The cost of overconfidence in public information

We investigate the effects of investor overconfidence in public information on cross-sectional asset returns. The results show that investors in the US equity market are overconfident about public signals for mature firms that are relatively easy to price—old, large, and dividend-paying firms, value firms, and firms with a higher proportion of tangible assets, little external financing, and low sales growth. However, the effects of the overconfidence on cross-sectional stock returns are reversed quickly and comprise more than half of the short-term return reversals. The risk-adjusted cost of being overconfident about the noisy public signals, measured by return reversals of hedge portfolios formed on unexpected responses, is over 1.1% per month in the first month after portfolio formation, and is still significant despite the active arbitrage trading in the 2000s.     

The dividend month premium

We find an asset pricing anomaly whereby companies have positive abnormal returns in months when they are predicted to issue a dividend. Abnormal returns in predicted dividend months are high relative to other companies and relative to dividend-paying companies in months without a predicted dividend, making risk-based explanations unlikely. The anomaly is as large as the value premium, but less volatile. The premium is consistent with price pressure from dividend-seeking investors. Measures of liquidity and demand for dividends are associated with larger price increases in the period before the ex-day (when there is no news about the dividend) and larger reversals afterward.     

Asymmetric return dynamics and technical trading strategies

We investigate the profitability of technical trading strategies based on an asymmetric reverting property of stock returns. We identify an asymmetry in return dynamics for daily returns on the S&P 500 index. Return dynamics evolve along a positive (negative) unconditional mean after a prior positive (negative) return. The trading strategies based on this asymmetry generate a positive return for buy signals, a negative return for sell signals, and a positive return for the spread between buy and sell signals. Our results imply that the observed asymmetry in return dynamics is the main source of profitability for the implied strategies, thereby corroborating arguments for the usefulness of technical trading strategies.     

The Value Spread

We decompose the cross-sectional variance of firms' book-to-market ratios using both a long U.S. panel and a shorter international panel. In contrast to typical aggregate time-series results, transitory cross-sectional variation in expected 15-year stock returns causes only a relatively small fraction (20 to 25 percent) of the total cross-sectional variance. The remaining dispersion can be explained by expected 15-year profitability and persistence of valuation levels. Furthermore, this fraction appears stable across time and across types of stocks. We also show that the expected return on value-minus-growth strategies is atypically high at times when their spread in book-to-market ratios is wide.     

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.     

Are idiosyncratic volatility and MAX priced in the Canadian market?

The negative relationship between realized idiosyncratic volatility (RIvol) and future returns uncovered by Ang et al. (2006) for the U.S. market has been attributed to return reversals. For the Canadian market where return reversals are considerably less important, we find that RIvol is positively related to future returns, even after controlling for risk loadings, illiquidity and reversals. Unlike the findings of Bali et al. (2001) for the U.S. market, we find that the relationship between extreme positive returns (MAX) and future returns for the Canadian market is positive and that idiosyncratic volatility continues to be consistently positively related to future returns after controlling for MAX. We find evidence that suggests that reversals for stocks with extreme daily returns are confined to (typically small) stocks with low institutional holdings.     

Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using Pacific Basin stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property, and that the asymmetric reverting property of stock returns is exploitable in generating profitable buy and sell signals for technical trading rules. We show that the positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric dynamics of stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical analysis.     

Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

Reversal of Monday returns

This paper elaborates an interesting aspect of the Monday anomaly: Monday returns are relatively more likely to reverse over the subsequent days. We document that, although the Monday low-return anomaly disappeared, the subsequent reversal of Monday returns remains robust to date. The reversals, measured over a five-day horizon, are pervasive across international stock markets, reasonably stable over time, significant following both positive and negative Monday returns, and not confined to extreme Monday returns. Trading strategies designed to exploit these reversals earn economic profits. We examine potential explanations for the reversal of Monday returns using trading flows data of investor types from Korea. All predictions of the Foster and Viswanathan [J. Finance, 1993, 48, 187–211] model are confirmed: volatility is higher, trading volume is lower, market depth is lower and price impact costs are higher on Mondays. The model implies lower price quality on Mondays, but does not specifically predict reversal of Monday returns. We show that the trading intensity of international/institutional investors is lower on Mondays. This appears to make the market relatively more susceptible to individual investors’ trading, which is negatively correlated with international/institutional investors. Thus, Monday returns are relatively more likely to reverse during the subsequent days of the week when institutional investors trade more aggressively.     

JUMPS,NEWS, AND SUBSEQUENT RETURN DYNAMICS: AN INTRADAY STUDY

We detect jumps in a high-frequency price series of exchange-traded funds (ETFs) that track the broad indexes of U.S. equity markets. Although many jumps (43%) are related to macroeconomic news, more jumps (57%) are not. No-news jumps are followed by significant return reversals for at least 60 minutes. The return dynamics after news-related jumps vary with the news characteristics. Scheduled-news jumps are followed by reversals, whereas unscheduled-news jumps are followed by momentum. Whether related to news or not, negative jumps are followed by stronger return reversals than are positive jumps.     

Distinguishing Between Rationales for Short‐Horizon Predictability of Stock Returns

In this paper, we shed light on short‐horizon return reversals. We show theoretically that a risk‐based rationale for reversals implies a relation between returns and past order flow, whereas a reversion in beliefs of biased agents does not do so. The empirical results indicate that returns are more strongly related to own‐return lags than to lagged order imbalances. Thus, the evidence suggests that monthly reversals are not completely captured by inventory effects and may be driven, in part, by belief reversion. We do find that returns are cross‐sectionally related to lagged imbalance innovations at horizons longer than a month.     

Does program trading contribute to excess comovement of stock returns?

Daily returns of stocks with high program trading comove more with each other but less with others. This significant comovement is disconnected with market movements and news of fundamentals and becomes stronger when market uncertainty is higher. It can be explained by neither the hypotheses of gradual information diffusion and liquidity provision nor the effects of quantitative trading signals, earnings announcements and index fund trading. Its non-fundamental nature is further demonstrated by the observation of program trading stimulating return reversals. Underlying this comovement is the high persistence of program trading. Our findings support the theory of habitat investing and demonstrate program trading creates a distinct source of excess return comovement.     

Is asymmetric mean-reverting pattern in stock returns systematic? Evidence from Pacific-basin markets in the short-horizon

This paper applies asymmetric nonlinear smooth transition generalized autoregressive conditional heteroskedasticity (ANST-GARCH) models to the analysis of mean-reversion and time-varying volatility in weekly index returns of the stock markets of nine countries in the Pacific-basin. It finds that the returns exhibit an asymmetric pattern of return reversals, viz., on average, a negative return reverts more quickly, with a greater magnitude, to a positive return than a positive return reverting to a negative one. The asymmetric pattern of return reversals is directly associated with the unequal pricing behavior on the part of investors. Following a negative return shock, investors do not appear to require any additional premium to the leverage effect; instead they actually neutralize the risk in the form of a reduced premium! The reduction in risk premium causes not only the current stock price to rise but also the realized negative return to revert faster with a greater magnitude.     

The cyclical behavior of the risk of value strategy: Evidence from Taiwan

Using Taiwanese equity data, we find that value-minus-growth strategies (HML) earn significantly positive expected returns, and that the value spread in B/M is widened following a financial crisis. Value firms disinvest more than growth firms in bad times. The HML betas are higher for periods of higher expected equity premium, higher market volatility, and lower GDP growth. Furthermore, while the HML betas are negative and positive for the pre- and post-crisis sample, respectively, the value (growth) betas increase (decrease) from pre- to post-crisis period. Also, the beta-premium sensitivity is positive for HML and value stocks, and negative for growth stocks.     

Idiosyncratic risk and expected returns in frontier markets: Evidence from GCC

We investigate the pricing of idiosyncratic volatility of seven frontier markets in six GCC countries. We find a significant (marginal) negative relationship between expected returns and lagged idiosyncratic volatility for individual stocks in Saudi Arabia (Qatar) but none in Kuwait and Abu Dhabi. However, when we estimate conditional idiosyncratic volatility either by EGARCH or AR Models, the relationship turns positive. Introducing unexpected idiosyncratic volatility as an explanatory variable to control for any unexpected returns uncovers the true relationship between expected idiosyncratic volatility and expected returns. The evidence turns out to be robust for return reversals and other control variables. Moreover, the pricing of idiosyncratic risk is less evident in higher country governance and seems to be unrelated to the degree of financial development.     

Asset liquidity and stock returns

We document the significant predictive power of firms' asset liquidity in the cross section of subsequent stock returns. The annual return spread between portfolios featuring the highest and lowest levels of asset liquidity is significantly positive. Our proposed measure of asset liquidity outperforms those measures developed by Gopalan et al. (2012) in predicting returns. The asset liquidity anomaly also provides significantly positive alphas when controlling for the asset pricing factors in the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model. Asset liquidity exhibits strong return forecasting power even after controlling for acknowledged cross-sectional determinants of return. The positive relation between asset liquidity and future returns tends to be stronger for firms with greater asset productivity, higher quality cash flow and lower capital investment.     

An examination of the relation between asymmetric risk measures,prior returns and expected daily stock returns

We use a sample of individual firm stock returns over the 1988–2009 time period to determine whether: (1) expected daily returns are related to asymmetric risk measures, (2) expected daily returns are related to the directional change of the prior day's price, and (3) our results are robust to the addition of firm size, book-to-market equity and liquidity. We find that investors are compensated for asymmetric risk; however, the positive risk–return relation is present only for our smallest firm quintile. We find a short-term return reversal present in all subgroups, except for the largest firms in our sample. We also document that the low volatility anomaly may be related to firm size and liquidity.     

Are return seasonalities due to risk or mispricing?

Stocks tend to earn high or low returns relative to other stocks every year in the same month (Heston and Sadka, 2008). We show these seasonalities are balanced out by seasonal reversals: a stock that has a high expected return relative to other stocks in one month has a low expected return relative to other stocks in the other months. The seasonalities and seasonal reversals add up to zero over the calendar year, which is consistent with seasonalities being driven by temporary mispricing. Seasonal reversals are economically large and statistically highly significant, and they resemble, but are distinct from, long-term reversals.     

News-driven return reversals: Liquidity provision ahead of earnings announcements

This study documents a six-fold increase in short-term return reversals during earnings announcements relative to non-announcement periods. Following prior research, we use reversals as a proxy for expected returns market makers demand for providing liquidity. Our findings highlight significant time-series variation in the magnitude of short-term return reversals and suggest that market makers demand higher expected returns prior to earnings announcements because of increased inventory risks that stem from holding net positions through the release of anticipated earnings news. Collectively, our findings suggest that uncertainty regarding anticipated information events elicits predictable increases in the compensation demanded for providing liquidity and that these increases significantly affect the dynamics and information content of market prices.     

Is Financial Flexibility a Priced Factor in the Stock Market?

This paper develops a factor analysis–based measure for shifts in corporate financial flexibility (FFLEX) that can be observed from public accounting information. Companies that experience positive shifts in FFLEX are associated with higher future investment growth opportunities. We show that FFLEX is a robust determinant of future stock returns. Firms that have increased their financial flexibility are associated with lower stock returns in the subsequent period. A zero‐cost return portfolio produces a significant positive monthly premium of 0.69%, which is driven by covariance (risk). Risk inherent in the flexibility factor is not explained away by either prominent pricing characteristics or factors.