空头兴趣效应
空头兴趣效应 策略利用做空兴趣水平预测股票表现。做空比例低或回补天数少的证券通常优于被大量做空的证券。每月按照空头兴趣排序,组合买入最低组并做空最高组。
细节
- 入场条件:按空头比例或回补天数每月排序。
- 多空方向:双向。
- 出场条件:每月再平衡。
- 止损:无显式止损。
- 默认值:
CandleType = TimeSpan.FromMinutes(5).TimeFrame()
- 筛选:
- 分类:基本面
- 方向:双向
- 指标:基本面
- 止损:无
- 复杂度:基础
- 时间框架:中期
- 季节性:是
- 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-interest effect strategy that trades the primary stock when its synthetic short-pressure proxy diverges from a benchmark stock.
/// </summary>
public class ShortInterestEffectStrategy : Strategy
{
private readonly StrategyParam<string> _security2Id;
private readonly StrategyParam<int> _pressureLength;
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 ExponentialMovingAverage _primaryPressure = null!;
private ExponentialMovingAverage _benchmarkPressure = null!;
private SimpleMovingAverage _spreadAverage = null!;
private StandardDeviation _spreadDeviation = null!;
private decimal _latestPrimaryScore;
private decimal _latestBenchmarkScore;
private decimal? _previousZScore;
private bool _primaryUpdated;
private bool _benchmarkUpdated;
private int _cooldownRemaining;
/// <summary>
/// Benchmark security identifier.
/// </summary>
public string Security2Id
{
get => _security2Id.Value;
set => _security2Id.Value = value;
}
/// <summary>
/// Smoothing length for the synthetic short-pressure proxy.
/// </summary>
public int PressureLength
{
get => _pressureLength.Value;
set => _pressureLength.Value = value;
}
/// <summary>
/// Lookback period used to normalize the short-pressure spread.
/// </summary>
public int NormalizationPeriod
{
get => _normalizationPeriod.Value;
set => _normalizationPeriod.Value = value;
}
/// <summary>
/// Z-score threshold required to open a position.
/// </summary>
public decimal EntryThreshold
{
get => _entryThreshold.Value;
set => _entryThreshold.Value = value;
}
/// <summary>
/// Z-score threshold required to close a position.
/// </summary>
public decimal ExitThreshold
{
get => _exitThreshold.Value;
set => _exitThreshold.Value = value;
}
/// <summary>
/// Closed candles to wait before another position change.
/// </summary>
public int CooldownBars
{
get => _cooldownBars.Value;
set => _cooldownBars.Value = value;
}
/// <summary>
/// Stop loss percentage.
/// </summary>
public decimal StopLoss
{
get => _stopLoss.Value;
set => _stopLoss.Value = value;
}
/// <summary>
/// Candle type used for calculations.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
public ShortInterestEffectStrategy()
{
_security2Id = Param(nameof(Security2Id), Paths.HistoryDefaultSecurity2)
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General");
_pressureLength = Param(nameof(PressureLength), 10)
.SetRange(2, 80)
.SetDisplay("Pressure Length", "Smoothing length for the synthetic short-pressure proxy", "Indicators");
_normalizationPeriod = Param(nameof(NormalizationPeriod), 24)
.SetRange(5, 120)
.SetDisplay("Normalization Period", "Lookback period used to normalize the short-pressure 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), 8)
.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!;
_primaryPressure = null!;
_benchmarkPressure = null!;
_spreadAverage = null!;
_spreadDeviation = null!;
_latestPrimaryScore = 0m;
_latestBenchmarkScore = 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 };
_primaryPressure = new ExponentialMovingAverage { Length = PressureLength };
_benchmarkPressure = new ExponentialMovingAverage { Length = PressureLength };
_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();
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, primarySubscription);
DrawCandles(area, benchmarkSubscription);
DrawOwnTrades(area);
}
StartProtection(
new Unit(2, UnitTypes.Percent),
new Unit(StopLoss, UnitTypes.Percent));
}
private void ProcessPrimaryCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
_latestPrimaryScore = UpdatePressure(_primaryPressure, candle);
_primaryUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private void ProcessBenchmarkCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
_latestBenchmarkScore = UpdatePressure(_benchmarkPressure, candle);
_benchmarkUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private static decimal UpdatePressure(ExponentialMovingAverage average, ICandleMessage candle)
{
var priceBase = Math.Max(candle.OpenPrice, 1m);
var downside = Math.Max(0m, candle.OpenPrice - candle.ClosePrice) / priceBase;
var squeeze = Math.Max(0m, candle.HighPrice - candle.ClosePrice) / priceBase;
var pressureProxy = 1m + (downside * 6m) + (squeeze * 3m);
return average.Process(pressureProxy, candle.OpenTime, true).ToDecimal();
}
private void TryProcessSpread(DateTime time)
{
if (!_primaryUpdated || !_benchmarkUpdated)
return;
_primaryUpdated = false;
_benchmarkUpdated = false;
var spread = _latestBenchmarkScore - _latestPrimaryScore;
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 ExponentialMovingAverage, SimpleMovingAverage, StandardDeviation
from StockSharp.Algo.Strategies import Strategy
from StockSharp.BusinessEntities import Security
from indicator_extensions import *
class short_interest_effect_strategy(Strategy):
"""Short-interest effect strategy that trades the primary stock when its synthetic short-pressure proxy diverges from a benchmark stock."""
def __init__(self):
super(short_interest_effect_strategy, self).__init__()
self._security2_id = self.Param("Security2Id", "TONUSDT@BNBFT") \
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General")
self._pressure_length = self.Param("PressureLength", 10) \
.SetRange(2, 80) \
.SetDisplay("Pressure Length", "Smoothing length for the synthetic short-pressure proxy", "Indicators")
self._normalization_period = self.Param("NormalizationPeriod", 24) \
.SetRange(5, 120) \
.SetDisplay("Normalization Period", "Lookback period used to normalize the short-pressure 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", 8) \
.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_pressure = None
self._benchmark_pressure = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_score = 0.0
self._latest_benchmark_score = 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_interest_effect_strategy, self).OnReseted()
self._benchmark = None
self._primary_pressure = None
self._benchmark_pressure = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_score = 0.0
self._latest_benchmark_score = 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_interest_effect_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
pressure_len = int(self._pressure_length.Value)
norm_period = int(self._normalization_period.Value)
self._primary_pressure = ExponentialMovingAverage()
self._primary_pressure.Length = pressure_len
self._benchmark_pressure = ExponentialMovingAverage()
self._benchmark_pressure.Length = pressure_len
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()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, primary_subscription)
self.DrawCandles(area, benchmark_subscription)
self.DrawOwnTrades(area)
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
self._latest_primary_score = self._update_pressure(self._primary_pressure, candle)
self._primary_updated = True
self._try_process_spread(candle.OpenTime)
def _process_benchmark_candle(self, candle):
if candle.State != CandleStates.Finished:
return
self._latest_benchmark_score = self._update_pressure(self._benchmark_pressure, candle)
self._benchmark_updated = True
self._try_process_spread(candle.OpenTime)
def _update_pressure(self, average, candle):
price_base = max(float(candle.OpenPrice), 1.0)
downside = max(0.0, float(candle.OpenPrice) - float(candle.ClosePrice)) / price_base
squeeze = max(0.0, float(candle.HighPrice) - float(candle.ClosePrice)) / price_base
pressure_proxy = 1.0 + (downside * 6.0) + (squeeze * 3.0)
return float(process_float(average, pressure_proxy, candle.OpenTime, True))
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_benchmark_score - self._latest_primary_score
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_interest_effect_strategy()