StockSharp.Strategies.0451_Three_Ema_Cross.py
5.0.0
Prefix Reserved
dotnet add package StockSharp.Strategies.0451_Three_Ema_Cross.py --version 5.0.0
NuGet\Install-Package StockSharp.Strategies.0451_Three_Ema_Cross.py -Version 5.0.0
<PackageReference Include="StockSharp.Strategies.0451_Three_Ema_Cross.py" Version="5.0.0" />
<PackageVersion Include="StockSharp.Strategies.0451_Three_Ema_Cross.py" Version="5.0.0" />
<PackageReference Include="StockSharp.Strategies.0451_Three_Ema_Cross.py" />
paket add StockSharp.Strategies.0451_Three_Ema_Cross.py --version 5.0.0
#r "nuget: StockSharp.Strategies.0451_Three_Ema_Cross.py, 5.0.0"
#:package StockSharp.Strategies.0451_Three_Ema_Cross.py@5.0.0
#addin nuget:?package=StockSharp.Strategies.0451_Three_Ema_Cross.py&version=5.0.0
#tool nuget:?package=StockSharp.Strategies.0451_Three_Ema_Cross.py&version=5.0.0
Three EMA Cross Strategy (Python Version)
The Three EMA Cross strategy combines a classic fast/slow moving average crossover with a longer trend filter. After the fast EMA crosses above the slow EMA, the strategy waits for a pullback to the fast average while the closing price remains above a broader trend EMA. This setup attempts to capture continuation moves after a brief retracement within the prevailing trend.
Positions are exited when momentum fades and the fast EMA crosses back below the slow EMA. A percentage-based stop loss protects the position if price moves against the trade. The technique works well on markets with persistent trends and tends to avoid choppy ranges.
Details
- Entry Criteria:
- Recent fast EMA cross above slow EMA within last N bars.
- Current close ≥ fast EMA and session low ≤ fast EMA.
- Trend EMA ≤ current close.
- Long/Short: Long only.
- Exit Criteria:
- Fast EMA drops below slow EMA.
- Stops: Stop loss at
stop_loss_percent
of entry price. - Default Values:
FastEmaLength
= 10SlowEmaLength
= 20TrendEmaLength
= 100StopLossPercent
= 2.0CrossBackBars
= 10
- Filters:
- Category: Trend following
- Direction: Long
- Indicators: EMA
- Stops: Yes
- Complexity: Medium
- Timeframe: Any
- Seasonality: No
- Neural networks: No
- Divergence: No
- Risk level: Medium
Learn more about Target Frameworks and .NET Standard.
This package has no dependencies.
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Version | Downloads | Last Updated |
---|---|---|
5.0.0 | 224 | 8/7/2025 |
fixes.