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Gold Dust 策略
概述
Gold Dust 策略在 StockSharp 框架中重现了 MetaTrader 5 顾问程序 “Gold Dust”。策略通过线性加权移动平均线(LWMA)构建一到两个感知器,输入价格使用加权价(高+低+2×收盘)。每个感知器比较价格与均线在四个按周期等距的时间点之间的差值。当感知器结果为正时开空,为负时开多,与原版 EA 完全一致。本移植版依赖 StockSharp 的高层烛线订阅接口,不需要手动管理指标缓存。
信号生成
- 订阅参数
CandleType 指定的烛线并计算周期为 MaPeriod 的 WeightedMovingAverage。
- 每根收盘烛线记录其开盘价、收盘价及对应的 LWMA 值,始终保留三个完整周期的历史,模拟原版
CopyRates 与 CopyBuffer 的行为。
- 计算与均线的偏差:
a1:当前收盘价减去当前 LWMA;
a2:一个周期前的开盘价减去当时的 LWMA;
a3:两个周期前的开盘价减去当时的 LWMA;
a4:三个周期前的开盘价减去当时的 LWMA。
- 对应感知器按照
result = Σ(wi × ai) 计算输出,每个权重等于原始参数(例如 X11)减去 100,这与 MQL 版本中的 w = x - 100 完全一致。
- 根据
PassMode 决定如何解释感知器结果:
1 – 只使用第一组权重;
2 – 只使用第二组权重;
3 – 只有当两组同时给出相同的非零符号时才生成信号。
- 结果为负时建立或维持多头,结果为正时建立或维持空头,结果为零时视作无共识并尝试在有浮盈时平仓。
仓位管理
- 入场:策略使用固定的
TradeVolume。开多之前若存在空头,将先以相同数量买入对冲;开空时也采取同样处理,从而保证同一时间只有一个方向的仓位。
- 止损:
StopLossPips 会根据 Security.PriceStep 换算成绝对价格距离。若标的报价保留 3 或 5 位小数,会额外乘以 10,以还原原始 EA 的 “adjusted point” 逻辑。止损在每根完成的烛线上检查,一旦烛线最低价(多头)或最高价(空头)触碰到止损价位,就用市价单离场。
- 移动止损:当
TrailingStopPips 大于零时启用。价格向有利方向移动超过 TrailingStopPips + TrailingStepPips 后,止损将被推进到 收盘价 ± TrailingStopPips。即便初始止损为零也会创建移动止损,与 EA 中的 PositionModify 相同。移动止损在烛线收盘时更新。
- 盈利退出:当两个感知器均给出零信号时,策略只会在浮动收益为正的情况下主动平仓,对应原版
CloseProfitPositions 中 “盈利+掉期+佣金 > 0” 的判定。
参数
| 参数 |
默认值 |
说明 |
TradeVolume |
1 |
新建仓位的基本手数,反向信号会先平掉已有仓位再开新单。 |
StopLossPips |
150 |
初始止损距离(调整后的点)。设为 0 可关闭初始止损。 |
TrailingStopPips |
25 |
移动止损距离(调整后的点)。设为 0 可关闭移动止损。 |
TrailingStepPips |
5 |
移动止损推进前需要的额外获利距离。 |
MaPeriod |
20 |
加权移动平均线周期。 |
CandleType |
H1 |
计算所用的烛线类型,可根据数据源支持的周期修改。 |
PassMode |
1 |
决定使用哪组感知器:1 – 第一组;2 – 第二组;3 – 两组都同意时才行动。 |
X11, X21, X31, X41 |
100 |
感知器 #1 的原始权重值,实际使用前会自动减去 100。 |
X12, X22, X32, X42 |
100 |
感知器 #2 的原始权重值,处理方式与第一组相同。 |
移植说明
- 原 EA 在每个 Tick 上调整止损;StockSharp 版本在烛线收盘时执行同样的逻辑,以保持在高层 API 内实现。
CMoneyFixedMargin 资金管理被固定手数 TradeVolume 所取代,如需风险模型可在外部包装。
- 感知器计算使用有限长度的列表缓存烛线和指标值,无需调用
CopyBuffer。
- 点值换算遵循 MetaTrader 的 “adjusted point” 规则,对三位或五位报价自动乘以 10。
使用建议
- 在终端中选择交易品种并设置与原 MT5 图表一致的
CandleType。
- 将感知器权重
X** 与 PassMode 调整为在 MetaTrader 中优化得到的组合,也可以在 StockSharp 内继续优化。
- 根据经纪商最小手数及步长设定
TradeVolume。策略在反手时会自动加上已有反向仓位的绝对值。
- 关注日志输出,移动止损调整和止损触发都会写入日志,方便对照原始 EA 的行为。
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 GoldDustStrategy : 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 GoldDustStrategy()
{
_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 gold_dust_strategy(Strategy):
def __init__(self):
super(gold_dust_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(gold_dust_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(gold_dust_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 gold_dust_strategy()