An uncertainty quantification framework for the achievability of backtesting results of trading strategies

Raymond Hon-Fu Chan, Alfred Ka-Chun Ma and Lanston Lane-Chun Yeung

Abstract

Backtesting has always been indispensable in analyzing the profitability of trading strategies in the empirical finance literature. When measuring return, while most of the literature implicitly assumes that a trade can be implemented at the same closing price as the one generating the trading signal, some empirical evidence has been found suggesting that this assumption presents a significant challenge to the robustness of their results. Hence, several alternative return measurements have been proposed, including the incorporation of a one-day delay to mitigate this execution latency. The mix of opinions on this issue prompted us to quantify whether backtesting results could be achieved with such implementation uncertainty. In particular, we propose a framework for implementing and backtesting trading strategies. A new concept called return-at-risk is introduced to quantify such an ability, and we illustrate our proposed framework using a representative class of trading strategies. Our results show that a significant number of technical trading strategies with positive returns are found to be unviable in the presence of implementation uncertainty.