// 1. Define Strategy Parameters fast_period = Param("Fast MA", 10, 2, 50, 1); slow_period = Param("Slow MA", 30, 5, 200, 1); // 2. Calculate Indicators fast_ma = MA(Close, fast_period); slow_ma = MA(Close, slow_period); // 3. Define Entry and Exit Rules Buy = Cross(fast_ma, slow_ma); // Buy when fast MA crosses above slow MA Sell = Cross(slow_ma, fast_ma); // Sell when fast MA crosses below slow MA // 4. Handle Short Selling (Set to 0 if trading Long-Only) Short = 0; Cover = 0; // 5. Plot Arrows on the Chart for Visual Verification PlotShapes(IIf(Buy, shapeUpArrow, shapeNone), colorGreen, 0, Low, -15); PlotShapes(IIf(Sell, shapeDownArrow, shapeNone), colorRed, 0, High, -15); Use code with caution. 5. Advanced AFL Concepts: Portfolio Backtesting and Loops
to build features based on market-wide breadth (e.g., number of stocks above their 200-day EMA). Stack Overflow Example: Multi-Indicator Composite Feature
Create reusable code blocks to simplify complex strategies.
In the world of trading and technical analysis, the ability to code custom indicators and trading systems gives a major edge. For users of AmiBroker, one of the most powerful charting and backtesting platforms available, that ability comes through the AmiBroker Formula Language (AFL). This comprehensive guide explores everything you need to know about AFL code—from basic concepts and functions to advanced optimization techniques and real-world strategy examples.
Yes, AFL syntax is very similar to C++ and other C-based languages, making it relatively easy to learn for developers, but it is optimized specifically for array calculations. amibroker afl code
// 4. Combined "Deep" Feature // Weighted combination for a ranking or ML input DeepFeature = (0.5 * MomFeature) + (0.3 * VolFeature) + (0.2 * VolTrend);
If you are looking to get a custom script created, you might consider professional AFL writing services to translate your strategy into code.
// Define Moving Averages MA_Short = MA(Close, 50); MA_Long = MA(Close, 200);
AmiBroker supports up to 64 optimization variables, returning a sorted list of the most profitable parameter sets. Define Entry and Exit Rules Buy = Cross(fast_ma,
Ensure variables are appropriately scoped and initialized to prevent unexpected values during execution. Array Handling: Since AFL is array-based, verify that functions like are applied correctly to historical data arrays. Optimization of "Foreign" Data: SetForeign()
Every statement in AFL must end with a semicolon ; .
This comprehensive guide breaks down AmiBroker AFL code from fundamental concepts to advanced architecture. 1. What is AmiBroker AFL Code?
BuyPrice = Close; // Execute at closing price SellPrice = Close; Use code with caution. 3. Handling Position Sizing AFL allows you to define strict money management rules. PositionSize = -10; // Allocate 10% of equity per trade Use code with caution. Common Use Cases for AFL Code AFL is built for vectorized processing
Mastering AmiBroker AFL Code: The Ultimate Guide to Algorithmic Trading
is a high-level, C-like scripting language specifically designed for technical analysis, strategy development, and algorithmic trading. Unlike traditional programming languages that process data one step at a time, AFL is built for vectorized processing , allowing it to handle massive arrays of historical price data with near-assembler level speed. Core Concepts of AFL Code
// Define Setup Criteria MA_Volume = MA( Volume, 50 ); VolumeBreakout = Volume > ( MA_Volume * 2 ); // Twice the 50-day average volume PriceFilter = Close > 10 AND Close < 500; // Filter out penny stocks and ultra-high prices // The Master Filter Condition Filter = VolumeBreakout AND PriceFilter AND Close > Open; // Configure the Output Report Grid AddColumn( Close, "Closing Price", 1.2, colorDefault, IIf( Close > Open, colorGreen, colorRed ) ); AddColumn( Volume, "Today's Volume", 1.0 ); AddColumn( MA_Volume, "50-Day Avg Volume", 1.0 ); AddColumn( ( Volume / MA_Volume ), "Volume Multiple", 1.1 ); Use code with caution. Exploration Layout: