Overnight Returns Research Articles

Dissecting the lottery‐like anomaly: Evidence from China

AbstractThis paper dissects the lottery‐like anomaly in Chinese A‐share stocks by decomposing total stock returns into overnight and intraday returns. Our findings indicate that negative overnight returns are concentrated among lottery‐like stocks, and the lottery‐like anomaly is primarily driven by the overnight return component. Considering the unique institutional features of China, we further show that the lottery‐like anomaly induced by overnight returns is more pronounced in stocks with a high gambling preference among retail investors and high limits of arbitrage. Overall, our results suggest that investors' optimism and trading constraints have a substantial impact on market efficiency in China.

Only strong short-term contrarian effect exists in Chinese stock market: The role of the T+1 trading mechanism

We use an alternative sorting method which groups stocks into return intervals rather than percentiles to test the relationship between the T+1 trading mechanism and the short-term contrarian effect in the China's A-share market. Our sample period is from January 2010 to December 2020. China's stock market exhibits a significant contrarian effect in daily, weekly, and monthly frequencies, while the momentum effect is not significant. This paper argues that the special T+1 trading mechanism of China's stock market is the reason for this typical anomaly. The essence of the T+1 trading mechanism is a marketability put option, and this paper takes the volatility as the core of the analysis. This study shows that stock market volatility has a significant impact on the overnight return, with higher volatility leading to a higher discount. Through different daily, weekly, and monthly frequency groupings, the study finds that the winner's portfolio would reverse significantly in the next period. Under the T+1 mechanism, the high return stock portfolio is also characterized by high volatility and high turnover. The contrarian effect of China's stock market is unique in that both the winner's portfolio and the loser's portfolio will fall, but the winner's portfolio will fall more. The reversal of the winner's portfolio dominates in the entire market. The paper provides a new explanation for the contrarian effect and adds a unique explanation to the study of worldwide contrarian effect.

Overnight return reversal in the Chinese stock market

ABSTRACT This article shows that the overnight return reversal is strong at a firm level in the Chinese stock market: the overnight return negatively predicts the first half-hour return of individual stocks. We explain this phenomenon from the perspective of the pre-open auction mechanism. Taking a step further, we find that the Chinese stock market shows a pattern with average negative overnight return and positive first half-hour return. Additionally, the predictability is stronger on negative overnight returns and negative informational shocks compared with positive overnight returns and positive informational shocks. Both phenomena may be led by the combined effects of the pre-open auction mechanism and T + 1 trading rule.

Asymmetric trading restriction and return comovement

This study decomposes the overall return comovement into intraday and overnight comovement based on a model-free framework. It shows that intraday return comovement contributes the most to the overall return comovement, but the impact of overnight return comovement is persistent. Investors under the market with asymmetric trading restrictions (ATR) tend to sell stocks early in the market and buy them near the end of the market. This correlated trading behavior contributes to the specific comovement in stock returns, especially the overnight return. Our findings remain solid even after controlling for more stock attributes and changing the proxies for return comovement and investor trading behavior. We also document a weakening (reinforcing) effect of the short-selling mechanism (disposition effect) on the ATR-induced return comovement. Our results provide a deeper understanding of investors’ trading behavior under ultra-short-term trading restrictions and the source of return comovement in the literature.

Equity markets volatility clustering: A multiscale analysis of intraday and overnight returns

Volatility clustering, widely observed in daily equity market returns, has not been analyzed for high-resolution intraday and overnight returns, nor has its time scale dependency been systematically explored. This paper examines the volatility clustering of intraday and overnight returns in 15 global equity markets, both developed and emerging. Findings reveal universal volatility clustering in intraday and overnight returns across various time scales, from daily to monthly and beyond. It appears that the volatility clustering of overnight returns is even more pronounced than intraday returns. However, the cross clustering between two volatility series is generally weak within each market. These observations suggest both short- and long-term investment risks, providing meaningful insights for equity market investors’ risk management.

Tail risk forecasting with semiparametric regression models by incorporating overnight information

AbstractThis research incorporates realized volatility and overnight information into risk models, wherein the overnight return often contributes significantly to the total return volatility. Extending a semiparametric regression model based on asymmetric Laplace distribution, we propose a family of RES‐CAViaR‐oc models by adding overnight return and realized measures as a nowcasting technique for simultaneously forecasting Value‐at‐Risk (VaR) and expected shortfall (ES). We utilize Bayesian methods to estimate unknown parameters and forecast VaR and ES jointly for the proposed model family. We also conduct extensive backtests based on joint elicitability of the pair of VaR and ES during the out‐of‐sample period. Our empirical study on four international stock indices confirms that overnight return and realized volatility are vital in tail risk forecasting.

The Intraday Heterogeneity and Risk Pricing Reversal Between Day and Night: Evidence from China

ABSTRACT Using a large panel of high-frequency trading data, this article investigates the intraday heterogeneity of risk pricing process in the Chinese stock market. Our research reveals that the financial assets in China exhibit intraday beta variation: high/low market risk level assets, with beta values above/below unity, tend to have downward/upward sloping beta trajectories across the intraday trading periods. We confirm a trend reversal of the risk-return relation between day and night in the Chinese market: the assets’ intraday returns are negatively correlated with their market risk level, whereas their overnight returns are positively correlated with their risk level. Further investigation shows a connection between the intraday beta variation and the day-night reversal anomaly, and the risk-return reversal between day and night can be partially explained by the intraday beta variation of financial assets. After controlling for the intraday beta variation, the risk-return reversal anomaly between day and night becomes less pronounced in the Chinese market.

야간수익률과 고유변동성이 기대수익률에 미치는 영향

Purpose - This paper examines whether overnight returns and idiosyncratic volatility (IVOL) jointly affects the cross-section of expected stock returns in the Korean stock market.
 Design/methodology/approach - Constructing 5x5 bivariate monthly portfolios independently sorted on overnight returns and IVOL, this paper tests whether overpricing of stocks with high overnight returns is more pronounced for the stocks that also have high IVOL. In addition, we also investigate whether time-variation in the degree of overpricing for those stocks can be explained by market volatility.
 Findings - Our results show that stocks having both high overnight returns and high IVOL exhibit strong negative returns in the future. In contrast, we are unable to observe such negative returns for the stocks that have high overnight returns and low IVOL. This suggests that overpricing of stocks with high overnight returns is concentrated for the stocks having high IVOL. Moreover, we also find that the degree to which such stocks are overpriced is negatively related to market volatility.
 Research implications or Originality - his paper is the first attempt to explore whether degree of overpricing of stocks having high overnight returns is related to IVOL. We also discover time-varying property of overpricing is jointly driven by overnight returns and IVOL. Our results indicate that IVOL might help explain other previously documented stock return anomalies, suggesting interesting topics for future research.

Earnings announcements in China: Overnight-intraday disparity

Based on a unique arrangement of trading and disclosure times around earnings announcements in the Chinese stock market, we provide evidence of a striking overnight-intraday disparity in terms of the reaction to earnings news. Specifically, we find that the overnight period exhibits a strong and consistent reaction to earnings announcements, whereas the intraday period trades against both the earnings news and the prior market reaction during the overnight period. In addition, we show that abnormal overnight returns on earnings announcement days exhibit strong predictability for future stock returns, consistent with the overnight returns containing value-relevant signals. In contrast, we observe no return predictability for abnormal intraday returns on earnings announcement days, which as a result, also undermines the return predictability of abnormal daily returns. We propose possible explanations for the overnight-intraday disparity. We conclude that the differences in trading mechanisms between the two periods as well as in investor composition likely drive the phenomenon.

Overnight returns and investor sentiment: Further evidence from the Taiwan stock market

This study reexamines the relationship between overnight returns and investor sentiment—a finding documented by Aboody et al. (2018, JFQA)—on the Taiwan Stock Exchange (TWSE). We aim to verify whether the overnight returns on the TWSE are reflective of investor sentiment and clarify how the trading activities of different investor types affect the patterns of overnight returns. We show that overnight returns cause short-term persistence and long-term return reversal on the TWSE, both of which are driven by investor sentiment. In addition, the percentage of retail trading enhances the patterns of overnight returns. A high individual trading volume ratio raises the tendency of short-term overnight return persistence. Our findings provide further support for the validity of overnight returns in measuring investor sentiment. When overnight returns fail to work as a valid sentiment proxy in many non-US markets, their success on the TWSE suggests that the connection with the US market, the preference of investors for chasing information, and the structure of market participants are likely to be the most important determinants of whether they are reflective of investor sentiment.

Analyzing time-different connectedness among systemic financial markets during the financial crisis and conventional era: New evidence from the VARX-DCC-MEGARCH model

ABSTRACT This investigation utilized the VARX-DCC-MEGARCH model assimilated with skewed-t density to analyze the time-different (i.e., daytime, overnight, and daily) connectedness among S&P 500, DAX 30, FTSE-100, Nikkei 225, and Shanghai Composite Index. This investigation discovered that the current daytime returns transmission from the DAX 30, FTSE 100, and Nikkei 225 index to ensuing overnight returns of the S&P 500 index was inconsequential during the stable period. The study also quantified that shocks befallen in the current overnight returns of the S&P 500 partake bidirectional and negative ties with shocks that occurred in subsequent day-wise returns of the DAX 30 index. Moreover, during crises, only the Shanghai composite index spillovers the volatility of the FTSE 100 index. The study revealed a leverage effect for the day-wise return of the S&P 500, DAX 30, and overnight returns of the FTSE 100 index.

When do they trade? Heterogeneous investors in China

This paper investigates whether different investor clienteles trade at different time of the day in the Chinese stock market. We document a unique overnight and intraday return pattern, which is that negative overnight returns are followed by positive daytime reversals. We find that compared to retail investors, institutions trade more actively around the market opening and closing. More importantly, the results show that stock prices move with institutions’, rather than retail investors’ trades across the day. This suggests that clientele trading time could be a potential explanation for the distinct return pattern observed in the Chinese stock market.

Arbitrage Opportunities and Overnight Returns in Leveraged and Inverse ETFs

Arbitrage Opportunities and Overnight Returns in Leveraged and Inverse ETFs

Distracted by the Stock Market: Stock Market Overnight Returns and Worker Productivity

Distracted by the Stock Market: Stock Market Overnight Returns and Worker Productivity

The Asymmetric Overnight Return Anomaly in the Chinese Stock Market

Traditional asset pricing theory suggests that to compensate for the uncertainty that investors bear, risky assets should generate considerably higher rates of return than the risk-free rate. However, the overnight return anomaly in the Chinese stock market, which refers to the anomaly that overnight return is significantly negative, contradicts the risk–return trade-off. We find that this anomaly is asymmetrical, as the overnight return is significantly negative after a negative daytime return, whereas the anomaly does not occur following a positive daytime return. We explain this anomaly from the perspective of investor attention. We show that the attention of individual investors behaves asymmetrically such that they draw more attention on negative daytime returns, and play an essential role in explaining the overnight return puzzle.

A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information

AbstractThis study is the first to examine the impacts of overnight and intraday oil futures cross‐market information on predicting the US stock market volatility the high‐frequency data. In‐sample estimations present that high overnight oil futures RV can lead to high RV of the S&P 500. Moreover, negative overnight returns are more powerful than positive components, implying the existence of the leverage effect. From statistical and economic perspectives, out‐of‐sample results indicate that the decompositions of overnight oil futures and intraday RVs, based on signed intraday returns, can significantly increase the models' predictive ability. Finally, when considering the US stock market overnight effect, the decompositions are still useful to predict volatility, especially during high US stock market fluctuations and high and low EPU states.

Overnight returns, daytime reversals, and future stock returns: Is China different?

Akbas et al. (2021) demonstrate that a more intense daily “tug of war” between overnight noise traders and daytime arbitrageurs predicts higher future returns in the US market. We investigate whether the daily tug of war contains predictive information about future stock returns in China. Using the frequency of negative daytime reversals, we find no significant difference in the future returns of stocks with a high versus a low level of intensity in this tug of war. However, we find persistent positive overnight returns followed by daytime reversals of almost similar magnitudes once we decompose the future returns into their overnight and daytime components. Thus, positive returns of the overnight component and negative returns of the daytime component cancel out each other, resulting in no predictive relationship between the daily tug of war and future returns in China.

The Pricing of ESG: Evidence From Overnight Return and Intraday Return

By featuring the link of investor heterogeneity to the persistence of the overnight and intraday components of returns, we examine the ESG–overnight (intraday) alpha relation in the Chinese stock market. The empirical results show that ESG score has a significantly negative effect on the expected stock overnight returns in Fama–MacBeth regression. Consistently, given the biggest market capitalization and the least illiquidity subsamples, the trading strategies by going long (short) the top (bottom) ESG quintile would yield negative profits. In addition, we conduct the implication of the ESG pricing by dividing the full sample into green stock subsample and sin stock subsample, and the empirical results present that the ESG pricing is pervasive of the green-type stocks. These conclusions verify the pricing of ESG and support the conjecture that green stocks have lower expected returns because ESG investors value sustainability.

A Behavior Perspective of Distress Anomaly: Evidence From Overnight Returns

Using measurement of overnight returns, this article documents that trading behaviors due to information shocks and investor sentiments contribute to distress anomaly. We find that stocks with the highest (lowest) overnight returns are accompanied with the greatest (smallest) distress risk premium, and accordingly, a conditional distress probability portfolio composed with double sort of overnight returns and distress probability would yield significant profitability. The regression outcomes demonstrate that probability of default significantly interacts with average overnight returns in explaining the future stock returns. The conventional distress anomaly is subsumed by the conditional distress factor, but not vice versa; and only profits of conventional distress-probability portfolios, not of the conditional portfolios, mainly come from stocks with characteristics that are associated with stock mispricing. The empirical results indicate that investors hold distressed stocks longer than expected because positive information shocks occur with high level of information supply and good information quality.

Overnight volatility, realized volatility, and option pricing

AbstractThe equity market is not trading around the clock, and the overnight information has been proved be important for understanding pricing anomalies, improving volatility forecasting accuracy, and so forth. However, there is little research investigating its impact on option pricing. In this paper, we provide a framework that integrates intraday, overnight returns, and realized volatility simultaneously within an augmented Autoregressive Volatility model. The analytical option‐pricing formula for the new model is derived through the closed‐form moment generation function. The empirical results based on S&P 500 index options show that distinguishing the overnight component from daily returns has the potential capability to reduce the pricing errors, both in‐sample and out‐of‐sample.