News Trading EA Strategy
基于新闻事件的时间型对冲策略。在预定时间于当前价格上下固定距离同时挂出买入止损和卖出止损订单。在激活窗口内,每根K线更新订单以跟随价格。若有持仓,则取消相反的挂单,并根据止盈、止损或订单到期退出。
详情
- 入场条件:
- 在对冲窗口内于 close + Distance * step 挂买入止损,在 close - Distance * step 挂卖出止损。
- 做多/做空:双向
- 出场条件:相反挂单、止盈/止损或订单到期
- 止损:固定止损与止盈
- 默认值:
StartDateTime= DateTime.NowStartStraddle= 0StopStraddle= 15Volume= 0.01mDistance= 55mTakeProfit= 30mStopLoss= 30mExpiration= 20CandleType= TimeSpan.FromMinutes(1).TimeFrame()
- 过滤:
- 类别: News
- 方向: 双向
- 指标: 无
- 止损: 有
- 复杂度: 初级
- 时间框架: 事件
- 季节性: 无
- 神经网络: 无
- 背离: 无
- 风险等级: 高
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>
/// Volatility breakout strategy using StdDev for big candle detection.
/// </summary>
public class NewsTradingEaStrategy : Strategy
{
private readonly StrategyParam<int> _stdDevPeriod;
private readonly StrategyParam<int> _emaPeriod;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevFast;
private decimal _prevSlow;
private bool _hasPrev;
public int StdDevPeriod { get => _stdDevPeriod.Value; set => _stdDevPeriod.Value = value; }
public int EmaPeriod { get => _emaPeriod.Value; set => _emaPeriod.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public NewsTradingEaStrategy()
{
_stdDevPeriod = Param(nameof(StdDevPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("StdDev Period", "Volatility period", "Indicators");
_emaPeriod = Param(nameof(EmaPeriod), 20)
.SetGreaterThanZero()
.SetDisplay("EMA Period", "EMA period", "Indicators");
_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();
_prevFast = 0;
_prevSlow = 0;
_hasPrev = false;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var fast = new ExponentialMovingAverage { Length = 12 };
var slow = new ExponentialMovingAverage { Length = EmaPeriod };
SubscribeCandles(CandleType)
.Bind(fast, slow, ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal fastVal, decimal slowVal)
{
if (candle.State != CandleStates.Finished) return;
if (!_hasPrev)
{
_prevFast = fastVal;
_prevSlow = slowVal;
_hasPrev = true;
return;
}
var crossUp = _prevFast <= _prevSlow && fastVal > slowVal;
var crossDown = _prevFast >= _prevSlow && fastVal < slowVal;
if (crossUp && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
}
else if (crossDown && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
}
_prevFast = fastVal;
_prevSlow = slowVal;
}
}
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 news_trading_ea_strategy(Strategy):
def __init__(self):
super(news_trading_ea_strategy, self).__init__()
self._std_dev_period = self.Param("StdDevPeriod", 14) \
.SetDisplay("StdDev Period", "Volatility period", "Indicators")
self._ema_period = self.Param("EmaPeriod", 20) \
.SetDisplay("EMA Period", "EMA period", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Candle type", "General")
self._prev_fast = 0.0
self._prev_slow = 0.0
self._has_prev = False
@property
def std_dev_period(self):
return self._std_dev_period.Value
@property
def ema_period(self):
return self._ema_period.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(news_trading_ea_strategy, self).OnReseted()
self._prev_fast = 0.0
self._prev_slow = 0.0
self._has_prev = False
def OnStarted2(self, time):
super(news_trading_ea_strategy, self).OnStarted2(time)
fast = ExponentialMovingAverage()
fast.Length = 12
slow = ExponentialMovingAverage()
slow.Length = self.ema_period
self.SubscribeCandles(self.candle_type).Bind(fast, slow, self.process_candle).Start()
def process_candle(self, candle, fast_val, slow_val):
if candle.State != CandleStates.Finished:
return
fv = float(fast_val)
sv = float(slow_val)
if not self._has_prev:
self._prev_fast = fv
self._prev_slow = sv
self._has_prev = True
return
cross_up = self._prev_fast <= self._prev_slow and fv > sv
cross_down = self._prev_fast >= self._prev_slow and fv < sv
if cross_up and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
elif cross_down and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._prev_fast = fv
self._prev_slow = sv
def CreateClone(self):
return news_trading_ea_strategy()