中轨才形成做空信号。
这样多指标组合可以形成有效的过滤机制,提高交易信号的可靠性。此外,Strategy还设置了止损和止盈条件来控制风险。
但是,多指标组合也存在指标滞后的问题,可能错过最佳入场点位。实盘中仍需优化参数,并关注整体经济环境对交易的影响。只有做到全面风险管理,才能长期获得稳定收益。
/*backtest
start: 2023-01-01 00:00:00
end: 2023-03-10 00:00:00
period: 45m
basePeriod: 5m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © rajm14
//@version=5
strategy(title = "Golden Swing Strategy - Souradeep Dey", shorttitle = "GSS", overlay = true, process_orders_on_close = true, default_qty_type = strategy.cash, default_qty_value=100000, currency = currency.USD)
// Indicator - RSI - 20
rsiSrc = input(defval = close, title = "RSI Source")
rsiLen = input.int(defval = 20, title = "RSI Length", minval = 0, maxval = 200, step = 1)
rsi = ta.rsi(rsiSrc, rsiLen)
//plot(rsi)
// Indicator - Stochastic (55,34,21)
kLength = input.int(defval = 55, title="Stoch %K Length", minval=1)
kSmooth = input.int(defval = 34, title="Stoch %K Smoothing", minval=1)
dLength = input.int(defval = 21, title="Stoch %D Smoothing", minval=1)
kLine = ta.sma(ta.stoch(close, high, low, kLength), kSmooth)
dLine = ta.sma(kLine, dLength)
// plot(kLine, color=color.red)
// plot(dLine, color=color.green)
// Indicator - ATR(5)
atrLength = input(5, "ATR Length")
atr = ta.atr(5)
// plot(atr)
// Indicator - SuperTrend(10,2)
atrPeriod = input(10, "SuperTrend ATR Length")
stSrc = hl2
stfactor = input.float(2.0, "SuperTrend Multiplier", step = 0.1)
stAtr = ta.atr(atrPeriod)
[supertrend, direction] = ta.supertrend(stfactor, atrPeriod)
bodyMiddle = (open + close) / 2
upTrend = direction < 0 ? supertrend : na
downTrend = direction < 0? na : supertrend
// plot(bodyMiddle, display=display.none)
// plot(upTrend)
// plot(downTrend)
// Indicator - Bollinger Bands (20,2)
bblength = input.int(defval = 20, title = "BB Length")
bbsource = input(defval = close, title = "BB Source")
bbStdDev = input.float(defval = 2.0, title = "BB Std Dev", step = 0.1)
bbmultiplier = bbStdDev * ta.stdev(bbsource, bblength)
bbMband = ta.sma(bbsource, bblength)
bbUband = bbMband + bbmultiplier
bbLband = bbMband - bbmultiplier
// plot (bbUband, color = color.red, linewidth = 2)
// plot (bbMband, color = color.black, linewidth = 2)
// plot (bbLband, color = color.green, linewidth = 2)
// Trade Entry
LongEntry = rsi >= 50 and kLine > dLine and low < supertrend and direction < 0 and supertrend < bbMband
ShortEntry = rsi <= 50 and kLine < dLine and high > supertrend and direction > 0 and supertrend > bbMband
plotshape(LongEntry, style = shape.triangleup, text = "Long", location = location.belowbar, size = size.large, color = color.green)
plotshape(ShortEntry, style = shape.triangledown, text = "Short", location = location.abovebar, size = size.large, color = color.red)
//Trade execution
if LongEntry
strategy.entry(id = "Buy", direction = strategy.long, limit = close * .5 * atr)
closelong = close >= strategy.position_avg_price * 2.2 * atr
stoplong = close <= strategy.position_avg_price * 1.1 * atr
if closelong
strategy.close(id = "Buy")
if stoplong
strategy.close(id = "Buy")
if ShortEntry
strategy.entry(id = "Sell", direction = strategy.long, limit = close * .5 * atr)
closeshort = close <= strategy.position_avg_price * 2.2 * atr
stopshort = close >= strategy.position_avg_price * 1.1 * atr
if closeshort
strategy.close(id = "Sell")
if stopshort
strategy.close(id = "Sell")