Swing Cyborg 策略
概述
Swing Cyborg 是一种辅助型策略,根据交易者对中长期趋势的主观判断来执行交易。用户设置预期的趋势方向以及该趋势有效的时间段,策略使用 RSI 指标确认入场并通过固定的目标管理退出。
参数
Volume– 下单手数。TrendPrediction– 预期趋势方向(Uptrend 或 Downtrend)。TrendTimeframe– 用于计算 RSI 和交易的时间周期(M30、H1 或 H4)。TrendStart– 趋势开始时间。TrendEnd– 趋势结束时间。Aggressiveness– 资金管理等级:- 低:止盈 300 点,止损 200 点。
- 中:止盈 500 点,止损 250 点。
- 高:止盈 600 点,止损 300 点。
交易逻辑
- 等待所选周期形成新的蜡烛。
- 仅在当前时间位于
TrendStart和TrendEnd之间时交易。 - 计算 RSI(14)。
- 若没有持仓:
TrendPrediction为 Uptrend 且 RSI ≤ 65 时买入。TrendPrediction为 Downtrend 且 RSI ≥ 35 时卖出。
- 使用
StartProtection在达到预设盈利或亏损点数时自动平仓。
策略仅在蜡烛收盘后作出决策,并且在持有仓位时不会开立新的仓位。
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>
/// SwingCyborg strategy using RSI overbought/oversold levels.
/// </summary>
public class SwingCyborgStrategy : Strategy
{
private readonly StrategyParam<int> _rsiPeriod;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevRsi;
private bool _hasPrev;
public int RsiPeriod { get => _rsiPeriod.Value; set => _rsiPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public SwingCyborgStrategy()
{
_rsiPeriod = Param(nameof(RsiPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("RSI Period", "RSI period", "Parameters");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Candle type", "General");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
=> [(Security, CandleType)];
protected override void OnReseted()
{
base.OnReseted();
_prevRsi = 0;
_hasPrev = false;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var rsi = new RelativeStrengthIndex { Length = RsiPeriod };
SubscribeCandles(CandleType)
.Bind(rsi, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal rsiVal)
{
if (candle.State != CandleStates.Finished) return;
if (!_hasPrev)
{
_prevRsi = rsiVal;
_hasPrev = true;
return;
}
// Buy when RSI exits oversold
if (_prevRsi <= 30m && rsiVal > 30m && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
// Sell when RSI exits overbought
else if (_prevRsi >= 70m && rsiVal < 70m && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_prevRsi = rsiVal;
}
}
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 RelativeStrengthIndex
from StockSharp.Algo.Strategies import Strategy
class swing_cyborg_strategy(Strategy):
def __init__(self):
super(swing_cyborg_strategy, self).__init__()
self._rsi_period = self.Param("RsiPeriod", 14) \
.SetDisplay("RSI Period", "RSI period", "Parameters")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Candle type", "General")
self._prev_rsi = 0.0
self._has_prev = False
@property
def rsi_period(self):
return self._rsi_period.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(swing_cyborg_strategy, self).OnReseted()
self._prev_rsi = 0.0
self._has_prev = False
def OnStarted2(self, time):
super(swing_cyborg_strategy, self).OnStarted2(time)
rsi = RelativeStrengthIndex()
rsi.Length = self.rsi_period
self.SubscribeCandles(self.candle_type) \
.Bind(rsi, self.process_candle) \
.Start()
def process_candle(self, candle, rsi_val):
if candle.State != CandleStates.Finished:
return
rsi_val = float(rsi_val)
if not self._has_prev:
self._prev_rsi = rsi_val
self._has_prev = True
return
if self._prev_rsi <= 30.0 and rsi_val > 30.0 and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif self._prev_rsi >= 70.0 and rsi_val < 70.0 and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._prev_rsi = rsi_val
def CreateClone(self):
return swing_cyborg_strategy()