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JBrainTrend1Stop 策略
JBrainTrend1Stop 策略是 MetaTrader 5 专家顾问 Exp_JBrainTrend1Stop 在 StockSharp 平台上的移植版本。它将两条 Average True Range、Stochastic 振荡器以及三条 Jurik 移动平均线结合起来,用于识别 BrainTrading 趋势反转。当 Jurik 平滑后的价格出现足够大的摆动并且 Stochastic 脱离中性区间时,策略会切换方向、更新 BrainTrend 止损线,并且(在可选的情况下)在指定的延迟后反转净持仓。
交易逻辑
- 订阅
CandleType 指定的K线,并将其输入以下指标:
- 主
AverageTrueRange,周期为 AtrPeriod。
- 扩展
AverageTrueRange,周期为 AtrPeriod + StopDPeriod。
StochasticOscillator,周期为 StochasticPeriod,%K 只做一次平滑(与 MT5 设置一致)。
- 三条
JurikMovingAverage(高/低/收),均使用 JmaLength 和 JmaPhase 参数。
- 每根收盘K线计算:
range = ATR / 2.3(对应原始代码中的常量 d)。
range1 = ATR_extended * 1.5(对应常量 s)。
val3 = |JMA_close - JMA_close[向前两根]|,复现 MT5 缓冲区差值。
- 当
val3 > range 且 Stochastic 脱离中性区间时:
- 若
%K < 47,进入看空模式(_trendState = -1),将止损初始化为 JMA_high + range1 / 4,并生成 sell 信号。
- 若
%K > 53,进入看多模式(_trendState = 1),止损为 JMA_low - range1 / 4,并生成 buy 信号。
- 在模式保持不变时,BrainTrend 止损线按
range1 向价格靠拢(看空时为 JMA_high + range1,看多时为 JMA_low - range1)。
- 信号会在
SignalBar 根已完成K线之后触发:
- Buy 信号会在允许时先平掉空头(
SellClose),并在允许开仓 (BuyOpen) 时建立多头。
- Sell 信号会在允许时平掉多头(
BuyClose),并在允许开仓 (SellOpen) 时建立空头。
图表会自动叠加 Jurik 平滑的收盘价、Stochastic 振荡器以及交易标记。
参数
| 参数 |
说明 |
默认值 |
CandleType |
策略处理的K线类型。 |
H4(4小时K线) |
AtrPeriod |
BrainTrend 触发所用的主 ATR 周期。 |
7 |
StochasticPeriod |
Stochastic %K/%D 周期(%K 仅平滑 1 根)。 |
9 |
StopDPeriod |
附加到第二条 ATR 周期的额外长度(AtrPeriod + StopDPeriod)。 |
3 |
JmaLength |
应用于高/低/收的 Jurik MA 周期。 |
7 |
JmaPhase |
传递给 Jurik MA 的相位参数(限制在 [-100, 100])。 |
100 |
SignalBar |
信号执行前需要等待的已完成K线数量。 |
1 |
BuyOpen / SellOpen |
是否允许在信号后建立多头/空头。 |
true |
BuyClose / SellClose |
是否允许在反向信号出现时平多/平空。 |
true |
请通过策略的 Volume 属性或券商设置控制下单手数。
与 MT5 原版的差异
- 原策略的资金管理模块(
MM、MMMode、Deviation_ 等)被标准的 Volume 下单方式所取代,没有复刻滑点控制。
- 固定点差的止损/止盈(
StopLoss_、TakeProfit_)未实现。如需保护,请在宿主平台中自行配置风险管理。
- BrainTrend 止损线仅用于内部判定信号,不会被下成挂单。
- Jurik 移动平均来自 StockSharp 的实现,并通过反射应用相位参数,与仓库中其他 BrainTrading 策略保持一致。
使用步骤
- 将策略附加到标的证券,并设置
CandleType(建议使用 4 小时K线以贴近原版)。
- 调整指标参数(
AtrPeriod、StochasticPeriod、StopDPeriod、JmaLength、JmaPhase)以匹配期望的 BrainTrend 灵敏度。
- 通过
SignalBar 控制信号与建仓之间的延迟。
- 根据交易方向设置
Volume 以及开仓/平仓开关(BuyOpen、SellOpen、BuyClose、SellClose)。
- 如有需要,在宿主环境中添加额外的风险控制(止损、仓位限制等)。
启动后,策略会追踪 BrainTrend 反转,在允许的情况下平掉对冲仓位,并在指定延迟后反转净头寸。
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
public class JBrainTrend1StopStrategy : Strategy
{
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private readonly StrategyParam<int> _stopLossPoints;
private readonly StrategyParam<int> _takeProfitPoints;
private ExponentialMovingAverage _fast;
private ExponentialMovingAverage _slow;
private decimal _prevFast;
private decimal _prevSlow;
private decimal _entryPrice;
private int _cooldown;
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public int StopLossPoints { get => _stopLossPoints.Value; set => _stopLossPoints.Value = value; }
public int TakeProfitPoints { get => _takeProfitPoints.Value; set => _takeProfitPoints.Value = value; }
public JBrainTrend1StopStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 14).SetGreaterThanZero().SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 50).SetGreaterThanZero().SetDisplay("Slow Period", "Slow EMA period", "Indicator");
_stopLossPoints = Param(nameof(StopLossPoints), 200).SetNotNegative().SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk");
_takeProfitPoints = Param(nameof(TakeProfitPoints), 400).SetNotNegative().SetDisplay("Take Profit", "Take-profit in price steps", "Risk");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
protected override void OnReseted()
{
base.OnReseted();
_fast = null; _slow = null;
_prevFast = 0; _prevSlow = 0; _entryPrice = 0; _cooldown = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_fast = new ExponentialMovingAverage { Length = FastPeriod };
_slow = new ExponentialMovingAverage { Length = SlowPeriod };
var subscription = SubscribeCandles(TimeSpan.FromMinutes(5).TimeFrame());
subscription.Bind(_fast, _slow, ProcessCandle);
subscription.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal fastValue, decimal slowValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_fast.IsFormed || !_slow.IsFormed) { _prevFast = fastValue; _prevSlow = slowValue; return; }
if (_cooldown > 0) { _cooldown--; _prevFast = fastValue; _prevSlow = slowValue; return; }
var close = candle.ClosePrice;
var step = Security?.PriceStep ?? 1m;
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{ if (Position < 0) BuyMarket(); BuyMarket(); _entryPrice = close; _cooldown = 100; }
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{ if (Position > 0) SellMarket(); SellMarket(); _entryPrice = close; _cooldown = 100; }
_prevFast = fastValue; _prevSlow = slowValue;
}
}
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 ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class j_brain_trend1_stop_strategy(Strategy):
def __init__(self):
super(j_brain_trend1_stop_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 14) \
.SetDisplay("Fast Period", "Fast MA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 50) \
.SetDisplay("Slow Period", "Slow MA period", "Indicator")
self._stop_loss_points = self.Param("StopLossPoints", 200) \
.SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk")
self._take_profit_points = self.Param("TakeProfitPoints", 400) \
.SetDisplay("Take Profit", "Take-profit in price steps", "Risk")
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
@property
def fast_period(self):
return self._fast_period.Value
@property
def slow_period(self):
return self._slow_period.Value
@property
def stop_loss_points(self):
return self._stop_loss_points.Value
@property
def take_profit_points(self):
return self._take_profit_points.Value
def OnReseted(self):
super(j_brain_trend1_stop_strategy, self).OnReseted()
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
def OnStarted2(self, time):
super(j_brain_trend1_stop_strategy, self).OnStarted2(time)
self._fast = ExponentialMovingAverage()
self._fast.Length = self.fast_period
self._slow = ExponentialMovingAverage()
self._slow.Length = self.slow_period
subscription = self.SubscribeCandles(DataType.TimeFrame(TimeSpan.FromMinutes(5)))
subscription.Bind(self._fast, self._slow, self._process_candle)
subscription.Start()
def _process_candle(self, candle, fast_value, slow_value):
if candle.State != CandleStates.Finished:
return
fast_val = float(fast_value)
slow_val = float(slow_value)
if not self._fast.IsFormed or not self._slow.IsFormed:
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_fast = fast_val
self._prev_slow = slow_val
return
close = float(candle.ClosePrice)
step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
if self.Position > 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close <= self._entry_price - self.stop_loss_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close >= self._entry_price + self.take_profit_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
elif self.Position < 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close >= self._entry_price + self.stop_loss_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close <= self._entry_price - self.take_profit_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._prev_fast <= self._prev_slow and fast_val > slow_val and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = close
self._cooldown = 100
elif self._prev_fast >= self._prev_slow and fast_val < slow_val and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = close
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return j_brain_trend1_stop_strategy()