MTF RSI SAR 策略
该策略结合四个周期的 RSI、Parabolic SAR 和 布林带,用于在短期回调后捕捉趋势延续。信号基于 5 分钟K线,更高周期仅用于过滤和确认。
概念
- RSI 过滤 – 5、15、30、60 分钟 RSI 全部高于 50 时做多,全部低于 50 时做空,以保证交易方向与更大级别趋势一致。
- Parabolic SAR 过滤 – 5、15、30 分钟 SAR 点位在当前K线下方做多,在上方做空,确认价格运行方向。
- 布林带触发 – 5 分钟K线收盘价突破上轨触发做多,跌破下轨触发做空,提供超买/超卖信号。
- 入场与出场 – 当所有启用的过滤器同向时开仓,反向信号出现时平仓。
三个过滤器均可通过参数单独关闭,可实现仅用 RSI、仅用布林带或仅用 SAR 的模式。
参数
UseRsi– 启用 RSI 过滤(默认:true)UseBollinger– 启用布林带触发(默认:true)UseSar– 启用 Parabolic SAR 过滤(默认:true)RsiPeriod– RSI 计算周期(默认:14)BollingerPeriod– 布林带周期(默认:20)BollingerWidth– 布林带宽度(标准差倍数,默认:2)SarStep– Parabolic SAR 加速因子(默认:0.02)SarMax– Parabolic SAR 最大加速(默认:0.2)CandleType– 基础K线周期,默认 5 分钟
交易规则
- 多头:所有启用过滤器给出看涨信号。
- 空头:所有启用过滤器给出看跌信号。
- 退出:出现反向信号时平仓。
说明
- 策略对单一品种同时订阅 5、15、30、60 分钟四个周期。
- 用于展示如何利用 StockSharp 高级 API 实现多周期确认。
- 策略未设置固定止损和止盈,如需风险控制请另行添加。
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;
/// <summary>
/// RSI and Parabolic SAR strategy.
/// Buys when RSI below oversold and SAR below price; sells on opposite.
/// </summary>
public class MtfRsiSarStrategy : Strategy
{
private readonly StrategyParam<int> _rsiPeriod;
private readonly StrategyParam<decimal> _rsiOversold;
private readonly StrategyParam<decimal> _rsiOverbought;
private readonly StrategyParam<DataType> _candleType;
public int RsiPeriod { get => _rsiPeriod.Value; set => _rsiPeriod.Value = value; }
public decimal RsiOversold { get => _rsiOversold.Value; set => _rsiOversold.Value = value; }
public decimal RsiOverbought { get => _rsiOverbought.Value; set => _rsiOverbought.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public MtfRsiSarStrategy()
{
_rsiPeriod = Param(nameof(RsiPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("RSI Period", "RSI period", "Indicators");
_rsiOversold = Param(nameof(RsiOversold), 35m)
.SetDisplay("RSI Oversold", "RSI oversold level", "Indicators");
_rsiOverbought = Param(nameof(RsiOverbought), 65m)
.SetDisplay("RSI Overbought", "RSI overbought level", "Indicators");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var rsi = new RelativeStrengthIndex { Length = RsiPeriod };
var sar = new ParabolicSar();
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(rsi, sar, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal rsi, decimal sar)
{
if (candle.State != CandleStates.Finished)
return;
var close = candle.ClosePrice;
// Buy: RSI oversold + SAR below price
if (rsi < RsiOversold && sar < close)
{
if (Position < 0)
BuyMarket();
if (Position <= 0)
BuyMarket();
}
// Sell: RSI overbought + SAR above price
else if (rsi > RsiOverbought && sar > close)
{
if (Position > 0)
SellMarket();
if (Position >= 0)
SellMarket();
}
// Exit long when RSI overbought
else if (Position > 0 && rsi > RsiOverbought)
{
SellMarket();
}
// Exit short when RSI oversold
else if (Position < 0 && rsi < RsiOversold)
{
BuyMarket();
}
}
}
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 ParabolicSar, RelativeStrengthIndex
from StockSharp.Algo.Strategies import Strategy
class mtf_rsi_sar_strategy(Strategy):
def __init__(self):
super(mtf_rsi_sar_strategy, self).__init__()
self._rsi_period = self.Param("RsiPeriod", 14) \
.SetDisplay("RSI Period", "RSI period", "Indicators")
self._rsi_oversold = self.Param("RsiOversold", 35.0) \
.SetDisplay("RSI Oversold", "RSI oversold level", "Indicators")
self._rsi_overbought = self.Param("RsiOverbought", 65.0) \
.SetDisplay("RSI Overbought", "RSI overbought level", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles", "General")
@property
def rsi_period(self):
return self._rsi_period.Value
@property
def rsi_oversold(self):
return self._rsi_oversold.Value
@property
def rsi_overbought(self):
return self._rsi_overbought.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnStarted2(self, time):
super(mtf_rsi_sar_strategy, self).OnStarted2(time)
rsi = RelativeStrengthIndex()
rsi.Length = self.rsi_period
sar = ParabolicSar()
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(rsi, sar, self.on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def on_process(self, candle, rsi, sar):
if candle.State != CandleStates.Finished:
return
close = candle.ClosePrice
# Buy: RSI oversold + SAR below price
if rsi < self.rsi_oversold and sar < close:
if self.Position < 0:
self.BuyMarket()
if self.Position <= 0:
self.BuyMarket()
# Sell: RSI overbought + SAR above price
elif rsi > self.rsi_overbought and sar > close:
if self.Position > 0:
self.SellMarket()
if self.Position >= 0:
self.SellMarket()
# Exit long when RSI overbought
elif self.Position > 0 and rsi > self.rsi_overbought:
self.SellMarket()
# Exit short when RSI oversold
elif self.Position < 0 and rsi < self.rsi_oversold:
self.BuyMarket()
def CreateClone(self):
return mtf_rsi_sar_strategy()