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Investigating mean reversion in financial markets using Hurst Model

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  • Samuel Tabot Enow

    (Research Associate, The IIE VEGA School)

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. Key Words:Mean reversion, Hurst model, Efficient market hypothesis, Stock markets, Portfolio management

Suggested Citation

  • Samuel Tabot Enow, 2023. "Investigating mean reversion in financial markets using Hurst Model," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 12(6), pages 197-201, September.
    • Handle: RePEc:rbs:ijbrss:v:12:y:2023:i:6:p:197-201
    DOI: 10.20525/ijrbs.v12i6.2664
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    References listed on IDEAS

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    1. Chaves, Denis B. & Viswanathan, Vivek, 2016. "Momentum and mean-reversion in commodity spot and futures markets," Journal of Commodity Markets, Elsevier, vol. 3(1), pages 39-53.
    2. Fama, Eugene F & French, Kenneth R, 1988. "Permanent and Temporary Components of Stock Prices," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 246-273, April.
    3. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    4. Gianfreda, Angelica & Maranzano, Paolo & Parisio, Lucia & Pelagatti, Matteo, 2023. "Testing for integration and cointegration when time series are observed with noise," Economic Modelling, Elsevier, vol. 125(C).
    5. Latini, Luca & Piccirilli, Marco & Vargiolu, Tiziano, 2019. "Mean-reverting no-arbitrage additive models for forward curves in energy markets," Energy Economics, Elsevier, vol. 79(C), pages 157-170.
    6. Luigi Buzzacchi & Luca Ghezzi, 2023. "Mean Reversion Lessens Mean Blur: Evidence from the S&P Composite Index," IJFS, MDPI, vol. 11(1), pages 1-13, January.
    7. Kurmas Akdogan, 2018. "Mean-reversion and structural change in European food prices," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 163-173.
    8. Robert Engle & Clive Granger, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    9. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    10. Maren Diane Schmeck & Stefan Schwerin, 2021. "The Effect of Mean-Reverting Processes in the Pricing of Options in the Energy Market: An Arithmetic Approach," Risks, MDPI, vol. 9(5), pages 1-19, May.
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