The goal of this project is to open the black box behind backtesting trading strategies and demonstrate that this is one of the cases where the implementation practices are far from the theoretical background that should govern them.
Backtesting has been identified as a part of risk management since it provides an estimate of the portfolio's potential risk under various scenarios contributing to more robust portfolio management practices and playing a critical role in regulatory compliance. Conversely, backtesting has evolved into an industry standard and is an essential component in the formulation, evaluation, and implementation of investment strategies. By enabling the rigorous evaluation and improvement of trading strategies, backtesting helps to ensure that prices reflect all available information more accurately, contributing to market efficiency and stability.
The research objectives of this research Virtual Network are:
1) Fill the gap in the literature by investigating potential approaches to developing a statistically accurate backtesting framework for financial institutions.
2) Propose several approaches for constructing a statistically valid backtesting framework, considering their potential benefits, drawbacks, and implementation challenges.
3) Offer recommendations for implementing a statistically valid backtesting framework in practice and outlining potential avenues for future research in this area.