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ASCV BrainTrend Signal 策略
ASCV BrainTrend Signal 策略是原始 MetaTrader Expert Advisor 的移植版本,基于 BrainTrend1 指标的信号执行交易。StockSharp 实现通过高层 API 结合 ATR、随机振荡指标以及 Jurik 移动平均 (JMA),用于识别动量反转并设置可选的止损、止盈和跟踪止损。
策略思路
- 使用 ATR 计算当前波动率,得到用于确认信号的动态阈值。
- 对收盘价应用 Jurik 平滑,并与两根之前的 JMA 值比较。
- 当平滑差值大于
ATR / 2.3 时,根据随机指标 %K 判断方向:
%K < 47:进入潜在做空状态。
%K > 53:进入潜在做多状态。
- 信号在下一根完成的 K 线上执行,可通过 ReverseSignals 参数反转多空逻辑。
- 止损、止盈及跟踪止损以“点”(最小报价步长的倍数)表示。
开平仓规则
- 做多:上一根 K 线生成买入信号,且当前仓位不是多头。下单量为
Volume + |Position|,若有空头仓位会先行平仓。
- 做空:上一根 K 线生成卖出信号,且当前仓位不是空头。
- 止损:
entry ± StopLossPips * priceStep,若下一根 K 线触及该价位则市价平仓。
- 止盈:
entry ± TakeProfitPips * priceStep(参数大于 0 时启用)。
- 跟踪止损:当
TrailingStopPips 和 TrailingStepPips 都大于 0 时启用。价格向有利方向移动 TrailingStopPips + TrailingStepPips 后,止损价向有利方向移动 TrailingStopPips。
参数
| 参数 |
说明 |
默认值 |
AtrPeriod |
ATR 波动率周期。 |
14 |
StochasticPeriod |
随机指标基础周期。 |
12 |
JmaLength |
Jurik 平滑长度。 |
7 |
StopLossPips |
止损点数。 |
15 |
TakeProfitPips |
止盈点数。 |
46 |
TrailingStopPips |
跟踪止损距离。 |
0 (关闭) |
TrailingStepPips |
跟踪止损触发步长。 |
5 |
ReverseSignals |
反转多空信号。 |
false |
CandleType |
工作时间框架 (默认 15 分钟)。 |
15m |
使用提示
- 仅在完成的 K 线上计算指标,可减少盘中噪声。
- 若
Security.MinPriceStep 不可用,会使用默认步长 0.0001 将点值转换为价格差。
- 图表会绘制蜡烛图、随机指标和 JMA,方便实时监控策略状态。
- 跟踪止损实现与原始 EA 一致,只会向盈利方向移动,并要求达到距离和步长的双重条件。
建议
- 根据交易品种的波动率调整
AtrPeriod 与 StochasticPeriod。
- 对于最小报价步长较大的资产,适当增大止损和止盈,避免过早出场。
- 需要反向运行时可启用
ReverseSignals 参数。
- 实际交易应结合券商风控或其他风险管理手段。
using System;
using System.Collections.Generic;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// ASCV BrainTrend Signal strategy. Uses DEMA crossover (8/25).
/// </summary>
public class AscvBrainTrendSignalStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private decimal? _prevFast;
private decimal? _prevSlow;
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public AscvBrainTrendSignalStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(1).TimeFrame()).SetDisplay("Candle Type", "Timeframe", "General");
_fastPeriod = Param(nameof(FastPeriod), 8).SetGreaterThanZero().SetDisplay("Fast DEMA", "Fast DEMA period", "Indicators");
_slowPeriod = Param(nameof(SlowPeriod), 25).SetGreaterThanZero().SetDisplay("Slow DEMA", "Slow DEMA period", "Indicators");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities() => [(Security, CandleType)];
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevFast = null;
_prevSlow = null;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_prevFast = null; _prevSlow = null;
var fast = new DoubleExponentialMovingAverage { Length = FastPeriod };
var slow = new DoubleExponentialMovingAverage { Length = SlowPeriod };
var subscription = SubscribeCandles(CandleType);
subscription.Bind(fast, slow, ProcessCandle).Start();
var area = CreateChartArea();
if (area != null) { DrawCandles(area, subscription); DrawIndicator(area, fast); DrawIndicator(area, slow); DrawOwnTrades(area); }
}
private void ProcessCandle(ICandleMessage candle, decimal fast, decimal slow)
{
if (candle.State != CandleStates.Finished) return;
if (!IsFormedAndOnlineAndAllowTrading()) { _prevFast = fast; _prevSlow = slow; return; }
if (_prevFast == null || _prevSlow == null) { _prevFast = fast; _prevSlow = slow; return; }
var prevAbove = _prevFast.Value > _prevSlow.Value;
var currAbove = fast > slow;
_prevFast = fast; _prevSlow = slow;
if (!prevAbove && currAbove && Position <= 0) { if (Position < 0) BuyMarket(); BuyMarket(); }
else if (prevAbove && !currAbove && Position >= 0) { if (Position > 0) SellMarket(); SellMarket(); }
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import DoubleExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class ascv_brain_trend_signal_strategy(Strategy):
def __init__(self):
super(ascv_brain_trend_signal_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(1))) \
.SetDisplay("Candle Type", "Timeframe", "General")
self._fast_period = self.Param("FastPeriod", 8) \
.SetDisplay("Fast DEMA", "Fast DEMA period", "Indicators")
self._slow_period = self.Param("SlowPeriod", 25) \
.SetDisplay("Slow DEMA", "Slow DEMA period", "Indicators")
self._prev_fast = None
self._prev_slow = None
@property
def CandleType(self):
return self._candle_type.Value
@property
def FastPeriod(self):
return self._fast_period.Value
@property
def SlowPeriod(self):
return self._slow_period.Value
def OnReseted(self):
super(ascv_brain_trend_signal_strategy, self).OnReseted()
self._prev_fast = None
self._prev_slow = None
def OnStarted2(self, time):
super(ascv_brain_trend_signal_strategy, self).OnStarted2(time)
self._prev_fast = None
self._prev_slow = None
fast = DoubleExponentialMovingAverage()
fast.Length = self.FastPeriod
slow = DoubleExponentialMovingAverage()
slow.Length = self.SlowPeriod
subscription = self.SubscribeCandles(self.CandleType)
subscription.Bind(fast, slow, self._on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, fast)
self.DrawIndicator(area, slow)
self.DrawOwnTrades(area)
def _on_process(self, candle, fast_value, slow_value):
if candle.State != CandleStates.Finished:
return
fv = float(fast_value)
sv = float(slow_value)
if self._prev_fast is None or self._prev_slow is None:
self._prev_fast = fv
self._prev_slow = sv
return
prev_above = self._prev_fast > self._prev_slow
curr_above = fv > sv
self._prev_fast = fv
self._prev_slow = sv
if not prev_above and curr_above and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif prev_above and not curr_above and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
def CreateClone(self):
return ascv_brain_trend_signal_strategy()