Introduction to Backtesting a Trading System using Amibroker

Backtesting is a critical step in validating your strategy. It’s the process of applying trading rules to historical market data to assess how a strategy would have performed in the past. This gives traders an indication of how well a system might work in the future. Amibroker, with its powerful backtesting engine, is an excellent tool for this purpose, allowing traders to simulate and optimize strategies with ease.

Why Backtesting Matters

Backtesting is essential for any serious trader. It helps determine if a trading strategy is robust, profitable, and worth using in live markets. Without backtesting, you’re essentially going in blind, making decisions based on gut feelings or incomplete data. A well-executed backtest helps uncover potential weaknesses in a system and provides insights into how well it might perform across different market conditions.

Key Features of Amibroker for Backtesting

Amibroker offers several powerful features that make backtesting a breeze. From custom scripting using Amibroker Formula Language (AFL) to detailed performance reports, you can backtest strategies with high precision. Some standout features include:

• Historical Data Testing: Apply your strategy to years of historical market data.
• Robust Optimization Tools: Fine-tune your trading parameters to achieve better results.
• Portfolio Testing: Test strategies across multiple stocks or markets at once.
• Detailed Reports: View performance metrics like profit factors, drawdowns, and win rates, giving you a clear picture of how the strategy holds up.

Simple EMA Crossover Trading System

//Marketcalls Backtesting Tutorial

_SECTION_BEGIN("EMA Crossover Trading System");
SetChartOptions(0,chartShowArrows|chartShowDates);

//Plot CandleSticks
Plot( C, "Price", ParamColor( "Color", colorDefault ), ParamStyle( "Style", styleCandle, maskPrice ) );


//Compute EMA 20 and EMA50

EMA20 = EMA(C,20);
EMA50 = EMA(C,50);


//Plot the EMA lines


Plot(EMA20,"EMA20",colorGreen,styleLine);  //Shorter Length EMA
Plot(EMA50,"EMA50",colorblue,styleLine);  //Longer Length EMA


//Logical Buy and Sell Rules

Buy = Cross(EMA20,EMA50);  //Positive Crossover 
sell = Cross(EMA50,EMA20); //Negative Crossover

//Short AND Cover for a system which wants to go short


//Plot Buy and Sell Arrows

/* Plot Buy and Sell Signal Arrows */

PlotShapes(IIf(Buy, shapeSquare, shapeNone),colorGreen, 0, L, Offset=-40);
PlotShapes(IIf(Buy, shapeSquare, shapeNone),colorLime, 0,L, Offset=-50);
PlotShapes(IIf(Buy, shapeUpArrow, shapeNone),colorWhite, 0,L, Offset=-45);
PlotShapes(IIf(Sell, shapeSquare, shapeNone),colorRed, 0, H, Offset=40);
PlotShapes(IIf(Sell, shapeSquare, shapeNone),colorOrange, 0,H, Offset=50);
PlotShapes(IIf(Sell, shapeDownArrow, shapeNone),colorWhite, 0,H, Offset=-45);



//At what Price to Buy

BuyPrice = Close;
SellPrice = Close;


//Money Management - How much to buy


SetPositionSize( 100000, spsValue ); // 1 Lakh in each trade

//PositionSize = 100000;



//Trade Delays

SetTradeDelays(0,0,0,0);




_SECTION_END();

Steps to Backtest Using Amibroker

1. Create or Load a Strategy: Start by creating or loading your trading strategy using AFL. Define your buy and sell conditions clearly.
2. Select a Time Frame: Choose the historical data range you want to test on. This could be one year, five years, or more, depending on how thorough you want your backtest to be.
3. Run the Backtest: Using Amibroker’s backtesting engine, run your strategy on the selected data. Amibroker will automatically execute buy/sell orders based on your defined rules and provide a detailed performance report.
4. Analyze Results: Look through the performance metrics, such as win/loss ratios, total profits, and drawdowns. This will help you determine whether your strategy is ready for live trading or needs further tweaking.
5. Optimize the Strategy: If needed, optimize your parameters by running multiple backtests with different settings to find the best combination that yields optimal results.

Key Metrics to Consider

When analyzing backtest results, pay close attention to certain metrics that indicate the strength and reliability of a strategy. Some important ones include:

• Profit Factor: A ratio of gross profits to gross losses. A profit factor above 1.5 is typically considered good.
• Max Drawdown: The largest peak-to-valley decline in the portfolio’s equity. Keeping drawdowns low is critical to managing risk.
• Winning Percentage: This metric tells you how often your trades are successful.
• Sharpe Ratio: A measure of risk-adjusted return. The higher, the better.

Is Your Strategy Ready for the Markets?

Backtesting is a powerful way to evaluate the potential of your trading system before risking real capital. Amibroker’s comprehensive set of tools allows traders to efficiently simulate, optimize, and refine their strategies. However, while backtesting offers valuable insights, remember that it’s not foolproof. Markets evolve, and a strategy that worked in the past may not perform the same in the future. Still, by properly backtesting your trading system using Amibroker, you can significantly increase your chances of success in the live markets.