Intraday and Overnight Volatility Clustering Effect

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Volatility clustering is a phenomenon observed in financial markets where periods of high volatility tend to cluster together, followed by periods of low volatility. This pattern suggests that extreme price movements are not randomly distributed over time but rather occur in clusters or groups.

Volatility clustering has undergone extensive study within the daily timeframe. Reference [1] delves into volatility clustering within intraday and overnight timeframes. It specifically investigates clustering within each timeframe and between them. The authors pointed out,

This paper explores the stylized fact of volatility clustering for intraday and overnight returns in global equity markets. As a widely accepted notion, three factors are crucial for investing in equities: return, risk, and time…Our analysis leads us to several consistent conclusions:

(i) Volatility clustering is universal in intraday and overnight returns across multiple time scales, spanning from daily to weekly, monthly, and even longer periods;

(ii) Most markets display more pronounced volatility clustering in overnight returns than in intraday returns;

(iii) Cross clustering between the volatilities of intraday and overnight returns appears relatively weak in each market, particularly on small and medium time scales;

(iv) The consistency across developed and emerging markets significantly outweighs the divergence, underlining the universal nature of volatility clustering.

The paper also provides guidance on how to use the results to design trading strategies,

Given the volatility clustering phenomenon in overnight returns and the feedback of large overnight volatility in generating positive returns, one can arbitrage during periods of significant overnight fluctuations by adopting a ‘buy on close and sell on opening’ strategy. This can help avoid negative returns triggered by large intraday fluctuations. From a long-term investment strategy perspective, it is advisable to adopt a short position during periods of intraday volatility clustering and a long position during periods of overnight volatility clustering, as our analysis indicates that the likelihood of both large intraday and overnight volatility clustering occurring simultaneously is relatively low.

We believe that the results have practical implications, as they will help better manage intraday and overnight risks.

Let us know what you think in the comments below or in the discussion forum.

References

[1] Xiaojun Zhao, Na Zhang, Yali Zhang, Chao Xu, Pengjian Shang, Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns, Journal of Empirical Finance 77 (2024) 101487

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