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HMA Seasonal Divergence Strategy
This strategy combines the Hull Moving Average (HMA) with seasonal open interest clustering to find divergences between price and market positioning. It assumes that when price temporarily moves against the direction of rising open interest, a trend continuation is likely. The system is designed to trade both long and short, using the HMA slope to gauge momentum and the seasonal open interest data to measure participation levels.
Testing indicates an average annual return of about 40%. It performs best in the crypto market.
A trade setup occurs when the HMA changes relative to the previous bar while seasonal open interest confirms the move, but price prints in the opposite direction. This bullish or bearish divergence between price and positioning often signals the end of a short-term pullback within a larger trend. The strategy waits for these conditions before entering and places a volatility-based stop to manage risk.
Positions are closed when the HMA slope reverses, signifying that momentum has shifted. Because the stop level uses a multiple of the Average True Range (ATR), the risk adapts to market volatility. This helps prevent premature exits during periods of expansion and keeps losses contained when volatility contracts.
Details
Entry Criteria :
Long : HMA(t) > HMA(t-1) && OI_Cluster_Seasonal(t) > OI_Cluster_Seasonal(t-1) && Price(t) < Price(t-1) (bullish divergence).
Short : HMA(t) < HMA(t-1) && OI_Cluster_Seasonal(t) < OI_Cluster_Seasonal(t-1) && Price(t) > Price(t-1) (bearish divergence).
Long/Short : Both sides.
Exit Criteria :
Long : HMA(t) < HMA(t-1) (HMA begins falling).
Short : HMA(t) > HMA(t-1) (HMA begins rising).
Stops : Yes, stop-loss placed at N * ATR from entry.
Default Values :
HMA period = 9.
OI_Cluster_Seasonal = seasonal OI at cluster levels over five years.
N = 2 (stop-loss = 2 * ATR).
Filters :
Category: Trend following
Direction: Both
Indicators: Multiple
Stops: Yes
Complexity: Complex
Timeframe: Medium-term
Seasonality: Yes
Neural networks: Yes
Divergence: Yes
Risk level: High
namespace StockSharp.Samples.Strategies;
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;
/// <summary>
/// Moving average crossover strategy.
/// Enters long when fast MA crosses above slow MA.
/// Enters short when fast MA crosses below slow MA.
/// Implements stop-loss as a percentage of entry price.
/// </summary>
public class MaCrossoverStrategy : Strategy
{
private readonly StrategyParam<int> _fastLength;
private readonly StrategyParam<int> _slowLength;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
private decimal _entryPrice;
private bool _isLongPosition;
/// <summary>
/// Fast MA period length.
/// </summary>
public int FastLength
{
get => _fastLength.Value;
set => _fastLength.Value = value;
}
/// <summary>
/// Slow MA period length.
/// </summary>
public int SlowLength
{
get => _slowLength.Value;
set => _slowLength.Value = value;
}
/// <summary>
/// Stop-loss percentage.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// The type of candles to use for strategy calculation.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Constructor.
/// </summary>
public MaCrossoverStrategy()
{
_fastLength = Param(nameof(FastLength), 100)
.SetGreaterThanZero()
.SetDisplay("Fast MA Length", "Period of the fast moving average", "MA Settings")
.SetOptimize(5, 20, 5);
_slowLength = Param(nameof(SlowLength), 400)
.SetGreaterThanZero()
.SetDisplay("Slow MA Length", "Period of the slow moving average", "MA Settings")
.SetOptimize(20, 100, 10);
_stopLossPercent = Param(nameof(StopLossPercent), 2.0m)
.SetGreaterThanZero()
.SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk Management")
.SetOptimize(1.0m, 5.0m, 1.0m);
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(1).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
// Initialize variables
_entryPrice = 0;
_isLongPosition = false;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
// Create indicators
var fastMa = new ExponentialMovingAverage { Length = FastLength };
var slowMa = new ExponentialMovingAverage { Length = SlowLength };
// Create and setup subscription for candles
var subscription = SubscribeCandles(CandleType);
// Previous values for crossover detection
var previousFastValue = 0m;
var previousSlowValue = 0m;
var wasFastLessThanSlow = false;
var isInitialized = false;
subscription
.Bind(fastMa, slowMa, (candle, fastValue, slowValue) =>
{
// Skip unfinished candles
if (candle.State != CandleStates.Finished)
return;
// Check if strategy is ready to trade
if (!IsFormedAndOnlineAndAllowTrading())
return;
// Initialize on first complete values
if (!isInitialized && fastMa.IsFormed && slowMa.IsFormed)
{
previousFastValue = fastValue;
previousSlowValue = slowValue;
wasFastLessThanSlow = fastValue < slowValue;
isInitialized = true;
LogInfo($"Strategy initialized. Fast MA: {fastValue}, Slow MA: {slowValue}");
return;
}
if (!isInitialized)
return;
// Current crossover state
var isFastLessThanSlow = fastValue < slowValue;
LogInfo($"Candle: {candle.OpenTime}, Close: {candle.ClosePrice}, Fast MA: {fastValue}, Slow MA: {slowValue}");
// Check for crossovers
if (wasFastLessThanSlow != isFastLessThanSlow)
{
// Crossover happened
if (!isFastLessThanSlow) // Fast MA crossed above Slow MA
{
// Buy signal
if (Position <= 0)
{
_entryPrice = candle.ClosePrice;
_isLongPosition = true;
BuyMarket(Volume + Math.Abs(Position));
}
}
else // Fast MA crossed below Slow MA
{
// Sell signal
if (Position >= 0)
{
_entryPrice = candle.ClosePrice;
_isLongPosition = false;
SellMarket(Volume + Math.Abs(Position));
}
}
// Update the crossover state
wasFastLessThanSlow = isFastLessThanSlow;
}
// Update previous values
previousFastValue = fastValue;
previousSlowValue = slowValue;
})
.Start();
// Setup chart if available
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, fastMa);
DrawIndicator(area, slowMa);
DrawOwnTrades(area);
}
}
private void CheckStopLoss(decimal currentPrice)
{
if (_entryPrice == 0)
return;
var stopLossThreshold = _stopLossPercent.Value / 100.0m;
if (_isLongPosition && Position > 0)
{
// For long positions, exit if price falls below entry price - stop percentage
var stopPrice = _entryPrice * (1.0m - stopLossThreshold);
if (currentPrice <= stopPrice)
{
SellMarket(Math.Abs(Position));
LogInfo($"Long stop-loss triggered at {currentPrice}. Entry was {_entryPrice}, Stop level: {stopPrice}");
}
}
else if (!_isLongPosition && Position < 0)
{
// For short positions, exit if price rises above entry price + stop percentage
var stopPrice = _entryPrice * (1.0m + stopLossThreshold);
if (currentPrice >= stopPrice)
{
BuyMarket(Math.Abs(Position));
LogInfo($"Short stop-loss triggered at {currentPrice}. Entry was {_entryPrice}, Stop level: {stopPrice}");
}
}
}
}
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.Indicators import ExponentialMovingAverage
from StockSharp.Algo.Strategies import Strategy
class ma_crossover_strategy(Strategy):
"""
Moving average crossover strategy.
Enters long when fast MA crosses above slow MA.
Enters short when fast MA crosses below slow MA.
"""
def __init__(self):
super(ma_crossover_strategy, self).__init__()
self._fast_length = self.Param("FastLength", 100).SetDisplay("Fast MA Length", "Period of the fast moving average", "MA Settings")
self._slow_length = self.Param("SlowLength", 400).SetDisplay("Slow MA Length", "Period of the slow moving average", "MA Settings")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0).SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk Management")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(1))).SetDisplay("Candle Type", "Type of candles to use", "General")
self._entry_price = 0.0
self._is_long_position = False
@property
def candle_type(self):
return self._candle_type.Value
def OnReseted(self):
super(ma_crossover_strategy, self).OnReseted()
self._entry_price = 0.0
self._is_long_position = False
def OnStarted2(self, time):
super(ma_crossover_strategy, self).OnStarted2(time)
fast_ma = ExponentialMovingAverage()
fast_ma.Length = self._fast_length.Value
slow_ma = ExponentialMovingAverage()
slow_ma.Length = self._slow_length.Value
self._was_fast_less = False
self._is_initialized = False
subscription = self.SubscribeCandles(self.candle_type)
subscription.Bind(fast_ma, slow_ma, self._process_candle).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, fast_ma)
self.DrawIndicator(area, slow_ma)
self.DrawOwnTrades(area)
def _process_candle(self, candle, fast_val, slow_val):
if candle.State != CandleStates.Finished:
return
fv = float(fast_val)
sv = float(slow_val)
if not self._is_initialized:
self._was_fast_less = fv < sv
self._is_initialized = True
return
is_fast_less = fv < sv
if self._was_fast_less != is_fast_less:
if not is_fast_less:
if self.Position <= 0:
self._entry_price = float(candle.ClosePrice)
self._is_long_position = True
self.BuyMarket()
else:
if self.Position >= 0:
self._entry_price = float(candle.ClosePrice)
self._is_long_position = False
self.SellMarket()
self._was_fast_less = is_fast_less
def CreateClone(self):
return ma_crossover_strategy()