The Exp AFIRMA Strategy reproduces the MetaTrader expert advisor Exp_AFIRMA.mq5 using the StockSharp high-level API. The
original system relies on the AFIRMA indicator (Adaptive Finite Impulse Response Moving Average) that blends a windowed FIR
smoother with a short ARMA forecast. The StockSharp version keeps the same market logic: it opens long positions when the ARMA
component turns upward and exits or reverses when the forecast rolls over to the downside.
Trading decisions are made on completed candles from a configurable timeframe (default: H4). The strategy evaluates the ARMA
values of several closed bars to confirm a slope change. Orders are placed at market with optional protective stops and targets
implemented through StockSharp's risk management.
Trading Logic
Indicator calculation
The built-in AfirmaIndicator recreates the two-stage AFIRMA filter. A windowed FIR smoother (length = Taps, bandwidth =
Periods) produces a base moving average.
The ARMA forecast is computed through the same least-squares coefficients as in the MQL source. The indicator exposes both
FIR and ARMA values; the strategy only consumes the ARMA component.
Signal evaluation
At every finished candle the most recent ARMA value is stored. The parameter SignalBar (default: 1) specifies how many
already closed bars should be skipped. For example, the default setting analyses bars [t-1, t-2, t-3] to trigger at the
open of bar t.
Bullish setup: previous ARMA value is lower than its predecessor (ARMA[t-2] < ARMA[t-3]) and the newest value is above
the previous (ARMA[t-1] > ARMA[t-2]). This closes short exposure and opens/extends a long position if allowed.
Bearish setup: previous ARMA value is higher than its predecessor while the newest value is below it. This closes long
exposure and opens/extends a short position if permitted.
Position management
Only one position is maintained. New entries bring the position toward ±TradeVolume. Existing exposure is flattened before
flipping.
Optional risk protection uses StartProtection with price-based stop-loss and take-profit distances.
Parameters
Parameter
Description
TradeVolume
Base position size used for both long and short entries.
CandleType
Timeframe/data type requested from the market data adapter (default: 4-hour candles).
Periods
Reciprocal bandwidth of the FIR stage (1 / (2 * Periods)), identical to the original EA input.
Taps
Number of FIR coefficients. Internally adjusted to the nearest odd value if needed.
Window
Window function applied to the FIR filter (Rectangular, Hanning1, Hanning2, Blackman, BlackmanHarris).
SignalBar
Number of already closed bars to look back for confirmation. 1 corresponds to the last fully closed bar.
EnableBuyEntries / EnableSellEntries
Allow opening of long/short positions.
EnableBuyExits / EnableSellExits
Allow closing of long/short positions on opposite signals.
StopLossPoints
Optional protective stop expressed in price units.
TakeProfitPoints
Optional protective target expressed in price units.
Notes on the Conversion
Money-management options (MM, MMMode, Deviation_) from the MetaTrader version are replaced with the simpler
TradeVolume parameter. Use StockSharp portfolio settings for advanced sizing or slippage control.
The original EA sends stop-loss and take-profit values in points. Here they are provided in absolute price units so that the
protection module can be reused across different instruments. Convert points to price by multiplying by the appropriate price
step.
When SignalBar = 1 the strategy reads the last three completed ARMA values and opens orders on the next bar, matching the
behaviour of the source code that relies on CopyBuffer with shift one. Setting SignalBar = 0 still works but uses the most
recently closed bar because StockSharp calculations are performed on finished candles.
The AFIRMA indicator implementation matches the original math, including the supported window types and coefficient formulas,
allowing you to display FIR and ARMA lines on a chart if desired.
Usage Tips
Attach the strategy to a security and portfolio, configure TradeVolume, and select the candle timeframe through
CandleType.
Enable or disable long/short directions according to your trading plan.
Set StopLossPoints and TakeProfitPoints if you want automated risk management; otherwise leave them at zero to trade
without fixed exits.
Monitor the generated chart to verify the AFIRMA lines and the executed trades when tuning Periods, Taps, and SignalBar.
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;
/// <summary>
/// Exp AFIRMA strategy using EMA crossover as adaptive filter approximation.
/// Buys when fast EMA crosses above slow EMA, sells on reverse.
/// </summary>
public class ExpAfirmaStrategy : 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;
/// <summary>
/// Fast EMA period.
/// </summary>
public int FastPeriod
{
get => _fastPeriod.Value;
set => _fastPeriod.Value = value;
}
/// <summary>
/// Slow EMA period.
/// </summary>
public int SlowPeriod
{
get => _slowPeriod.Value;
set => _slowPeriod.Value = value;
}
/// <summary>
/// Stop-loss distance in price steps.
/// </summary>
public int StopLossPoints
{
get => _stopLossPoints.Value;
set => _stopLossPoints.Value = value;
}
/// <summary>
/// Take-profit distance in price steps.
/// </summary>
public int TakeProfitPoints
{
get => _takeProfitPoints.Value;
set => _takeProfitPoints.Value = value;
}
/// <summary>
/// Initializes a new instance of the <see cref="ExpAfirmaStrategy"/> class.
/// </summary>
public ExpAfirmaStrategy()
{
_fastPeriod = Param(nameof(FastPeriod), 21)
.SetGreaterThanZero()
.SetDisplay("Fast Period", "Fast EMA period", "Indicator");
_slowPeriod = Param(nameof(SlowPeriod), 100)
.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");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
yield return (Security, TimeSpan.FromMinutes(5).TimeFrame());
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
_fast = null;
_slow = null;
_prevFast = 0;
_prevSlow = 0;
_entryPrice = 0;
_cooldown = 0;
}
/// <inheritdoc />
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;
// Check SL/TP
if (Position > 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close <= _entryPrice - StopLossPoints * step)
{
SellMarket();
_entryPrice = 0;
_cooldown = 80;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
if (TakeProfitPoints > 0 && close >= _entryPrice + TakeProfitPoints * step)
{
SellMarket();
_entryPrice = 0;
_cooldown = 80;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
}
else if (Position < 0 && _entryPrice > 0)
{
if (StopLossPoints > 0 && close >= _entryPrice + StopLossPoints * step)
{
BuyMarket();
_entryPrice = 0;
_cooldown = 80;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
if (TakeProfitPoints > 0 && close <= _entryPrice - TakeProfitPoints * step)
{
BuyMarket();
_entryPrice = 0;
_cooldown = 80;
_prevFast = fastValue;
_prevSlow = slowValue;
return;
}
}
// EMA crossover
if (_prevFast <= _prevSlow && fastValue > slowValue && Position <= 0)
{
if (Position < 0)
BuyMarket();
BuyMarket();
_entryPrice = close;
_cooldown = 80;
}
else if (_prevFast >= _prevSlow && fastValue < slowValue && Position >= 0)
{
if (Position > 0)
SellMarket();
SellMarket();
_entryPrice = close;
_cooldown = 80;
}
_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 exp_afirma_strategy(Strategy):
def __init__(self):
super(exp_afirma_strategy, self).__init__()
self._fast_period = self.Param("FastPeriod", 21) \
.SetDisplay("Fast Period", "Fast EMA period", "Indicator")
self._slow_period = self.Param("SlowPeriod", 100) \
.SetDisplay("Slow Period", "Slow EMA 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(exp_afirma_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(exp_afirma_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 = 80
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 = 80
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 = 80
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 = 80
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 = 80
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 = 80
self._prev_fast = fast_val
self._prev_slow = slow_val
def CreateClone(self):
return exp_afirma_strategy()