Short-term overreaction to specific events: Evidence from an emerging market

This paper investigates the short-term overreaction to specific events and whether stock prices are predictable in the Egyptian stock exchange (EGX). We find evidence of the short-term overreaction in the EGX. Losers (“bad news” portfolios) significantly outperform winners (“good news” portfolios) and investors can earn abnormal return by selling the winners and buying losers. Terrorist attacks have negative and significant abnormal returns for three days post event followed by price reversals on day four post event. Whereas, the tensions in the Middle East region have a negative and significant abnormal returns on event day followed by price reversals on day one post event. Moreover, the formation of a new government has no effect on the average abnormal returns post event in the EGX. The results also show that small firms tend to have greater price reversals compared to large firms. Overall, our results provide evidence of the leakage of information in the EGX.     

Stock Returns following Large One-Day Declines: Evidence on Short-Term Reversals and Longer-Term Performance

We examine stock returns following large one-day price declines and find that the bid-ask bounce and the degree of market liquidity explain short-term price reversals. Further, we do not find evidence consistent with the overreaction hypothesis. We observe that securities with large one-day price declines perform poorly over an extended time horizon.     

Intraday price reversals in the US stock index futures market: A 15-year study

This paper gives a long-term assessment of intraday price reversals in the US stock index futures market following large price changes at the market open. We find highly significant intraday price reversals over a 15-year period (November 1987–September 2002) as well as significant intraday reversals in our yearly and day-of-the-week investigations. Moreover, the strength of the intraday overreaction phenomenon seems more pronounced following large positive price changes at the market open. That being said, the question of whether a trader can consistently profit from this information remains open as the significance of intraday price reversals is sharply reduced when gross trading results are adjusted by a bid–ask proxy for transactions costs.     

Long‐Term Return Reversals: Overreaction or Taxes?

Long‐term reversals in U.S. stock returns are better explained as the rational reactions of investors to locked‐in capital gains than an irrational overreaction to news. Predictors of returns based on the overreaction hypothesis have no power, while those that measure locked‐in capital gains do, completely subsuming past returns measures that are traditionally used to predict long‐term returns. In data from Hong Kong, where investment income is not taxed, reversals are nonexistent, and returns are not forecastable either by traditional measures or by measures based on the capital gains lock‐in hypothesis that successfully predict U.S. returns.     

Investor sentiment and stock returns: Some international evidence

We examine whether consumer confidence – as a proxy for individual investor sentiment – affects expected stock returns internationally in 18 industrialized countries. In line with recent evidence for the U.S., we find that sentiment negatively forecasts aggregate stock market returns on average across countries. When sentiment is high, future stock returns tend to be lower and vice versa. This relation also holds for returns of value stocks, growth stocks, small stocks, and for different forecasting horizons. Finally, we employ a cross-sectional perspective and provide evidence that the impact of sentiment on stock returns is higher for countries which have less market integrity and which are culturally more prone to herd-like behavior and overreaction.     

Do Stock Market Investors Overreact?

This paper investigates the evidence on the stock market overreaction hypothesis (ORH), which holds that, if stock prices systematically overshoot as a consequence of excessive investor optimism or pessimism, price reversals should be predictable from past price performance. The ORH stands in contradiction to the efficient markets hypothesis which is a cornerstone of financial economics. This study is unique in the overreaction literature because it is restricted to larger and better-known listed companies, whose shares are more frequently traded. This restriction more or less eliminates two alternative explanations to the overreaction hypothesis: it minimises the influence of bid-ask biases and infrequent trading, and reduces the possibility that reversals are primarily a small-firm phenomenon. The paper also investigates a third alternative explanation, namely that time-varying risk explains the reversal effect. The study employs unbiased methods of return computation and uses data from 1975 to 1991 for nearly 1,000 UK companies. Overall, the evidence appears to be consistent with the overreaction hypothesis, subject to certain qualifications.     

Sentiment stocks

To study how investor sentiment at the firm level affects stock returns, we match more than 58 million social media messages in China with listed firms and construct a measure of individual stock sentiment based on the tone of those messages. We document that positive investor sentiment predicts higher stock risk-adjusted returns in the very short term followed by price reversals. This association between stock sentiment and stock returns is not explained by observable stock characteristics, unobservable time-invariant characteristics, market-wide sentiment, overreaction to news, or changing investor attention. Consistent with theories of investor sentiment, we find that the link between sentiment and stock returns is mainly driven by positive sentiment and non-professional investors. Finally, exploiting a unique feature of the Chinese stock market, we are able to isolate the causal effect of sentiment on stock returns from confounding factors.     

On the Role of Intangible Information and Capital Gains Taxes in Long‐Term Return Reversals

Prior studies have linked long‐term reversals to the magnitude of locked‐in capital gains suggesting that reversals are driven by tax effects and not overreaction. I find that locked‐in capital gains do not explain the reversals in winners when winner returns are based on intangible information. In fact, the reversals for intangible return winners are long lasting and robust to controls for growth in assets and capital expenditures. To the extent that reversals associated with intangible information stem from investors’ overreaction to intangible information and given the prior results linking reversals only to intangible information, my results suggest that overreaction still explains reversal patterns in US stock returns.     

THE EFFECT OF SIZE,BOOK-TO-MARKET EQUITY,PRIOR RETURNS,AND BETA ON STOCK RETURNS: JANUARY VERSUS THE REMAINDER OF THE YEAR

Size and book-to-market equity are shown to transcend beta in explaining stock returns. One possible explanation of the book-to-market equity effect is overreaction. We investigate the effect of size, book-to-market equity, prior returns, and beta on stock returns. We find significant reversals in January consistent with overreaction. We find a strong positive relation between returns and prior returns for February through December. Both patterns are distinct from either a size or book-to-market equity effect. Book-to-market equity is significantly related to returns, with some evidence of a stronger effect in January.     

Further Evidence On Investor Overreaction and Stock Market Seasonality

In a previous paper, we found systematic price reversals for stocks that experience extreme long-term gains or losses: Past losers significantly outperform past winners. We interpreted this finding as consistent with the behavioral hypothesis of investor overreaction. In this follow-up paper, additional evidence is reported that supports the overreaction hypothesis and that is inconsistent with two alternative hypotheses based on firm size and differences in risk, as measured by CAPM-betas. The seasonal pattern of returns is also examined. Excess returns in January are related to both short-term and long-term past performance, as well as to the previous year market return.     

Do the prices of stock index futures in Asia overreact to U.S. market returns?

We extend the overreaction study to interaction of international markets and find that intraday price reversals exist in Asian index futures markets following extreme movement in U.S. market. Profitable opportunities exist after considering transaction cost. We show that the reversal cannot be explained by rational arguments such as risk, liquidity and bid-ask spread. We further observe that a magnitude effect exists. Overreaction is more prominent in the latter period than in the initial period. After calm-down periods, overreaction is greatly reduced. These observations support the explanation that the source of price reversals lies in behavioral biases.     

WINNERS AND LOSERS ON NYSE: A RE-EXAMINATION USING DAILY CLOSING BID-ASK SPREADS

We study a sample of NYSE stocks that experienced a large one-day price change during 1992 and were reported as daily largest percentage gainers and largest percentage losers in the Wall Street Journal. The sample indicates significant reversals during the immediate post-announcement period. We test for market efficiency by using bid-ask spreads obtained from the transactions data for the days immediately after the announcement. The overall results indicate that the returns during the reversal period are less than the average bid-ask spread during the same time. We also find that major losers, firms with ?20 percent to ?50 percent event-date abnormal returns, experience price reversals generating returns that are significantly greater than the average bid-ask spread during that period. We interpret this result as consistent with the overreaction hypothesis. A test of a trading rule to exploit this overreaction is not profitable, providing support for weak-form market efficiency.     

Empirical Identification of Non-Informational Trades Using Trading Volume Data

This paper empirically identifies non-informational and informational trades using stock returns and trading volume data of the U.S., Japanese, and U.K. stock markets and five individual firms. We achieve the identification by imposing a restriction from theoretical considerations. Our results show that trading volume is mainly driven by non-informational trades, while stock price movements are primarily driven by informational trades. We also find that, around the 1987 stock market crash, trading volumes due to non-informational trades increased dramatically, while the decline in stock market prices was due mainly to informational trades. Increases in volatilities both in returns and in trading volumes during and after the crash are mainly due to non-informational trades. Regarding the trading volume-serial correlation in the stock returns relationship, we find evidence that is consistent with theoretical predictions that non-informational components can account for high trading volume accompanied by a low serial correlation of stock returns.     

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).     

Do industries lead stock markets? A reexamination

Hong et al. (2007) report that a number of U.S. industry returns can forecast the stock market using monthly data. Reexamining their results with an extended period, 1946–2013, and data, 48 industries, I find that only one to seven industries have significant predictive ability for the stock market, depending on the significance level (10% or 5%) and the model specifications used. However, I find some evidence of the opposite predictive direction from the stock market to industries. The stock market also performs better than industries in predicting economic growth. Using similar data, 34 industries, and period, 1946–2002, as Hong et al., I find that the results are less significant after data revisions. My overall results are consistent with the efficient market hypothesis.     

Do Low‐Priced Stocks Drive Long‐Term Contrarian Performance on the London Stock Exchange?

We investigate whether low‐priced stocks drive long‐term contrarian performance on the U.K. market. We find that contrarian performance at low, middle, and high price levels is positive. On the Fama‐French risk adjusted basis, we find both low‐priced and middle‐priced losers have significantly positive returns. When we adjust returns by market and liquidity risk, only middle‐priced losers maintain their positive returns. Our results reveal that low‐priced stocks are not fully responsible for contrarian performance. Our empirical evidence is generally consistent with the overreaction hypothesis and behavioral models of value investing.     

Is VIX an investor fear gauge in BRIC equity markets?

This study examines the intertemporal relationships between CBOE market volatility index (VIX) and stock market returns in Brazil, Russia, India, and China (BRIC), and between VIX and U.S. stock market returns, to uncover if VIX serves as an investor fear gauge in BRIC and U.S. markets. We conduct the VIX-returns analysis for the 1993–2007 period.Our results suggest a strong negative contemporaneous relation between daily changes (innovations) in VIX and U.S. stock market returns. This relation is stronger when VIX is higher and more volatile. A significant negative contemporaneous relation between VIX and equity returns also exists for China and Brazil during 1993–2007 and for India during 1993–1997. Similar to the U.S. market, the immediate negative relation between the Brazilian stock returns and VIX changes is much stronger when VIX is both high and more volatile. Our results also indicate a strong asymmetric relation between innovations in VIX and daily stock market returns in U.S., Brazil, and China, suggesting that VIX is more of a gauge of investor fear than investor positive sentiment. However, the asymmetric relationship between stock market returns and VIX is much weaker when VIX is large and more volatile. These results have potential implications for portfolio diversification and for stock market and option trading timing in the equity markets of Brazil, India, and China. Overall, our results indicate that VIX is not only an investor fear gauge for the U.S. stock market but also for the equity markets of China, Brazil, and India.     

Is the Mean Return of Hotel Real Estate Stocks Apt to Overreact to Past Performance?

This study examines the return patterns of hotel real estate stocks in the U.S. during the period from 1990 to 2007.We find that the magnitude and persistence of future mean returns of hotel real estate stocks can be predicted based on past returns, past earnings surprise, trading volume, firm size, and holding period. The empirical evidence found from this paper confirms that short-horizon contrarian profits can be partially explained by the lead-lag effects, while in the intermediate-term price momentum profits and long-term contrarian profits can be partially attributed to the firms’ overreaction to past price changes. Our results support the contrarian/overreaction hypothesis, and they are inconsistent with the Fama-French risk-based hypothesis or the underreaction hypothesis. The study also confirms the earning underreaction hypothesis and finds the high volume stocks tend to earn high momentum profits in the intermediate-term. The study finds that the earning momentum effect for hotel stocks is more short-lived and smaller in magnitude than the market average. Price momentum portfolios (or contrarian portfolios) of big hotel firms underperform small hotel firms and the hotel price momentum portfolio (or contrarian portfolios) significantly underperform the overall market over the intermediate-term (or the long-term). These findings imply that the U.S. hotel industry, particularly the big hotel firms, have experienced relatively conservative growth in the sample period. It suggests that a conservative hotel growth strategy accompanied by an internal-oriented financing policy is proper in a period of prosperity.     

Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in U.S. markets and also compare the excess returns between U.S. market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in U.S. equity index after 1975. During the 1990s break-even costs turned to be negative, –0.06%, even failing to beat a buy-holding strategyin U.S. equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.