News Pending Orders 策略
该策略在当前价格附近同时挂出买入和卖出止损单,并随着市场变化自动管理这些订单。适用于新闻发布时预期出现剧烈波动的情况。
工作原理
- 当没有持仓时,策略会挂出:
- 价格为
Ask + Step的 买入止损单; - 价格为
Bid - Step的 卖出止损单。
- 价格为
- 如果市场移动至少
StepTrail,则每隔TimeModify秒重新调整挂单价格。 - 当其中一单被触发后,另一单会被取消。
- 根据开仓价设置保护性的止损和可选的止盈。
- 达到指定盈利后,止损可移动到保本价并继续跟随价格移动。
策略只使用 Level1 数据,不依赖任何指标。
参数
| 参数 | 默认值 | 说明 |
|---|---|---|
Step |
10 | 挂出止损单的距离(以跳动为单位)。 |
StopLoss |
10 | 初始止损(跳动)。 |
TakeProfit |
50 | 止盈(跳动,0 表示不使用)。 |
TrailingStop |
10 | 跟踪止损距离(跳动)。 |
TrailingStart |
0 | 激活跟踪所需的盈利(跳动)。 |
StepTrail |
2 | 移动止损所需的最小变化(跳动)。 |
BreakEven |
false | 达到 MinProfitBreakEven 后将止损移至开仓价。 |
MinProfitBreakEven |
0 | 移至保本所需盈利(跳动)。 |
TimeModify |
30 | 调整挂单价格的时间间隔(秒)。 |
说明
- 订单管理基于 StockSharp 的高级 API。
- 平仓后会取消所有保护性订单。
- 仅提供 C# 版本,未包含 Python 实现。
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>
/// News-style volatility breakout strategy.
/// Enters on ATR expansion with momentum confirmation via EMA.
/// </summary>
public class NewsPendingOrdersStrategy : Strategy
{
private readonly StrategyParam<int> _emaPeriod;
private readonly StrategyParam<int> _atrPeriod;
private readonly StrategyParam<decimal> _atrMult;
private readonly StrategyParam<DataType> _candleType;
private decimal _prevAtr;
private decimal _entryPrice;
public int EmaPeriod { get => _emaPeriod.Value; set => _emaPeriod.Value = value; }
public int AtrPeriod { get => _atrPeriod.Value; set => _atrPeriod.Value = value; }
public decimal AtrMult { get => _atrMult.Value; set => _atrMult.Value = value; }
public DataType CandleType { get => _candleType.Value; set => _candleType.Value = value; }
public NewsPendingOrdersStrategy()
{
_emaPeriod = Param(nameof(EmaPeriod), 10)
.SetGreaterThanZero()
.SetDisplay("EMA Period", "EMA trend period", "Indicators");
_atrPeriod = Param(nameof(AtrPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("ATR Period", "ATR period", "Indicators");
_atrMult = Param(nameof(AtrMult), 1.5m)
.SetDisplay("ATR Mult", "ATR expansion multiplier", "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 OnReseted()
{
base.OnReseted();
_prevAtr = 0;
_entryPrice = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var ema = new ExponentialMovingAverage { Length = EmaPeriod };
var atr = new StandardDeviation { Length = AtrPeriod };
SubscribeCandles(CandleType).Bind(ema, atr, ProcessCandle).Start();
}
private void ProcessCandle(ICandleMessage candle, decimal ema, decimal atr)
{
if (candle.State != CandleStates.Finished) return;
if (_prevAtr <= 0) { _prevAtr = atr; return; }
var close = candle.ClosePrice;
var bodySize = Math.Abs(candle.ClosePrice - candle.OpenPrice);
// Volatility expansion: big body candle relative to stddev
var expansion = bodySize > atr * 0.5m;
if (expansion && close > ema && Position <= 0)
{
if (Position < 0) BuyMarket();
BuyMarket();
_entryPrice = close;
}
else if (expansion && close < ema && Position >= 0)
{
if (Position > 0) SellMarket();
SellMarket();
_entryPrice = close;
}
// Exit long
else if (Position > 0)
{
if (close < ema || (_entryPrice > 0 && close <= _entryPrice - atr * 2))
{
SellMarket();
_entryPrice = 0;
}
}
// Exit short
else if (Position < 0)
{
if (close > ema || (_entryPrice > 0 && close >= _entryPrice + atr * 2))
{
BuyMarket();
_entryPrice = 0;
}
}
_prevAtr = atr;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates
from StockSharp.Algo.Indicators import ExponentialMovingAverage, StandardDeviation
from StockSharp.Algo.Strategies import Strategy
class news_pending_orders_strategy(Strategy):
def __init__(self):
super(news_pending_orders_strategy, self).__init__()
self._ema_period = self.Param("EmaPeriod", 10) \
.SetDisplay("EMA Period", "EMA trend period", "Indicators")
self._atr_period = self.Param("AtrPeriod", 14) \
.SetDisplay("ATR Period", "ATR period", "Indicators")
self._atr_mult = self.Param("AtrMult", 1.5) \
.SetDisplay("ATR Mult", "ATR expansion multiplier", "Indicators")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Type of candles", "General")
self._prev_atr = 0.0
self._entry_price = 0.0
@property
def ema_period(self):
return self._ema_period.Value
@property
def atr_period(self):
return self._atr_period.Value
@property
def atr_mult(self):
return self._atr_mult.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(news_pending_orders_strategy, self).OnReseted()
self._prev_atr = 0.0
self._entry_price = 0.0
def OnStarted2(self, time):
super(news_pending_orders_strategy, self).OnStarted2(time)
ema = ExponentialMovingAverage()
ema.Length = self.ema_period
atr = StandardDeviation()
atr.Length = self.atr_period
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(ema, atr, self.on_process).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawOwnTrades(area)
def on_process(self, candle, ema, atr):
if candle.State != CandleStates.Finished:
return
if self._prev_atr <= 0:
self._prev_atr = atr
return
close = candle.ClosePrice
body_size = abs(float(candle.ClosePrice) - float(candle.OpenPrice))
# Volatility expansion: big body candle relative to stddev
expansion = body_size > atr * 0.5
if expansion and close > ema and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = close
elif expansion and close < ema and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = close
# Exit long
elif self.Position > 0:
if close < ema or (self._entry_price > 0 and close <= self._entry_price - atr * 2):
self.SellMarket()
self._entry_price = 0
# Exit short
elif self.Position < 0:
if close > ema or (self._entry_price > 0 and close >= self._entry_price + atr * 2):
self.BuyMarket()
self._entry_price = 0
self._prev_atr = atr
def CreateClone(self):
return news_pending_orders_strategy()