// --- Parameters --- Periods = Param("BB Periods", 20, 5, 50, 1); Width = Param("BB Width", 2.0, 1.0, 4.0, 0.1); ATRPeriod = Param("ATR Stop", 10, 5, 30, 1); // --- Calculations --- BBLower = BBandBot(C, Periods, Width); BBUpper = BBandTop(C, Periods, Width); TrendMA = MA(C, 200); ATR_Val = ATR(ATRPeriod);
This article will serve as your encyclopedic guide. We will cover the syntax, logic, advanced scanning, portfolio backtesting, and real-time trading integration. Before writing sophisticated strategies, you must understand how AFL thinks. 1.1 Vector Processing vs. Iterative Looping Unlike Python or C++, AFL is inherently vector-based . This means an operation applies to the entire price array simultaneously. amibroker afl code
RSI_14 = RSI(14); VolumeSurge = V > MA(V, 50) * 1.5; Filter = RSI_14 < 30 AND VolumeSurge; AddColumn(C, "Close", 1.2); AddColumn(RSI_14, "RSI", 1.2); AddColumn(V, "Volume", 1.0); Run this on 5,000 stocks. AmiBroker will return a list of only those meeting the criteria. Exploration allows you to output historical values into a grid. // --- Parameters --- Periods = Param("BB Periods",
for(i=0; i<BarCount; i++) myArray[i] = MA(C, 200)[i]; RSI_14 = RSI(14); VolumeSurge = V > MA(V, 50) * 1
// --- Entry Conditions --- BuySignal = C < BBLower AND C > TrendMA; // Price below lower band but above 200 MA Buy = ExRem(BuySignal, SellSignal); // Remove consecutive buy signals
Introduction: Why AFL is the Backbone of Quantitative Trading In the world of retail algorithmic trading, few platforms offer the perfect blend of power, speed, and customization like AmiBroker . For over two decades, professional traders and hobbyists alike have relied on AmiBroker for backtesting, scanning, and real-time trading. The secret sauce behind this dominance is AFL (AmiBroker Formula Language) .