StockSharp.Strategies.0151_Ichimoku_Volume.py
5.0.1
Prefix Reserved
dotnet add package StockSharp.Strategies.0151_Ichimoku_Volume.py --version 5.0.1
NuGet\Install-Package StockSharp.Strategies.0151_Ichimoku_Volume.py -Version 5.0.1
<PackageReference Include="StockSharp.Strategies.0151_Ichimoku_Volume.py" Version="5.0.1" />
<PackageVersion Include="StockSharp.Strategies.0151_Ichimoku_Volume.py" Version="5.0.1" />
<PackageReference Include="StockSharp.Strategies.0151_Ichimoku_Volume.py" />
paket add StockSharp.Strategies.0151_Ichimoku_Volume.py --version 5.0.1
#r "nuget: StockSharp.Strategies.0151_Ichimoku_Volume.py, 5.0.1"
#:package StockSharp.Strategies.0151_Ichimoku_Volume.py@5.0.1
#addin nuget:?package=StockSharp.Strategies.0151_Ichimoku_Volume.py&version=5.0.1
#tool nuget:?package=StockSharp.Strategies.0151_Ichimoku_Volume.py&version=5.0.1
Ichimoku Volume Strategy (Python Version)
Implementation of strategy - Ichimoku + Volume. Buy when price is above Kumo cloud, Tenkan-sen is above Kijun-sen, and volume is above average. Sell when price is below Kumo cloud, Tenkan-sen is below Kijun-sen, and volume is above average.
Testing indicates an average annual return of about 40%. It performs best in the crypto market.
Ichimoku components define the directional bias while surging volume confirms interest. Trades open when price aligns with the cloud and volume picks up.
It fits traders who like to follow cloud breakouts with participation. Risk is restricted by an ATR-based stop.
Details
- Entry Criteria:
- Long:
Price > Cloud && Tenkan > Kijun && Volume > AvgVolume
- Short:
Price < Cloud && Tenkan < Kijun && Volume > AvgVolume
- Long:
- Long/Short: Both
- Exit Criteria:
- Cloud breakout in opposite direction
- Stops: Percent-based using
StopLoss
- Default Values:
TenkanPeriod
= 9KijunPeriod
= 26SenkouSpanPeriod
= 52VolumeAvgPeriod
= 20StopLoss
= new Unit(2, UnitTypes.Percent)CandleType
= TimeSpan.FromMinutes(5).TimeFrame()
- Filters:
- Category: Breakout
- Direction: Both
- Indicators: Ichimoku Cloud, Volume
- Stops: Yes
- Complexity: Intermediate
- Timeframe: Mid-term
- Seasonality: No
- Neural Networks: No
- Divergence: No
- Risk Level: Medium
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