Is risk higher during non-trading periods? The risk trade-off for intraday versus overnight market returns

Riedel, Christoph; Wagner, Niklas

doi:10.1016/j.intfin.2015.05.012

Cited by 20 publications

(7 citation statements)

References 31 publications

(27 reference statements)

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“…The overall volatility is expected to decrease after the transfer. However, previous studies agree that volatility during trading hours differs from volatility during non-trading hours (Hansen and Lunde, 2006;de Pooter et al, 2008;Bollerslev et al, 2009;Riedel and Wagner, 2015). This research also examines the volatility change during the intraday and overnight periods after the transfer.…”

Section: Literature Review and Hypothesesmentioning

confidence: 91%

“…However, the intraday period is the day's most active period during which investors execute most of their trades. Market liquidity is relatively high during the intraday period for the majority of stock SEF 39,1 exchanges (French and Roll, 1986;Riedel and Wagner, 2015). Therefore, the documented increase in liquidity levels caused by an ST might be more implicit during trading hours.…”

Section: Intraday and Overnight Periodsmentioning

confidence: 99%

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The long-term effects of section transfers on return volatility: Intraday and overnight periods

Abo

2021

SEF

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Purpose Studies on transfers to a more regulated section show an increase in information disclosure and stocks’ liquidity levels. Classical theories suggest that volatility should also be reduced. This study aims to analyse the long-term effects of a section transfer to a more regulated section (TSE 1/TSE 2) on stock return volatility. Design/methodology/approach This study uses an empirical framework relying on two-sample t-tests and panel regressions. These use robust standard errors and control for fixed effects, day effects and macroeconomic factors. The return variance of comparable stocks’ benchmark sample, instead of market variance, is used as a control variable. Comparable stocks operate within the same industry and do not transfer during the sample period. The authors test our results’ robustness using generalized autoregressive conditional heteroskedasticity estimates. Findings The study’s main findings show that pre-transferred stocks are more volatile than the stocks’ benchmark sample. The transfer to a more regulated section leads to a gradual decrease in the total daily stock return volatility, intraday return volatility and overnight return volatility. Originality/value To the best of my knowledge, this study is the first to empirically address the volatility change caused by the stocks’ transfer to a more regulated section. This study highlights the benefits of choosing section transfers to reduce volatility.

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Section: Literature Review and Hypothesesmentioning

confidence: 91%

Section: Intraday and Overnight Periodsmentioning

confidence: 99%

The long-term effects of section transfers on return volatility: Intraday and overnight periods

Abo

2021

SEF

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“…kets is positive (e.g., Lockwood and Mcinish, 1990;Masulis and Ng, 1995;Karolyi and Stulz, 1996;Chan et al, 1996;Gutierrez et al, 2009;Kang and Babbs, 2010;Kelly and Clark, 2011;Berkman et al, 2012;Riedel and Wagner, 2015;Liu and Tse, 2017;Lou et al, 2019). In contrast, a small number of studies report opposite findings for Chinese stock markets.…”

Section: Introductionmentioning

confidence: 99%

The Overnight Return Puzzle and the 'T+1' Trading Rule in Chinese Stock Markets

Qiao

Dam

2019

SSRN Journal

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“…Earlier research related to risk contribution of business hour and non-business hour trading are the following: Riedel and Wagner (2015) use a conditional GARCH model for major stock markets indices covering US, France, German and Japan, and illustrate the tail risk of overnight returns is higher than intraday market returns. By using a joint distribution of overnight and daytime returns with a copula, Liu and Tse (2017b) find that overnight returns have a lower VAR and expected loss in the US market.…”

Section: Introductionmentioning

confidence: 99%

Empirical differences between the overnight and day trading hour returns

2018

CFRI

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Purpose The purpose of this paper is to provide a stable model which covers market information of return to examine the empirical differences between the returns during night and day in Chinese commodity futures market. Design/methodology/approach Commodity indices are constructed using principal components analysis to represent the market returns for day and night trading in the Chinese commodity futures market. Then VAR models are employed to predict the commodity indices’ returns and squared returns. Findings The symmetric VAR model failed to model the market returns since the asymmetric effects of positive and negative returns are not taken into account. By allowing asymmetric behavior among positive and negative variables, asymmetric VAR model is utilized to trace the leading effect of overnight returns to daytime trading returns. However, the symmetric VAR model outperforms the asymmetric model when evaluating the predictive power of squared returns during night trading hours. Two major results based on asymmetric model for the return are: There is a 6-day leading effect of nighttime return to daytime return in Chinese commodity futures market. It is risky to hold day trading position overnight. Research limitations/implications Asymmetric VAR model provides a new approach to forecasting the direction of price movement. Practical implications Investment managers are able to create a stable portfolio contains major market information. Day and night traders are likely to gain some suggestions to discover arbitrage opportunities. Social implications Since there is no commodity futures index in China, the method for creating indices for Chinese commodity futures is provided to market regulators. Originality/value Combining principal component analysis and asymmetric VAR model provides a stable and predictable model to obtain market information.

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Is risk higher during non-trading periods? The risk trade-off for intraday versus overnight market returns

Cited by 20 publications

References 31 publications

The long-term effects of section transfers on return volatility: Intraday and overnight periods

The long-term effects of section transfers on return volatility: Intraday and overnight periods

The Overnight Return Puzzle and the 'T+1' Trading Rule in Chinese Stock Markets

Empirical differences between the overnight and day trading hour returns

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