Investigating mean reversion in financial markets using Hurst Model

Abstract

In the dynamic world of financial markets, the prices of assets can exhibit dramatic fluctuations, sometimes soaring to dizzying heights or plummeting to alarming lows. However, amidst the chaos, a fascinating phenomenon emerges: a tendency for prices to revert back to their long-term average or mean level. This concept known as mean reversion has intrigued traders, investors, and researchers for decades. Understanding mean reversion provides valuable insights into market dynamics, investor behavior, and the potential for profitable trading strategies. The aim of this study was to empirically investigate mean reversion in financial markets. This study employed a Hurst model for a sample of five financial markets from June 1, 2018 to June 1, 2023. The findings revealed that four out of the five sampled financial markets exhibit mean reversion, which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjusting portfolio weights to take advantage of potential return predictability and manage risk.