The Trend Reversal strategy is a directional system that attempts to capture breakouts after a short-term pullback inside an existing trend. It was ported from the MetaTrader "Trend Reversal" expert advisor and rewritten to use the high-level StockSharp API. The conversion keeps the core confirmation stack (moving averages, momentum, and MACD) while replacing the original graphical line filters with price overlap checks that are easier to reproduce programmatically.
Indicator Stack
Linear Weighted Moving Averages (LWMA) on typical price with customizable fast and slow lengths. The fast line tracks the latest swing, while the slow line identifies the dominant trend.
Momentum oscillator calculated on the same timeframe. The strategy records the absolute distance from the neutral 100 level for the latest three closed candles to emulate the MetaTrader logic.
MACD signal line pair configured with independent fast, slow, and signal lengths. The histogram direction is used as a higher-timeframe confirmation for both long and short trades.
Trade Logic
Wait for a finished candle on the configured timeframe. The strategy ignores partially formed bars.
Ensure that both LWMAs and the momentum indicator are fully formed. Without enough history the system remains flat.
Keep a rolling queue of the three most recent momentum deviations from 100. A setup is valid only if at least one of these values exceeds the respective buy or sell threshold.
Require that the candle from two bars ago has a lower low than the high of the previous candle. This recreates the "overlapping" structure used in the original EA to detect a tight consolidation before the breakout.
Evaluate directional filters:
Long: fast LWMA above slow LWMA and MACD main value above the signal line.
Short: fast LWMA below slow LWMA and MACD main value below the signal line.
Respect the net position limit. The strategy enters or adds to a position only when the absolute exposure (current position divided by trade volume) is below the configured MaxPositions value.
Orders are sent with BuyMarket() or SellMarket() which allows partial or full reversals depending on the current exposure.
Risk Management
Optional take profit and stop loss distances (expressed in price units) can be attached through StockSharp's built-in protective block. Both levels are disabled when a parameter is set to zero.
No automatic trailing stop or break-even adjustment is included in this port. These features can be implemented with additional event handlers if needed.
Parameters
Name
Description
Default
CandleType
Primary timeframe used to build candles.
15-minute time frame
FastLength
Period for the fast LWMA.
6
SlowLength
Period for the slow LWMA.
85
MomentumLength
Period of the momentum oscillator.
14
MomentumBuyThreshold
Minimum absolute momentum deviation (from 100) that validates a long setup.
0.3
MomentumSellThreshold
Minimum absolute momentum deviation (from 100) that validates a short setup.
0.3
MacdFastLength
Fast EMA period used inside the MACD filter.
12
MacdSlowLength
Slow EMA period used inside the MACD filter.
26
MacdSignalLength
Signal EMA period used inside the MACD filter.
9
TakeProfit
Take profit distance in price units. Set to 0 to disable.
50
StopLoss
Stop loss distance in price units. Set to 0 to disable.
20
TradeVolume
Order volume expressed in lots.
1
MaxPositions
Maximum number of trade-volume units allowed in the net position.
1
Usage Notes
Attach the strategy to a security with valid step and price information so that protective orders work correctly.
For multi-directional trading (pyramiding or scaling in), increase MaxPositions. The strategy will keep adding positions as long as the filters remain valid and the exposure stays within this limit.
Backtesting should be performed with the same candle timeframe that the CandleType parameter specifies. StockSharp will automatically request the proper data when the strategy starts.
Because the MetaTrader version depended on hand-drawn trend lines, this rewrite substitutes those checks with a deterministic candle overlap condition. This keeps the behaviour consistent between backtests and live execution.
Differences Compared to the Original EA
Trailing stop, break-even moves, and equity-based emergency exits are not implemented to keep the sample focused on core signal generation.
Money management features such as lot multiplication and Magic Number filtering are not needed in StockSharp and were therefore removed.
The MACD confirmation uses the same timeframe as the trading candles instead of the original monthly aggregation. You can emulate the multi-timeframe setup by subscribing to a slower candle type and binding the MACD filter to that subscription if desired.
Optimization Tips
Optimize the moving average lengths first to match the market's dominant cycle, then fine-tune the momentum thresholds.
Experiment with wider stop-loss and take-profit distances when trading volatile instruments. Since the logic is trend-following, larger exit buffers often improve profitability.
Monitor drawdown statistics during optimization runs. Increasing MaxPositions can improve responsiveness but also magnifies risk.
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
public class TrendReversalStrategy : Strategy
{
private readonly StrategyParam<int> _fastPeriod;
private readonly StrategyParam<int> _slowPeriod;
private readonly StrategyParam<int> _stopLossPoints;
private readonly StrategyParam<int> _takeProfitPoints;
private ExponentialMovingAverage _fast;
private ExponentialMovingAverage _slow;
private decimal _prevFast;
private decimal _prevSlow;
private decimal _entryPrice;
private int _cooldown;
public int FastPeriod { get => _fastPeriod.Value; set => _fastPeriod.Value = value; }
public int SlowPeriod { get => _slowPeriod.Value; set => _slowPeriod.Value = value; }
public int StopLossPoints { get => _stopLossPoints.Value; set => _stopLossPoints.Value = value; }
public int TakeProfitPoints { get => _takeProfitPoints.Value; set => _takeProfitPoints.Value = value; }
public TrendReversalStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 14).SetGreaterThanZero().SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 50).SetGreaterThanZero().SetDisplay("Slow Period", "Slow EMA period", "Indicator");
_stopLossPoints = Param(nameof(StopLossPoints), 200).SetNotNegative().SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk");
_takeProfitPoints = Param(nameof(TakeProfitPoints), 400).SetNotNegative().SetDisplay("Take Profit", "Take-profit in price steps", "Risk");
}
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
protected override void OnReseted()
{
base.OnReseted();
_fast = null; _slow = null;
_prevFast = 0; _prevSlow = 0; _entryPrice = 0; _cooldown = 0;
}
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
_fast = new ExponentialMovingAverage { Length = FastPeriod };
_slow = new ExponentialMovingAverage { Length = SlowPeriod };
var subscription = SubscribeCandles(TimeSpan.FromMinutes(5).TimeFrame());
subscription.Bind(_fast, _slow, ProcessCandle);
subscription.Start();
}
private void ProcessCandle(ICandleMessage candle, decimal fastValue, decimal slowValue)
{
if (candle.State != CandleStates.Finished) return;
if (!_fast.IsFormed || !_slow.IsFormed) { _prevFast = fastValue; _prevSlow = slowValue; return; }
if (_cooldown > 0) { _cooldown--; _prevFast = fastValue; _prevSlow = slowValue; return; }
var close = candle.ClosePrice;
var step = Security?.PriceStep ?? 1m;
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step) { SellMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step) { BuyMarket(); _entryPrice = 0; _cooldown = 100; _prevFast = fastValue; _prevSlow = slowValue; return; }
}
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{ if (Position < 0) BuyMarket(); BuyMarket(); _entryPrice = close; _cooldown = 100; }
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{ if (Position > 0) SellMarket(); SellMarket(); _entryPrice = close; _cooldown = 100; }
_prevFast = fastValue; _prevSlow = slowValue;
}
}
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 trend_reversal_strategy(Strategy):
def __init__(self):
super(trend_reversal_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 14) \
.SetDisplay("Fast Period", "Fast MA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 50) \
.SetDisplay("Slow Period", "Slow MA period", "Indicator")
self._stop_loss_points = self.Param("StopLossPoints", 200) \
.SetDisplay("Stop Loss", "Stop-loss in price steps", "Risk")
self._take_profit_points = self.Param("TakeProfitPoints", 400) \
.SetDisplay("Take Profit", "Take-profit in price steps", "Risk")
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
@property
def fast_period(self):
return self._fast_period.Value
@property
def slow_period(self):
return self._slow_period.Value
@property
def stop_loss_points(self):
return self._stop_loss_points.Value
@property
def take_profit_points(self):
return self._take_profit_points.Value
def OnReseted(self):
super(trend_reversal_strategy, self).OnReseted()
self._fast = None
self._slow = None
self._prev_fast = 0.0
self._prev_slow = 0.0
self._entry_price = 0.0
self._cooldown = 0
def OnStarted2(self, time):
super(trend_reversal_strategy, self).OnStarted2(time)
self._fast = ExponentialMovingAverage()
self._fast.Length = self.fast_period
self._slow = ExponentialMovingAverage()
self._slow.Length = self.slow_period
subscription = self.SubscribeCandles(DataType.TimeFrame(TimeSpan.FromMinutes(5)))
subscription.Bind(self._fast, self._slow, self._process_candle)
subscription.Start()
def _process_candle(self, candle, fast_value, slow_value):
if candle.State != CandleStates.Finished:
return
fast_val = float(fast_value)
slow_val = float(slow_value)
if not self._fast.IsFormed or not self._slow.IsFormed:
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._cooldown > 0:
self._cooldown -= 1
self._prev_fast = fast_val
self._prev_slow = slow_val
return
close = float(candle.ClosePrice)
step = float(self.Security.PriceStep) if self.Security is not None and self.Security.PriceStep is not None else 1.0
if self.Position > 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close <= self._entry_price - self.stop_loss_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close >= self._entry_price + self.take_profit_points * step:
self.SellMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
elif self.Position < 0 and self._entry_price > 0:
if self.stop_loss_points > 0 and close >= self._entry_price + self.stop_loss_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self.take_profit_points > 0 and close <= self._entry_price - self.take_profit_points * step:
self.BuyMarket()
self._entry_price = 0.0
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
return
if self._prev_fast <= self._prev_slow and fast_val > slow_val and self.Position <= 0:
if self.Position < 0:
self.BuyMarket()
self.BuyMarket()
self._entry_price = close
self._cooldown = 100
elif self._prev_fast >= self._prev_slow and fast_val < slow_val and self.Position >= 0:
if self.Position > 0:
self.SellMarket()
self.SellMarket()
self._entry_price = close
self._cooldown = 100
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return trend_reversal_strategy()