订单情绪策略
概述
该策略根据盘口中买单和卖单的失衡进行交易。它计算双方的订单数量和总成交量比值,当某一方的优势超过设定阈值时开仓。策略只在指定的时间窗口内运行。
开仓后会降低阈值来监控相反的一方。如果相反一方超过这些降低后的阈值则平仓。同时使用以价格点表示的止损和止盈。
交易规则
- 做多入场:
买量 / 卖量 >= DiffVolumesEx且买单数 / 卖单数 >= DiffTradersEx- 任意一侧满足
MinTraders与MinVolume - 当前时间通过
CheckTradingTime
- 做空入场:使用对称逻辑判断卖方优势。
- 平仓:
- 多单在
卖量 / 买量 > 1 / DiffVolumes或卖单数 / 买单数 > 1 / DiffTraders时平仓 - 空单在
卖量 / 买量 < DiffVolumes或卖单数 / 买单数 < DiffTraders时平仓 - 交易时间之外全部平仓
- 多单在
- 止损:使用以价格点计算的止损和止盈。
参数
MinVolume– 任一侧所需的最小成交量(默认 20000)MinTraders– 任一侧所需的最小订单数量(默认 1000)DiffVolumesEx– 入场所需的成交量比(默认 2.0)DiffTradersEx– 入场所需的订单数量比(默认 1.5)MinDiffVolumesEx– 开仓后用于监控的成交量比(默认 1.5)MinDiffTradersEx– 开仓后用于监控的订单数量比(默认 1.3)SleepMinutes– 盘口检查的间隔分钟数(默认 5)TpPips– 止盈价差(默认 500)SlPips– 止损价差(默认 500)
说明
本策略暂不提供 Python 版本。
using System;
using System.Linq;
using System.Collections.Generic;
using Ecng.Common;
using Ecng.Collections;
using Ecng.Serialization;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Strategy trading on volume sentiment using candle data.
/// Compares bullish vs bearish volume over a lookback period.
/// </summary>
public class SessionOrderSentimentStrategy : Strategy
{
private readonly StrategyParam<decimal> _volumeRatio;
private readonly StrategyParam<int> _lookback;
private readonly StrategyParam<decimal> _stopLossPct;
private readonly StrategyParam<DataType> _candleType;
private readonly List<(decimal vol, bool isBull)> _volumeHistory = new();
private decimal _entryPrice;
/// <summary>
/// Volume ratio required for entry.
/// </summary>
public decimal VolumeRatio
{
get => _volumeRatio.Value;
set => _volumeRatio.Value = value;
}
/// <summary>
/// Lookback period in candles.
/// </summary>
public int Lookback
{
get => _lookback.Value;
set => _lookback.Value = value;
}
/// <summary>
/// Stop loss percentage.
/// </summary>
public decimal StopLossPct
{
get => _stopLossPct.Value;
set => _stopLossPct.Value = value;
}
/// <summary>
/// Candle type for processing.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Initialize <see cref="SessionOrderSentimentStrategy"/>.
/// </summary>
public SessionOrderSentimentStrategy()
{
_volumeRatio = Param(nameof(VolumeRatio), 1.5m)
.SetDisplay("Volume Ratio", "Bull/bear volume ratio for entry", "General")
.SetGreaterThanZero();
_lookback = Param(nameof(Lookback), 10)
.SetDisplay("Lookback", "Number of candles to look back", "General")
.SetGreaterThanZero();
_stopLossPct = Param(nameof(StopLossPct), 1m)
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk")
.SetGreaterThanZero();
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Timeframe for analysis", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
var subscription = SubscribeCandles(CandleType);
subscription
.Bind(ProcessCandle)
.Start();
}
private void ProcessCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
var isBull = candle.ClosePrice >= candle.OpenPrice;
_volumeHistory.Add((candle.TotalVolume, isBull));
if (_volumeHistory.Count > Lookback)
_volumeHistory.RemoveAt(0);
if (_volumeHistory.Count < Lookback)
return;
var bullVolume = 0m;
var bearVolume = 0m;
foreach (var (vol, bull) in _volumeHistory)
{
if (bull)
bullVolume += vol;
else
bearVolume += vol;
}
if (bearVolume == 0) bearVolume = 1;
if (bullVolume == 0) bullVolume = 1;
var bullBearRatio = bullVolume / bearVolume;
var bearBullRatio = bearVolume / bullVolume;
var close = candle.ClosePrice;
// Check stop loss
if (Position > 0 && close <= _entryPrice * (1m - StopLossPct / 100m))
{
SellMarket();
return;
}
if (Position < 0 && close >= _entryPrice * (1m + StopLossPct / 100m))
{
BuyMarket();
return;
}
// Bullish sentiment
if (bullBearRatio >= VolumeRatio)
{
if (Position < 0)
{
BuyMarket();
}
if (Position <= 0)
{
_entryPrice = close;
BuyMarket();
}
}
// Bearish sentiment
else if (bearBullRatio >= VolumeRatio)
{
if (Position > 0)
{
SellMarket();
}
if (Position >= 0)
{
_entryPrice = close;
SellMarket();
}
}
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_volumeHistory.Clear();
_entryPrice = 0m;
}
}
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
class session_order_sentiment_strategy(Strategy):
def __init__(self):
super(session_order_sentiment_strategy, self).__init__()
self._volume_ratio = self.Param("VolumeRatio", 1.5) \
.SetDisplay("Volume Ratio", "Bull/bear volume ratio for entry", "General")
self._lookback = self.Param("Lookback", 10) \
.SetDisplay("Lookback", "Number of candles to look back", "General")
self._stop_loss_pct = self.Param("StopLossPct", 1.0) \
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Timeframe for analysis", "General")
self._volume_history = []
self._entry_price = 0.0
@property
def volume_ratio(self):
return self._volume_ratio.Value
@property
def lookback(self):
return self._lookback.Value
@property
def stop_loss_pct(self):
return self._stop_loss_pct.Value
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(session_order_sentiment_strategy, self).OnReseted()
self._volume_history = []
self._entry_price = 0.0
def OnStarted2(self, time):
super(session_order_sentiment_strategy, self).OnStarted2(time)
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(self.process_candle).Start()
def process_candle(self, candle):
if candle.State != CandleStates.Finished:
return
is_bull = float(candle.ClosePrice) >= float(candle.OpenPrice)
vol = float(candle.TotalVolume)
lb = int(self.lookback)
self._volume_history.append((vol, is_bull))
if len(self._volume_history) > lb:
self._volume_history.pop(0)
if len(self._volume_history) < lb:
return
bull_volume = 0.0
bear_volume = 0.0
for v, b in self._volume_history:
if b:
bull_volume += v
else:
bear_volume += v
if bear_volume == 0:
bear_volume = 1.0
if bull_volume == 0:
bull_volume = 1.0
bull_bear_ratio = bull_volume / bear_volume
bear_bull_ratio = bear_volume / bull_volume
close = float(candle.ClosePrice)
sl = float(self.stop_loss_pct)
vr = float(self.volume_ratio)
# Check stop loss
if self.Position > 0 and close <= self._entry_price * (1.0 - sl / 100.0):
self.SellMarket()
return
if self.Position < 0 and close >= self._entry_price * (1.0 + sl / 100.0):
self.BuyMarket()
return
# Bullish sentiment
if bull_bear_ratio >= vr:
if self.Position < 0:
self.BuyMarket()
if self.Position <= 0:
self._entry_price = close
self.BuyMarket()
# Bearish sentiment
elif bear_bull_ratio >= vr:
if self.Position > 0:
self.SellMarket()
if self.Position >= 0:
self._entry_price = close
self.SellMarket()
def CreateClone(self):
return session_order_sentiment_strategy()