A fractional stable process with time-varying parameters is estimated.
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Selection of the free parameters leading to the best forecast of distribution.
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An indicator of market efficiency is proposed and compared to a Hurst exponent.
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Application to stock price series during the COVID-19 crisis.
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 Lévy-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.
Keywords
Alpha-stable distribution
Dynamic estimation
Efficient market hypothesis
Financial crisis
Hurst exponent
Data availability
The data used are publicly available from Yahoo finance.