Patterns in the Chaos: The Moving Hurst Indicator and Its Role in Indian Market Volatility

Param Shah, Ankush Raje () and Jigarkumar Shah ()
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Param Shah: Department of Computer Science Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382426, India
Ankush Raje: Department of Mathematics, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382426, India
Jigarkumar Shah: Department of Information and Communication Technology, School of Technology, Pandit Deendayal Energy University, Gandhinagar 382426, India

JRFM, 2024, vol. 17, issue 9, 1-11

Abstract: Estimating the impact of volatility in financial markets is challenging due to complex dynamics, including random fluctuations involving white noise and trend components involving brown noise. In this study, we explore the potential of leveraging the chaotic properties of time series data for improved accuracy. Specifically, we introduce a novel trading strategy based on a technical indicator, Moving Hurst (MH). MH utilizes the Hurst exponent which characterizes the chaotic properties of time series. We hypothesize and then prove empirically that MH outperforms traditional indicators like Moving Averages (MA) in analyzing Indian equity indices and capturing profitable trading opportunities while mitigating the impact of volatility.

Keywords: hurst exponent; fractal analysis; volatility; Indian equity markets; chaos theory (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2024
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