The Risk Reward Ratio Strategy is a high-level StockSharp port of the MetaTrader expert "Risk Reward Ratio". The strategy combines several momentum and trend confirmation filters with a disciplined risk-management module. Entries are generated from a confluence of stochastic oscillators, a linear weighted moving average (LWMA) crossover, a 14-period RSI filter, and a MACD trend check. Risk control is achieved through a pip-based stop-loss, an automatic reward-ratio take-profit, optional trailing stops and break-even logic, and an emergency flat switch that immediately liquidates the position.
The conversion keeps the original spirit of the MetaTrader expert while using StockSharp's candle subscriptions and indicator binding APIs. All indicator processing happens on finished candles and avoids direct access to indicator buffers, preserving the engine's streaming paradigm.
Trading Logic
Stochastic confluence
A fast stochastic (5, 2, 2) delivers the primary momentum signal using the %K line.
A slow stochastic (21, 10, 4) supplies the directional bias through its smoothed %D line.
Long setups require the fast %K to sit above the slow %D, while short setups require the opposite.
RSI confirmation
A 14-period RSI must be above 50 for long trades and below 50 for short trades, ensuring the market is aligned with the proposed direction.
Trend filter via LWMAs
Two linear weighted moving averages (lengths 6 and 85) must confirm the direction: the fast LWMA above the slow LWMA for longs, and below it for shorts.
MACD trend qualifier
The MACD histogram (12, 26, 9) needs to be in agreement with the signal direction. The main line must lead the signal line while staying on the appropriate side of zero.
Momentum deviation filter
A 14-period momentum indicator measures the distance from 100. At least one of the last three momentum readings must exceed the configurable threshold to prove that price is accelerating enough to justify a trade.
Position limits
Net exposure is capped by MaxPositions * TradeVolume so the strategy cannot pyramid beyond the original EA's constraint.
Orders are sent as market executions using BuyMarket and SellMarket. The strategy ignores unfinished candles and keeps all state inside class fields to respect the StockSharp event-driven architecture.
Risk Management
Stop-loss in pips – Every entry installs a protective stop at StopLossPips * PriceStep away from the fill price.
Reward ratio take-profit – The take-profit distance equals the stop distance multiplied by RewardRatio to maintain a fixed reward-to-risk relationship.
Trailing stop – When enabled, the stop moves behind price by TrailingStopPips once the market advances at least that distance from the entry.
Break-even shift – After BreakEvenTriggerPips of favorable travel, the stop is pushed to the entry plus an additional BreakEvenOffsetPips cushion (or minus for shorts), locking in gains.
Exit switch – Setting ExitSwitch to true flattens the current position at the next completed bar and disables further processing until the flag is turned off.
Parameters
Name
Default
Description
TradeVolume
0.1
Volume of each market order.
CandleType
15m time-frame
Primary candle series.
FastMaPeriod
6
Period of the fast LWMA.
SlowMaPeriod
85
Period of the slow LWMA.
MomentumThreshold
0.3
Minimum absolute distance of the momentum indicator from 100 needed to allow entries.
RewardRatio
2
Take-profit multiple relative to the stop-loss.
StopLossPips
20
Stop-loss distance in pips (PriceStep multiples).
MaxPositions
10
Maximum number of volume units (TradeVolume) allowed simultaneously.
EnableTrailing
true
Enables pip-based trailing stop updates.
TrailingStopPips
40
Trailing stop distance in pips.
EnableBreakEven
true
Activates break-even stop management.
BreakEvenTriggerPips
30
Profit (in pips) required before moving the stop to break-even.
BreakEvenOffsetPips
30
Extra pip offset added when the stop relocates to break-even.
ExitSwitch
false
Forces the strategy to flat all exposure on the next completed candle.
Workflow
Configure the desired instrument and candle series, then set risk parameters.
Start the strategy. It subscribes to candles, binds indicators, and begins processing completed bars.
When the entry conditions align, the engine submits a market order and stores stop/target levels.
On every finished candle the risk block evaluates trailing, break-even, and emergency exit rules.
Exits are triggered either by reaching stop/take-profit levels, trailing updates, break-even adjustments, or the emergency switch.
Notes
The conversion leverages StockSharp's indicator binding instead of manual buffer access, ensuring each indicator receives synchronized data.
All calculations rely on the instrument's PriceStep. If the step is zero or missing, risk distances remain disabled to avoid invalid price levels.
The strategy does not modify pending orders; it simply sends market orders to open/close positions, mirroring the way the original EA flattened exposure when thresholds were hit.
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 RiskRewardRatioStrategy : 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 RiskRewardRatioStrategy()
{
_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 risk_reward_ratio_strategy(Strategy):
def __init__(self):
super(risk_reward_ratio_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(risk_reward_ratio_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(risk_reward_ratio_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 risk_reward_ratio_strategy()