From dusk till dawn (and vice versa): Overnight-versus-daytime reversals and feedback trading

Although overnight-versus-daytime return reversals have often been ascribed to the heterogeneous clienteles of the overnight and daytime sessions, there exists no evidence to date on how those clienteles' trading behaviour motivates these reversals. We empirically investigate this issue for the first time by assessing whether these reversals are the result of feedback trading during overnight/daytime hours. Drawing on the S&P 500 ETF for the 1993–2021 period, we find that overnight (daytime) feedback trading largely motivates the expected positive (negative) overnight (daytime) returns; in line with this, days entailing the expected negative overnight-versus-daytime return reversals accommodate stronger feedback trading at the daily (i.e., close-to-close) frequency. Daytime feedback trading is present when the immediately preceding overnight session's returns are positive, while overnight feedback trading reveals a strong Monday-effect. We also show that overnight-versus-daytime variations of feedback trading hold across other large US ETFs.     

A leader of the world commodity futures markets in the making? The case of China's commodity futures

We use the daily data of 16 commodity futures contracts traded in China and corresponding foreign markets (the US, the UK, Japan, and Malaysia) to analyze the linkages between markets. Several findings are noteworthy. First, trading returns of foreign markets, such as the US, have significant impact on China's overnight (close-to-open) returns and vice-versa. Second, daytime (open-to-close) returns of many Chinese commodity futures contracts are not led by foreign daytime returns. Finally, the close-to-close returns analysis suggests that there are no significant lead-lag relationships between the Chinese and foreign markets. These results suggest that (1) the Chinese commodity futures markets are information-efficient, and (2) they are likely to be driven by local market dynamics occurring during the daytime trading session.     

Overreaction of country ETFs to US market returns: Intraday vs. daily horizons and the role of synchronized trading

In this paper we study the intraday price formation process of country Exchange Traded Funds (ETFs). We identify specific parts of the US trading day during which Net Asset Values (NAVs), currency rates, premiums and discounts, and the S&P 500 index have special effects on ETF prices, and characterize a special intraday and overnight updating structure between these variables and country ETF prices. Our findings suggest a structural difference between synchronized and non-synchronized trading hours. While during synchronized trading hours ETF prices are mostly driven by their NAV returns, during non-synchronized trading hours the S&P 500 index has a dominant effect. This effect also exceeds the one that the S&P 500 index has on the underlying foreign indices and suggests an overreaction to US market returns when foreign markets are closed.     

Overreaction of index futures in Hong Kong

In this paper we show that the pricing error of index futures relative to its fair value can be used to identify investors' overreaction in index futures market. Specifically, when investors are overly pessimistic (optimistic), the prices of index futures are well below (above) their fair values. When the excess pessimism (optimism) is gone, the prices of index futures revert to catch up with their fair values. After taking into consideration transaction cost, execution time lag, and risk adjustment, profitable strategies can be developed to exploit this overreaction. We find that overreaction exists during intraday trading and market closing.     

Bidders’ strategic timing of acquisition announcements and the effects of payment method on target returns and competing bids

Using a sample of acquisition announcements released during trading versus nontrading hours, this study examines how the strategic timing of acquisition announcements determines the impact of the method of payment on target stock returns and competition among bidders. For overnight acquisition announcements, we find that cash payment offers positively and significantly affect acquisition premiums and target returns, yet these results do not hold for daytime announcements. Cash payment offers made during nontrading hours are more likely to deter potential bidders and complete proposed transactions. However, we find no such relationship for daytime announcements. These findings suggest that the timing of acquisition announcements by bidders is important for assessing the effects of payment method as a signal of target valuation and a preemption of competing bids.     

Information Flow and Pricing Errors: A Unified Approach to Estimation and Testing

This study examines whether rates of information flow differbetween trading and nontrading periods, and whether the variancesof pricing errors differ at the open and close of trading. Theapproach improves on existing methods by allowing for correlationbetween pricing errors and information flow, and by conductinginferences at the individual security level. The daytime rateof information flow is about seven times the overnight rate,and the variances of pricing errors at the open are not differentfrom those at the close of trading. This evidence differs fromexisting results based on return variance ratios.     

The timing of information arrival and overnight returns

This paper examines the information assimilation of overnight returns after positive or negative news arriving during RHT (regular-hours-trading) or AHT (after-hour-trading). We first show that overnight returns are informative of earnings news arriving either during RHT or AHT, and the effects are strongest on the first day after the announcement. Our results then suggest that positive (negative) overnight returns after good (bad) earnings news arrival increase (decrease) CARs, with more pronounced effects for news released AHT. We further show that the market takes the timing of news release into account and reacts negatively to those released during AHT, causing significant under-performance in the subsequent CAR. Lastly, our finding of market underreaction to good news and overreaction to bad news when it is released during AHT suggest that it may be more appropriate for managers to release all news during RHT when market participants are at their trading desks.     

24-Hour realized volatilities and transatlantic volatility interdependence

This paper proposes an innovative econometric approach for the computation of 24-h realized volatilities across stock markets in Europe and the US. In particular, we deal with the problem of non-synchronous trading hours and intermittent high-frequency data during overnight non-trading periods. Using high-frequency data for the Euro Stoxx 50 and the S&P 500 Index between 2003 and 2011, we combine squared overnight returns and realized daytime variances to obtain synchronous 24-h realized volatilities for both markets. Specifically, we use a piece-wise weighting procedure for daytime and overnight information to take into account structural breaks in the relation between the two. To demonstrate the new possibilities that our approach opens up, we use the new 24-h volatilities to estimate a bivariate extension of Corsi et al.’s [Econom. Rev., 2008, 27(1–3), 46–78] HAR-GARCH model. The results suggest that the contemporaneous transatlantic volatility interdependence is remarkably stable over the sample period.     

A comparison of transaction costs on Xetra and on Nasdaq

Abstract

In today's financial world, providing high quality of order execution at low transaction costs is vitally important to the competitiveness of trading platforms; thus the stock market's microstructure has become a subject of fierce debate and models for computing transaction costs have been needed for quite a while. Capital market synergetics is appropriate to investigate the market microstructure's effectiveness and is implemented in the computer program KapSyn.

In this paper we compare transaction costs for small, medium-size and block-size orders on each exchange, examining different market scenarios. By investigating the peculiarities of Xetra and of Nasdaq we point out their comparative advantages: calculation results clearly show the high operating efficiency of Nasdaq's small-order execution system and Xetra's favourable execution of medium-size and block-size orders. Investors' trading decisions may benefit from taking these results into account. For policy makers and academics these findings contribute to the debate about the optimal design of a market microstructure by highlighting the areas of high performance.     

Overnight public information,order placement,and price discovery during the pre-opening period

This study examines the impact of corporate news announcements released overnight on price discovery during the pre-opening period in the Australian Securities Exchange. Our results suggest that the presence of these announcements increases the efficiency of indicative opening prices and that the intensity of these announcements significantly influences the aggressiveness of pre-opening orders. Using earnings announcements to compare the speed of price adjustments in response to overnight and daytime information of a homogeneous type, we find that prices respond immediately to overnight news upon the commencement of trading, whereas adjustments based on trading-hours news tend not to be instantaneous. Overall, our evidence highlights the important role of the pre-opening period in price discovery and the prospect of further enhancing this role by timing the release of public information to occur during non-trading hours.     

Do DOW returns really influence the intraday Spanish stock market behavior?

Although the behavior of the Spanish stock market has been studied from many different points of view, none of the previous research has ever analyzed the influence of previous daytime, overnight and daily returns from the DOW and IBEX upon 5-min intraday returns of the IBEX throughout the complete trading session. Clear evidence is provided relative to the influence of the DOW. The main finding that it underreacts to the DOW returns in the first hours of trading but overreacts during the last 2 h (after the opening of the US markets) would help to develop a profitable trading strategy.     

Information salience,investor sentiment,and stock returns: The case of British soccer betting

Soccer clubs listed on the London Stock Exchange provide a unique way of testing stock price reactions to different types of news. For each firm, two pieces of information are released on a weekly basis: experts' expectations about game outcomes through the betting odds, and the game outcomes themselves. The stock market reacts strongly to news about game results, generating significant abnormal returns and trading volumes. We find evidence that the abnormal returns for the winning teams do not reflect rational expectations but are high due to overreactions induced by investor sentiment. This is not the case for losing teams. There is no market reaction to the release of new betting information although these betting odds are excellent predictors of the game outcomes. The discrepancy between the strong market reaction to game results and the lack of reaction to betting odds may not only be the result from overreaction to game results but also from the lack of informational content or information salience of the betting information. Therefore, we also examine whether betting information can be used to predict short-run stock returns subsequent to the games. We reach mixed results: we conclude that investors ignore some non-salient public information such as betting odds, and betting information predicts a stock price overreaction to game results which is influenced by investors' mood (especially when the teams are strongly expected to win).     

When do investors gamble in the stock market?

Recent studies have uncovered gambling-motivated trading activities in financial markets in which investors seek lottery-type payoffs by using financial assets. Building on prospect theory, this study provides an important complement to prior research and investigates what period that investors make gambling-motivated trading in the stock market. Examining data from the Chinese stock market, investors are revealed to have asymmetric gambling preferences in gain and loss domains. Investors' gambling motivations are more easily triggered when the market is experiencing a loss. In such periods of time, investors may preferentially opt for lottery-type stocks that offer them a small chance to earn an extreme return at the risk of a likely small loss, simply due to their ‘aversion to a sure loss’.     

Investor heterogeneity and momentum-based trading strategies in China

The conventional momentum strategy performs poorly overall in China, because stock prices behave very differently when markets are open for trading versus when they are closed. Stocks that are past intraday (overnight) winners persistently outperform those that are past intraday (overnight) losers in the subsequent intraday (overnight) periods. However, the same intraday- (overnight-) momentum strategy suffers dramatically in the subsequent overnight (intraday) periods. Further analysis shows that past intraday (overnight) winners tend to be more (less) speculative stocks which are highly demanded during the day (night). Overall, our results are consistent with investor heterogeneity, and this persistent tug of war virtually eliminates the effectiveness of investors pursuing the momentum-based trading strategy in China.     

Do bulls and bears move across borders? International transmission of stock returns and volatility

This article investigates empirically how returns and volatilitiesof stock indices are correlated between the Tokyo and New Yorkmarkets. Using intradaily data that define daytime and overnightreturns for both markets, we find that Tokyo (New York) daytimereturns are correlated with New York (Tokyo) overnight returns.We interpret this result as evidence that information revealedduring the trading hours of one market has a global impact onthe returns of the other market. In order to extract the globalfactor from the daytime returns of one market, we propose andestimate a signal extraction model with GARCH processes.     

The Determinants of the Treasury Security Yield Curve

Investors' security demands and two points on the yield curve are jointly determined using a disaggregated structural model of the U.S. Treasury securities market. The empirical results indicate that the structural model is capable of accurately explaining Treasury yields and that changes in a variety of nonyield variables affect the yield curve. Among these nonyield variables are Treasury security supplies, which are found to have significant but somewhat volatile impacts depending on investors' wealth flows. The within-sample predictions from the structural model are also compared to those of a naive model.     

Is Stock Market Overreaction Persistent Over Time?

This paper examines the stability and persistence of the market overreaction hypothesis as posited by DeBondt and Thaler (1985 and 1987), and reinforced by Chopra, Lakonishok, and Ritter (1992). Using monthly CRSP data for the period 1926 through 1992, we find that returns obtained from a contrarian investment strategy are not time-stationary. Specifically, there is no winner-loser portfolio relationship during the post-war period of 1940_50s. The relationship resumes during the pre-energy-crisis subperiod, but weakens again during the post-energy-crisis subperiod. The effectiveness of trading based upon the overreaction hypothesis is, therefore, suspect.     

A note on the importance of overnight information in risk management models

This paper examines the economic value of overnight information to users of risk management models. In addition to the information revealed by overseas markets that trade during the (domestic) overnight period, this paper exploits information generated via recent innovations in the structure of financial markets. In particular, certain securities (and associated derivative products) can now be traded at any time over a 24-h period. As such, it is now possible to make use of information generated by trading, in (almost) identical securities, during the overnight period. Of the securities that are available over such time periods, S&P 500 related products are by far the most actively traded and are, therefore, the subject of this paper. Using a variety of conditional volatility models that allow time-dependent information flow within (and across) three different S&P 500 markets, the results show that overnight information flow has a significant impact on the conditional volatility of daytime traded S&P 500 securities. Moreover (time-consistent) forecasts from models that incorporate overnight information are shown to have economic value to risk managers. In particular, Value-at-Risk (VaR) models based on these conditional volatility models are shown to be more accurate than VaR models that ignore overnight information.     

Asymmetric information and the bid-ask spread: an empirical comparison between automated order execution and open outcry auction

This study examines the components of the bid-ask spread on the Sydney Futures Exchange. The Exchange uses open outcry auction for daytime trading, and switches to a screen-based automated order execution system at 16:30 h for overnight trading. After controlling for proxies of order flow characteristics, the study finds that screen-based traders are more sensitive to market volatility than floor-based traders in setting the bid-ask spread. Spreads from floor trading have a smaller adverse information component but a larger order processing cost component relative to screen trading. The results suggest that floor traders can better assess the presence of adverse information than screen traders.     

Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment

Using options price data on the Taiwanese stock market, we propose an options trading strategy based on the forecasting of volatility direction. The forecasting models are constructed with the incorporation of absolute returns, heterogeneous autoregressive-realized volatility (HAR-RV), and proxy of investor sentiment. After we take into consideration the margin-based transaction costs, the results of our simulated trading indicate that a straddle trading strategy that considers the forecasting of volatility direction with the incorporation of market turnover achieves the best Sharpe ratios. Our trading algorithm bridges the gap between options trading, market volatility, and the information content of investor overreaction.