Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics

TL;DR

This study examines how COVID-19 affected financial market efficiency by analyzing time-varying fractional stable dynamics, revealing significant efficiency loss in US markets but less impact on Asian and Australian markets.

Contribution

It introduces a dynamic estimation method for efficiency indicators using fractional Le9vy-stable motion with a novel discount factor parameter.

Findings

US indices showed a strong loss of efficiency during COVID-19

Asian and Australian indices were less affected, with questionable inefficiency

The method improves density forecasts for observed price returns

Abstract

This paper investigates the impact of COVID-19 on financial markets. It focuses on the evolution of the market efficiency, using two efficiency indicators: the Hurst exponent and the memory parameter of a fractional L\'evy-stable motion. The second approach combines, in the same model of dynamic, an alpha-stable distribution and a dependence structure between price returns. We provide a dynamic estimation method for the two efficiency indicators. This method introduces a free parameter, the discount factor, which we select so as to get the best alpha-stable density forecasts for observed price returns. The application to stock indices during the COVID-19 crisis shows a strong loss of efficiency for US indices. On the opposite, Asian and Australian indices seem less affected and the inefficiency of these markets during the COVID-19 crisis is even questionable.