Psar Bug 策略
概述
Psar Bug 策略 来自 MetaTrader 4 专家顾问 pSAR_bug.mq4,核心思想是在抛物线 SAR 第一次翻转到价格另一侧时立即反手。StockSharp 版本订阅蜡烛数据,只在蜡烛完成后计算,并借助高级 API 下达市价单,同时自动维护止损和止盈。
交易逻辑
- 按可配置的加速因子(默认
0.02)和最大加速因子(默认0.2)计算抛物线 SAR。 - 只在蜡烛状态为
Finished时评估信号:- 做多信号:当前 SAR 低于收盘价,且上一根蜡烛的 SAR 高于上一根收盘价,意味着指标从上方翻转到下方。
- 做空信号:当前 SAR 高于收盘价,且上一根蜡烛的 SAR 低于上一根收盘价,意味着指标从下方翻转到上方。
- 每次出现信号时都将仓位反向:出现买入信号时平掉所有空头并以设定手数开多,卖出信号时执行相反操作。
- 使用以最小报价步长表示的固定止损与止盈距离。通过
StartProtection初始化保护参数,平台会自动为每一笔新仓位附加对应的风险控制。
参数说明
| 名称 | 描述 |
|---|---|
TradeVolume |
下单手数,默认 0.1 手。 |
StopLossPoints |
止损距离,按照价格步长计量,对应原版 StopLoss 输入。 |
TakeProfitPoints |
止盈距离,按照价格步长计量,对应原版 TakeProfit 输入。 |
SarAccelerationStep |
抛物线 SAR 的初始加速因子。 |
SarAccelerationMax |
抛物线 SAR 的最大加速因子。 |
CandleType |
指标计算使用的蜡烛类型(时间框架),默认 15 分钟。 |
转换要点
- 原始 EA 直接使用图表上的周期与品种,迁移版将时间框架暴露为参数,方便在 Backtester 或 Designer 中调整。
- 止损与止盈以绝对价格位移表示,并在启动时一次性配置到保护模块中。
- 通过净额逻辑实现“先平仓再开仓”的效果:当出现反向信号时,买入
Volume + |Position|手可以同时平掉已有仓位并建立新的方向,从而复现 MetaTrader 的处理方式。
使用步骤
- 在 StockSharp Designer 或 Backtester 中选择交易品种、
CandleType以及风险参数。 - 确保数据源可用后启动策略;策略只在蜡烛收盘后触发信号。
- 借助平台提供的图表功能观察蜡烛、抛物线 SAR 以及成交记录,以验证翻转逻辑的执行情况。
using System;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// PsarBug: EMA trend with RSI confirmation and ATR stops.
/// </summary>
public class PsarBugStrategy : Strategy
{
private readonly StrategyParam<DataType> _candleType;
private readonly StrategyParam<int> _emaLength;
private readonly StrategyParam<int> _rsiLength;
private readonly StrategyParam<int> _atrLength;
private decimal _prevClose;
private decimal _entryPrice;
public PsarBugStrategy()
{
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(8).TimeFrame())
.SetDisplay("Candle Type", "Timeframe.", "General");
_emaLength = Param(nameof(EmaLength), 30)
.SetDisplay("EMA Length", "Trend filter.", "Indicators");
_rsiLength = Param(nameof(RsiLength), 14)
.SetDisplay("RSI Length", "RSI period.", "Indicators");
_atrLength = Param(nameof(AtrLength), 14)
.SetDisplay("ATR Length", "ATR period.", "Indicators");
}
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public int EmaLength
{
get => _emaLength.Value;
set => _emaLength.Value = value;
}
public int RsiLength
{
get => _rsiLength.Value;
set => _rsiLength.Value = value;
}
public int AtrLength
{
get => _atrLength.Value;
set => _atrLength.Value = value;
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_prevClose = 0;
_entryPrice = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_prevClose = 0;
_entryPrice = 0;
var ema = new ExponentialMovingAverage { Length = EmaLength };
var rsi = new RelativeStrengthIndex { Length = RsiLength };
var atr = new AverageTrueRange { Length = AtrLength };
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(ema, rsi, atr, ProcessCandle)
.Start();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, ema);
DrawOwnTrades(area);
}
}
private void ProcessCandle(ICandleMessage candle, decimal emaVal, decimal rsiVal, decimal atrVal)
{
if (candle.State != CandleStates.Finished)
return;
var close = candle.ClosePrice;
if (_prevClose == 0 || atrVal <= 0)
{
_prevClose = close;
return;
}
if (Position > 0)
{
if (close >= _entryPrice + atrVal * 2.5m || close <= _entryPrice - atrVal * 1.5m || close < emaVal)
{
SellMarket();
_entryPrice = 0;
}
}
else if (Position < 0)
{
if (close <= _entryPrice - atrVal * 2.5m || close >= _entryPrice + atrVal * 1.5m || close > emaVal)
{
BuyMarket();
_entryPrice = 0;
}
}
if (Position == 0)
{
if (close > emaVal && _prevClose <= emaVal && rsiVal > 50)
{
_entryPrice = close;
BuyMarket();
}
else if (close < emaVal && _prevClose >= emaVal && rsiVal < 50)
{
_entryPrice = close;
SellMarket();
}
}
_prevClose = close;
}
}
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.Strategies import Strategy
from StockSharp.Algo.Indicators import ExponentialMovingAverage, RelativeStrengthIndex, AverageTrueRange
class psar_bug_strategy(Strategy):
def __init__(self):
super(psar_bug_strategy, self).__init__()
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(8))) \
.SetDisplay("Candle Type", "Timeframe.", "General")
self._ema_length = self.Param("EmaLength", 30) \
.SetDisplay("EMA Length", "Trend filter.", "Indicators")
self._rsi_length = self.Param("RsiLength", 14) \
.SetDisplay("RSI Length", "RSI period.", "Indicators")
self._atr_length = self.Param("AtrLength", 14) \
.SetDisplay("ATR Length", "ATR period.", "Indicators")
self._prev_close = 0.0
self._entry_price = 0.0
@property
def CandleType(self):
return self._candle_type.Value
@property
def EmaLength(self):
return self._ema_length.Value
@property
def RsiLength(self):
return self._rsi_length.Value
@property
def AtrLength(self):
return self._atr_length.Value
def OnStarted2(self, time):
super(psar_bug_strategy, self).OnStarted2(time)
self._prev_close = 0.0
self._entry_price = 0.0
self._ema = ExponentialMovingAverage()
self._ema.Length = self.EmaLength
self._rsi = RelativeStrengthIndex()
self._rsi.Length = self.RsiLength
self._atr = AverageTrueRange()
self._atr.Length = self.AtrLength
subscription = self.SubscribeCandles(self.CandleType)
subscription.Bind(self._ema, self._rsi, self._atr, self.ProcessCandle).Start()
def ProcessCandle(self, candle, ema_val, rsi_val, atr_val):
if candle.State != CandleStates.Finished:
return
ev = float(ema_val)
rv = float(rsi_val)
av = float(atr_val)
close = float(candle.ClosePrice)
if self._prev_close == 0 or av <= 0:
self._prev_close = close
return
if self.Position > 0:
if close >= self._entry_price + av * 2.5 or close <= self._entry_price - av * 1.5 or close < ev:
self.SellMarket()
self._entry_price = 0.0
elif self.Position < 0:
if close <= self._entry_price - av * 2.5 or close >= self._entry_price + av * 1.5 or close > ev:
self.BuyMarket()
self._entry_price = 0.0
if not self.IsFormedAndOnlineAndAllowTrading():
self._prev_close = close
return
if self.Position == 0:
if close > ev and self._prev_close <= ev and rv > 50:
self._entry_price = close
self.BuyMarket()
elif close < ev and self._prev_close >= ev and rv < 50:
self._entry_price = close
self.SellMarket()
self._prev_close = close
def OnReseted(self):
super(psar_bug_strategy, self).OnReseted()
self._prev_close = 0.0
self._entry_price = 0.0
def CreateClone(self):
return psar_bug_strategy()