Earnings Quality Factor
The Earnings Quality Factor strategy rebalances annually on July 1, going long high quality and short low quality stocks based on earnings quality scores.
Details
- Entry Criteria: Annual July 1 rebalance using quality scores.
- Long/Short: Both.
- Exit Criteria: Next annual rebalance.
- Stops: No.
- Default Values:
MinTradeUsd = 100CandleType = TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Fundamental
- Direction: Both
- Indicators: Quality
- Stops: No
- Complexity: Intermediate
- Timeframe: Daily
- Seasonality: Yes
- Neural Networks: No
- Divergence: No
- Risk Level: Medium
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>
/// Earnings quality factor strategy that trades the primary instrument when its synthetic earnings quality diverges from a benchmark.
/// </summary>
public class EarningsQualityFactorStrategy : Strategy
{
private readonly StrategyParam<string> _security2Id;
private readonly StrategyParam<int> _qualityLength;
private readonly StrategyParam<int> _lookbackPeriod;
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 _primaryQuality = null!;
private ExponentialMovingAverage _benchmarkQuality = null!;
private SimpleMovingAverage _spreadAverage = null!;
private StandardDeviation _spreadDeviation = null!;
private decimal _latestPrimaryQuality;
private decimal _latestBenchmarkQuality;
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 earnings quality score.
/// </summary>
public int QualityLength
{
get => _qualityLength.Value;
set => _qualityLength.Value = value;
}
/// <summary>
/// Lookback period used to normalize the quality spread.
/// </summary>
public int LookbackPeriod
{
get => _lookbackPeriod.Value;
set => _lookbackPeriod.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>
/// The type of candles to use for calculations.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Initializes a new instance of the <see cref="EarningsQualityFactorStrategy"/> class.
/// </summary>
public EarningsQualityFactorStrategy()
{
_security2Id = Param(nameof(Security2Id), Paths.HistoryDefaultSecurity2)
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark security", "General");
_qualityLength = Param(nameof(QualityLength), 12)
.SetRange(2, 80)
.SetDisplay("Quality Length", "Smoothing length for the synthetic earnings quality score", "Indicators");
_lookbackPeriod = Param(nameof(LookbackPeriod), 24)
.SetRange(5, 120)
.SetDisplay("Lookback Period", "Lookback period used to normalize the quality spread", "Indicators");
_entryThreshold = Param(nameof(EntryThreshold), 1.2m)
.SetRange(0.2m, 5m)
.SetDisplay("Entry Threshold", "Z-score threshold required to open a position", "Signals");
_exitThreshold = Param(nameof(ExitThreshold), 0.3m)
.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), 2.5m)
.SetRange(0.5m, 10m)
.SetDisplay("Stop Loss %", "Stop loss percentage", "Risk");
_candleType = Param(nameof(CandleType), TimeSpan.FromHours(4).TimeFrame())
.SetDisplay("Candle Type", "Type of candles for calculation", "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!;
_primaryQuality = null!;
_benchmarkQuality = null!;
_spreadAverage = null!;
_spreadDeviation = null!;
_latestPrimaryQuality = 0m;
_latestBenchmarkQuality = 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 };
_primaryQuality = new ExponentialMovingAverage { Length = QualityLength };
_benchmarkQuality = new ExponentialMovingAverage { Length = QualityLength };
_spreadAverage = new SimpleMovingAverage { Length = LookbackPeriod };
_spreadDeviation = new StandardDeviation { Length = LookbackPeriod };
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;
_latestPrimaryQuality = UpdateQuality(_primaryQuality, candle);
_primaryUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private void ProcessBenchmarkCandle(ICandleMessage candle)
{
if (candle.State != CandleStates.Finished)
return;
_latestBenchmarkQuality = UpdateQuality(_benchmarkQuality, candle);
_benchmarkUpdated = true;
TryProcessSpread(candle.OpenTime);
}
private decimal UpdateQuality(ExponentialMovingAverage average, ICandleMessage candle)
{
var qualitySignal = CalculateQualitySignal(candle);
return average.Process(qualitySignal, candle.OpenTime, true).ToDecimal();
}
private decimal CalculateQualitySignal(ICandleMessage candle)
{
var priceBase = Math.Max(candle.OpenPrice, 1m);
var range = Math.Max(candle.HighPrice - candle.LowPrice, Security?.PriceStep ?? 1m);
var body = candle.ClosePrice - candle.OpenPrice;
var efficiency = body / range;
var stability = 1m - Math.Min(0.25m, range / priceBase);
return (efficiency * 2m) + stability;
}
private void TryProcessSpread(DateTime time)
{
if (!_primaryUpdated || !_benchmarkUpdated)
return;
_primaryUpdated = false;
_benchmarkUpdated = false;
var spread = _latestPrimaryQuality - _latestBenchmarkQuality;
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 earnings_quality_factor_strategy(Strategy):
"""Earnings quality factor strategy that trades the primary instrument when its synthetic earnings quality diverges from a benchmark."""
def __init__(self):
super(earnings_quality_factor_strategy, self).__init__()
self._security2_id = self.Param("Security2Id", "TONUSDT@BNBFT") \
.SetDisplay("Benchmark Security Id", "Identifier of the benchmark security", "General")
self._quality_length = self.Param("QualityLength", 12) \
.SetRange(2, 80) \
.SetDisplay("Quality Length", "Smoothing length for the synthetic earnings quality score", "Indicators")
self._lookback_period = self.Param("LookbackPeriod", 24) \
.SetRange(5, 120) \
.SetDisplay("Lookback Period", "Lookback period used to normalize the quality spread", "Indicators")
self._entry_threshold = self.Param("EntryThreshold", 1.2) \
.SetRange(0.2, 5.0) \
.SetDisplay("Entry Threshold", "Z-score threshold required to open a position", "Signals")
self._exit_threshold = self.Param("ExitThreshold", 0.3) \
.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", 2.5) \
.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", "Type of candles for calculation", "General")
self._benchmark = None
self._primary_quality = None
self._benchmark_quality = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_quality = 0.0
self._latest_benchmark_quality = 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(earnings_quality_factor_strategy, self).OnReseted()
self._benchmark = None
self._primary_quality = None
self._benchmark_quality = None
self._spread_average = None
self._spread_deviation = None
self._latest_primary_quality = 0.0
self._latest_benchmark_quality = 0.0
self._previous_z_score = None
self._primary_updated = False
self._benchmark_updated = False
self._cooldown_remaining = 0
def OnStarted2(self, time):
super(earnings_quality_factor_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
quality_len = int(self._quality_length.Value)
lookback = int(self._lookback_period.Value)
self._primary_quality = ExponentialMovingAverage()
self._primary_quality.Length = quality_len
self._benchmark_quality = ExponentialMovingAverage()
self._benchmark_quality.Length = quality_len
self._spread_average = SimpleMovingAverage()
self._spread_average.Length = lookback
self._spread_deviation = StandardDeviation()
self._spread_deviation.Length = lookback
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_quality = self.UpdateQuality(self._primary_quality, candle)
self._primary_updated = True
self.TryProcessSpread(candle.OpenTime)
def ProcessBenchmarkCandle(self, candle):
if candle.State != CandleStates.Finished:
return
self._latest_benchmark_quality = self.UpdateQuality(self._benchmark_quality, candle)
self._benchmark_updated = True
self.TryProcessSpread(candle.OpenTime)
def UpdateQuality(self, average, candle):
quality_signal = self.CalculateQualitySignal(candle)
result = process_float(average, quality_signal, candle.OpenTime, True)
return float(result)
def CalculateQualitySignal(self, candle):
price_base = max(float(candle.OpenPrice), 1.0)
price_step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
range_val = max(float(candle.HighPrice) - float(candle.LowPrice), price_step)
body = float(candle.ClosePrice) - float(candle.OpenPrice)
efficiency = body / range_val
stability = 1.0 - min(0.25, range_val / price_base)
return (efficiency * 2.0) + stability
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_quality - self._latest_benchmark_quality
mean_result = process_float(self._spread_average, spread, time, True)
mean = float(mean_result)
dev_result = process_float(self._spread_deviation, spread, time, True)
deviation = float(dev_result)
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 earnings_quality_factor_strategy()