Эффект ROA для акций
Стратегия Эффект ROA для акций нацелена на компании с высокой доходностью на активы. Внешний фундаментальный источник предоставляет значения ROA для торговой вселенной. В начале каждого месяца акции ранжируются по ROA, и портфель покупает верхний дециль и продаёт нижний.
Позиции имеют равный вес и ребалансируются ежемесячно, что позволяет использовать тенденцию прибыльных фирм опережать рынок.
Детали
- Вход: ежемесячное ранжирование по внешним данным ROA.
- Длинные/короткие позиции: обе стороны.
- Выход: ежемесячная ребалансировка.
- Стопы: отсутствуют.
- Значения по умолчанию:
Decile = 10MinTradeUsd = 200CandleType = TimeSpan.FromMinutes(5).TimeFrame()
- Фильтры:
- Категория: Фундаментальная
- Направление: Обе
- Индикаторы: Фундаментальные
- Стопы: Нет
- Сложность: Средняя
- Таймфрейм: Дневной
- Сезонность: Да
- Нейросети: Нет
- Дивергенции: Нет
- Уровень риска: Средний
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>
/// ROA effect strategy that trades the primary stock when its synthetic profitability proxy outperforms a benchmark stock.
/// </summary>
public class ROAEffectStocksStrategy : Strategy
{
private readonly StrategyParam<string> _security2Id;
private readonly StrategyParam<int> _profitabilityLength;
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 _primaryProfitability = null!;
private ExponentialMovingAverage _benchmarkProfitability = 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 profitability proxy.
/// </summary>
public int ProfitabilityLength
{
get => _profitabilityLength.Value;
set => _profitabilityLength.Value = value;
}
/// <summary>
/// Lookback period used to normalize the profitability 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 ROAEffectStocksStrategy()
{
_security2Id = Param(nameof(Security2Id), Paths.HistoryDefaultSecurity2)
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General");
_profitabilityLength = Param(nameof(ProfitabilityLength), 10)
.SetRange(2, 80)
.SetDisplay("Profitability Length", "Smoothing length for the synthetic profitability proxy", "Indicators");
_normalizationPeriod = Param(nameof(NormalizationPeriod), 24)
.SetRange(5, 120)
.SetDisplay("Normalization Period", "Lookback period used to normalize the profitability 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!;
_primaryProfitability = null!;
_benchmarkProfitability = 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 };
_primaryProfitability = new ExponentialMovingAverage { Length = ProfitabilityLength };
_benchmarkProfitability = new ExponentialMovingAverage { Length = ProfitabilityLength };
_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 = UpdateProfitability(_primaryProfitability, candle);
_primaryUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private void ProcessBenchmarkCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
_latestBenchmarkScore = UpdateProfitability(_benchmarkProfitability, candle);
_benchmarkUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private static decimal UpdateProfitability(ExponentialMovingAverage average, ICandleMessage candle)
{
var priceBase = Math.Max(candle.OpenPrice, 1m);
var bodyRatio = (candle.ClosePrice - candle.OpenPrice) / priceBase;
var stability = 1m - Math.Min(0.2m, (candle.HighPrice - candle.LowPrice) / priceBase);
var profitabilityProxy = bodyRatio + stability;
return average.Process(profitabilityProxy, candle.OpenTime, true).ToDecimal();
}
private void TryProcessSpread(DateTime time)
{
if (!_primaryUpdated || !_benchmarkUpdated)
return;
_primaryUpdated = false;
_benchmarkUpdated = false;
var spread = _latestPrimaryScore - _latestBenchmarkScore;
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 roa_effect_stocks_strategy(Strategy):
"""ROA effect strategy that trades the primary stock when its synthetic profitability proxy outperforms a benchmark stock."""
def __init__(self):
super(roa_effect_stocks_strategy, self).__init__()
self._security2_id = self.Param("Security2Id", "TONUSDT@BNBFT") \
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark stock", "General")
self._profitability_length = self.Param("ProfitabilityLength", 10) \
.SetRange(2, 80) \
.SetDisplay("Profitability Length", "Smoothing length for the synthetic profitability proxy", "Indicators")
self._normalization_period = self.Param("NormalizationPeriod", 24) \
.SetRange(5, 120) \
.SetDisplay("Normalization Period", "Lookback period used to normalize the profitability 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_profitability = None
self._benchmark_profitability = 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 GetWorkingSecurities(self):
result = []
if self.Security is not None:
result.append((self.Security, self.candle_type))
sec2_id = str(self._security2_id.Value)
if sec2_id:
s = Security()
s.Id = sec2_id
result.append((s, self.candle_type))
return result
def OnReseted(self):
super(roa_effect_stocks_strategy, self).OnReseted()
self._benchmark = None
self._primary_profitability = None
self._benchmark_profitability = 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(roa_effect_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
prof_len = int(self._profitability_length.Value)
norm_period = int(self._normalization_period.Value)
self._primary_profitability = ExponentialMovingAverage()
self._primary_profitability.Length = prof_len
self._benchmark_profitability = ExponentialMovingAverage()
self._benchmark_profitability.Length = prof_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.ProcessPrimaryCandle).Start()
benchmark_subscription.Bind(self.ProcessBenchmarkCandle).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 ProcessPrimaryCandle(self, candle):
if candle.State != CandleStates.Finished:
return
self._latest_primary_score = self._update_profitability(self._primary_profitability, candle)
self._primary_updated = True
self.TryProcessSpread(candle.OpenTime)
def ProcessBenchmarkCandle(self, candle):
if candle.State != CandleStates.Finished:
return
self._latest_benchmark_score = self._update_profitability(self._benchmark_profitability, candle)
self._benchmark_updated = True
self.TryProcessSpread(candle.OpenTime)
def _update_profitability(self, average, candle):
price_base = max(float(candle.OpenPrice), 1.0)
body_ratio = (float(candle.ClosePrice) - float(candle.OpenPrice)) / price_base
stability = 1.0 - min(0.2, (float(candle.HighPrice) - float(candle.LowPrice)) / price_base)
profitability_proxy = body_ratio + stability
return float(process_float(average, profitability_proxy, candle.OpenTime, True))
def TryProcessSpread(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_score - self._latest_benchmark_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 roa_effect_stocks_strategy()