Validate your financial models with historical data

Backtesting is a framework that uses historical data to validate financial models, including trading strategies and risk management models. Depending on the goals of validation, financial professional use more than one indicator or methodology to measure the effectiveness of financial models.

Backtesting is routinely performed in trading and risk management. As a result, there are a number of dedicated backtesting techniques specific to these two areas.

In trading, common backtesting techniques include:

  • In-sample vs. out-of-sample testing
  • Walk-forward analysis or walk-forward optimization
  • Instrument-level analysis vs. portfolio-level assessment

In risk management, backtesting is generally applied to value-at-risk (VaR) and is also known as VaR backtesting. There are various VaR backtesting techniques, such as:

  • Basel's traffic light test
  • Binomial test
  • Kupiec's proportion of failures test
  • Kupiec's time until first failure test
  • Christoffersen's conditional coverage mixed test
  • Christoffersen's conditional coverage independence test
  • Haas' time between failures or mixed Kupiec test
  • Haas' time between failures independence test

For more on backtesting, see MATLAB®, Financial Toolbox™, Trading Toolbox™, and Risk Management Toolbox™.

See also: algorithmic trading, automated trading, market risk, risk management

Risk Management with MATLAB

Develop, manage, review, and challenge internal and regulatory models.