混乱中的模式：移动赫斯特指标及其在印度市场波动中的作用

Q4 Business, Management and Accounting

Journal of Risk and Financial Management Pub Date : 2024-09-03 DOI:10.3390/jrfm17090390

Param Shah, Ankush Raje, Jigarkumar Shah

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引用次数: 0

摘要

由于复杂的动态变化，包括涉及白噪声的随机波动和涉及棕噪声的趋势成分，估算金融市场波动的影响具有挑战性。在本研究中，我们探索了利用时间序列数据的混沌特性提高准确性的潜力。具体来说，我们引入了一种基于技术指标 Moving Hurst (MH) 的新型交易策略。MH 利用了表征时间序列混沌特性的赫斯特指数。我们假设并通过实证证明，在分析印度股票指数和捕捉有利可图的交易机会时，MH 优于移动平均线（MA）等传统指标，同时还能减轻波动的影响。

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

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.

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