股票短期反转
股票短期反转 策略将均值回归应用于股票。每天买入上一周跌幅最大的股票并做空涨幅最大的股票,押注短暂的反转。
持仓仅持续几天,然后重新评估。
细节
- 入场条件:根据上一周收益进行每日排序。
- 多空方向:双向。
- 出场条件:持有几天或排名更新时平仓。
- 止损:可采用基于波动率的止损。
- 默认值:
CandleType = TimeSpan.FromMinutes(5).TimeFrame()
- 筛选:
- 分类:均值回归
- 方向:双向
- 指标:价格
- 止损:有
- 复杂度:基础
- 时间框架:短期
- 季节性:否
- 神经网络:否
- 背离:否
- 风险级别:中等
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Configuration;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// Short-term reversal strategy for stocks that trades the primary stock when its recent return overshoots or undershoots a benchmark stock.
/// </summary>
public class ShortTermReversalStocksStrategy : Strategy
{
private readonly StrategyParam<string> _security2Id;
private readonly StrategyParam<int> _lookbackPeriod;
private readonly StrategyParam<int> _normalizationPeriod;
private readonly StrategyParam<decimal> _entryThreshold;
private readonly StrategyParam<decimal> _exitThreshold;
private readonly StrategyParam<int> _cooldownBars;
private readonly StrategyParam<decimal> _stopLoss;
private readonly StrategyParam<DataType> _candleType;
private Security _benchmark = null!;
private RateOfChange _primaryReturn = null!;
private RateOfChange _benchmarkReturn = null!;
private SimpleMovingAverage _spreadAverage = null!;
private StandardDeviation _spreadDeviation = null!;
private decimal _latestPrimaryReturn;
private decimal _latestBenchmarkReturn;
private decimal? _previousZScore;
private bool _primaryUpdated;
private bool _benchmarkUpdated;
private int _cooldownRemaining;
public string Security2Id
{
get => _security2Id.Value;
set => _security2Id.Value = value;
}
public int LookbackPeriod
{
get => _lookbackPeriod.Value;
set => _lookbackPeriod.Value = value;
}
public int NormalizationPeriod
{
get => _normalizationPeriod.Value;
set => _normalizationPeriod.Value = value;
}
public decimal EntryThreshold
{
get => _entryThreshold.Value;
set => _entryThreshold.Value = value;
}
public decimal ExitThreshold
{
get => _exitThreshold.Value;
set => _exitThreshold.Value = value;
}
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
public decimal StopLoss
{
get => _stopLoss.Value;
set => _stopLoss.Value = value;
}
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public ShortTermReversalStocksStrategy()
{
_security2Id = Param(nameof(Security2Id), Paths.HistoryDefaultSecurity2)
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General");
_lookbackPeriod = Param(nameof(LookbackPeriod), 5)
.SetRange(2, 40)
.SetDisplay("Lookback Period", "Recent return lookback period", "Indicators");
_normalizationPeriod = Param(nameof(NormalizationPeriod), 16)
.SetRange(5, 120)
.SetDisplay("Normalization Period", "Lookback period used to normalize the reversal spread", "Indicators");
_entryThreshold = Param(nameof(EntryThreshold), 1.1m)
.SetRange(0.2m, 5m)
.SetDisplay("Entry Threshold", "Z-score threshold required to open a position", "Signals");
_exitThreshold = Param(nameof(ExitThreshold), 0.25m)
.SetRange(0m, 2m)
.SetDisplay("Exit Threshold", "Z-score threshold required to close a position", "Signals");
_cooldownBars = Param(nameof(CooldownBars), 6)
.SetRange(0, 120)
.SetDisplay("Cooldown Bars", "Closed candles to wait before another position change", "Risk");
_stopLoss = Param(nameof(StopLoss), 3m)
.SetRange(0.5m, 10m)
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Time frame for candles", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
if (Security != null)
yield return (Security, CandleType);
if (!Security2Id.IsEmpty())
yield return (new Security { Id = Security2Id }, CandleType);
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_benchmark = null!;
_primaryReturn = null!;
_benchmarkReturn = null!;
_spreadAverage = null!;
_spreadDeviation = null!;
_latestPrimaryReturn = 0m;
_latestBenchmarkReturn = 0m;
_previousZScore = null;
_primaryUpdated = false;
_benchmarkUpdated = false;
_cooldownRemaining = 0;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
if (Security == null)
throw new InvalidOperationException("Primary security is not specified.");
if (Security2Id.IsEmpty())
throw new InvalidOperationException("Benchmark security identifier is not specified.");
_benchmark = this.LookupById(Security2Id) ?? new Security { Id = Security2Id };
_primaryReturn = new RateOfChange { Length = LookbackPeriod };
_benchmarkReturn = new RateOfChange { Length = LookbackPeriod };
_spreadAverage = new SimpleMovingAverage { Length = NormalizationPeriod };
_spreadDeviation = new StandardDeviation { Length = NormalizationPeriod };
var primarySubscription = SubscribeCandles(CandleType, security: Security);
var benchmarkSubscription = SubscribeCandles(CandleType, security: _benchmark);
primarySubscription.Bind(ProcessPrimaryCandle).Start();
benchmarkSubscription.Bind(ProcessBenchmarkCandle).Start();
StartProtection(new Unit(2, UnitTypes.Percent), new Unit(StopLoss, UnitTypes.Percent));
}
private void ProcessPrimaryCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
var value = _primaryReturn.Process(candle);
if (value.IsEmpty || !_primaryReturn.IsFormed)
return;
_latestPrimaryReturn = value.ToDecimal();
_primaryUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private void ProcessBenchmarkCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
var value = _benchmarkReturn.Process(candle);
if (value.IsEmpty || !_benchmarkReturn.IsFormed)
return;
_latestBenchmarkReturn = value.ToDecimal();
_benchmarkUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private void TryProcessSpread(DateTime time)
{
if (!_primaryUpdated || !_benchmarkUpdated)
return;
_primaryUpdated = false;
_benchmarkUpdated = false;
var spread = _latestPrimaryReturn - _latestBenchmarkReturn;
var mean = _spreadAverage.Process(spread, time, true).ToDecimal();
var deviation = _spreadDeviation.Process(spread, time, true).ToDecimal();
if (!_spreadAverage.IsFormed || !_spreadDeviation.IsFormed || deviation <= 0m)
return;
if (!IsFormedAndOnlineAndAllowTrading())
return;
if (_cooldownRemaining > 0)
_cooldownRemaining--;
var zScore = (spread - mean) / deviation;
var bullishEntry = _previousZScore is decimal previousBullish && previousBullish > -EntryThreshold && zScore <= -EntryThreshold;
var bearishEntry = _previousZScore is decimal previousBearish && previousBearish < EntryThreshold && zScore >= EntryThreshold;
if (_cooldownRemaining == 0 && Position == 0)
{
if (bullishEntry)
{
BuyMarket();
_cooldownRemaining = CooldownBars;
}
else if (bearishEntry)
{
SellMarket();
_cooldownRemaining = CooldownBars;
}
}
else if (Position > 0 && zScore >= -ExitThreshold)
{
SellMarket(Position);
_cooldownRemaining = CooldownBars;
}
else if (Position < 0 && zScore <= ExitThreshold)
{
BuyMarket(Math.Abs(Position));
_cooldownRemaining = CooldownBars;
}
_previousZScore = zScore;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.BusinessEntities")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
from System import TimeSpan, Math
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes
from StockSharp.Algo.Indicators import RateOfChange, SimpleMovingAverage, StandardDeviation, CandleIndicatorValue
from StockSharp.Algo.Strategies import Strategy
from StockSharp.BusinessEntities import Security
from indicator_extensions import *
class short_term_reversal_stocks_strategy(Strategy):
"""Short-term reversal strategy for stocks that trades the primary stock when its recent return overshoots or undershoots a benchmark stock."""
def __init__(self):
super(short_term_reversal_stocks_strategy, self).__init__()
self._security2_id = self.Param("Security2Id", "TONUSDT@BNBFT") \
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General")
self._lookback_period = self.Param("LookbackPeriod", 5) \
.SetRange(2, 40) \
.SetDisplay("Lookback Period", "Recent return lookback period", "Indicators")
self._normalization_period = self.Param("NormalizationPeriod", 16) \
.SetRange(5, 120) \
.SetDisplay("Normalization Period", "Lookback period used to normalize the reversal spread", "Indicators")
self._entry_threshold = self.Param("EntryThreshold", 1.1) \
.SetRange(0.2, 5.0) \
.SetDisplay("Entry Threshold", "Z-score threshold required to open a position", "Signals")
self._exit_threshold = self.Param("ExitThreshold", 0.25) \
.SetRange(0.0, 2.0) \
.SetDisplay("Exit Threshold", "Z-score threshold required to close a position", "Signals")
self._cooldown_bars = self.Param("CooldownBars", 6) \
.SetRange(0, 120) \
.SetDisplay("Cooldown Bars", "Closed candles to wait before another position change", "Risk")
self._stop_loss = self.Param("StopLoss", 3.0) \
.SetRange(0.5, 10.0) \
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromHours(4))) \
.SetDisplay("Candle Type", "Time frame for candles", "General")
self._benchmark = None
self._primary_return = None
self._benchmark_return = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_return = 0.0
self._latest_benchmark_return = 0.0
self._previous_z_score = None
self._primary_updated = False
self._benchmark_updated = False
self._cooldown_remaining = 0
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(short_term_reversal_stocks_strategy, self).OnReseted()
self._benchmark = None
self._primary_return = None
self._benchmark_return = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_return = 0.0
self._latest_benchmark_return = 0.0
self._previous_z_score = None
self._primary_updated = False
self._benchmark_updated = False
self._cooldown_remaining = 0
def OnStarted2(self, time):
super(short_term_reversal_stocks_strategy, self).OnStarted2(time)
sec2_id = str(self._security2_id.Value)
if not sec2_id:
raise Exception("Benchmark security identifier is not specified.")
s = Security()
s.Id = sec2_id
self._benchmark = s
lookback = int(self._lookback_period.Value)
norm_period = int(self._normalization_period.Value)
self._primary_return = RateOfChange()
self._primary_return.Length = lookback
self._benchmark_return = RateOfChange()
self._benchmark_return.Length = lookback
self._spread_average = SimpleMovingAverage()
self._spread_average.Length = norm_period
self._spread_deviation = StandardDeviation()
self._spread_deviation.Length = norm_period
primary_subscription = self.SubscribeCandles(self.candle_type, True, self.Security)
benchmark_subscription = self.SubscribeCandles(self.candle_type, True, self._benchmark)
primary_subscription.Bind(self._process_primary_candle).Start()
benchmark_subscription.Bind(self._process_benchmark_candle).Start()
self.StartProtection(
Unit(2, UnitTypes.Percent),
Unit(float(self._stop_loss.Value), UnitTypes.Percent)
)
def _process_primary_candle(self, candle):
if candle.State != CandleStates.Finished:
return
civ = CandleIndicatorValue(self._primary_return, candle)
civ.IsFinal = True
value = self._primary_return.Process(civ)
if value.IsEmpty or not self._primary_return.IsFormed:
return
self._latest_primary_return = float(value)
self._primary_updated = True
self._try_process_spread(candle.OpenTime)
def _process_benchmark_candle(self, candle):
if candle.State != CandleStates.Finished:
return
civ = CandleIndicatorValue(self._benchmark_return, candle)
civ.IsFinal = True
value = self._benchmark_return.Process(civ)
if value.IsEmpty or not self._benchmark_return.IsFormed:
return
self._latest_benchmark_return = float(value)
self._benchmark_updated = True
self._try_process_spread(candle.OpenTime)
def _try_process_spread(self, time):
if not self._primary_updated or not self._benchmark_updated:
return
self._primary_updated = False
self._benchmark_updated = False
spread = self._latest_primary_return - self._latest_benchmark_return
mean = float(process_float(self._spread_average, spread, time, True))
deviation = float(process_float(self._spread_deviation, spread, time, True))
if not self._spread_average.IsFormed or not self._spread_deviation.IsFormed or deviation <= 0:
return
if not self.IsFormedAndOnlineAndAllowTrading():
return
if self._cooldown_remaining > 0:
self._cooldown_remaining -= 1
z_score = (spread - mean) / deviation
entry_thresh = float(self._entry_threshold.Value)
exit_thresh = float(self._exit_threshold.Value)
cooldown = int(self._cooldown_bars.Value)
bullish_entry = self._previous_z_score is not None and self._previous_z_score > -entry_thresh and z_score <= -entry_thresh
bearish_entry = self._previous_z_score is not None and self._previous_z_score < entry_thresh and z_score >= entry_thresh
if self._cooldown_remaining == 0 and self.Position == 0:
if bullish_entry:
self.BuyMarket()
self._cooldown_remaining = cooldown
elif bearish_entry:
self.SellMarket()
self._cooldown_remaining = cooldown
elif self.Position > 0 and z_score >= -exit_thresh:
self.SellMarket(self.Position)
self._cooldown_remaining = cooldown
elif self.Position < 0 and z_score <= exit_thresh:
self.BuyMarket(Math.Abs(self.Position))
self._cooldown_remaining = cooldown
self._previous_z_score = z_score
def CreateClone(self):
return short_term_reversal_stocks_strategy()