Gradual information diffusion and contrarian strategies

Various rational and behavioral models have been proposed to explain contrarian portfolio returns. In this article, I test the gradual information diffusion model of Hong and Stein [Hong, H., & Stein J. C. (1999). A unified theory of underreaction, momentum trading, and overreaction in asset markets. Journal of Finance, 54, 2143–2184]. Specifically, I study contrarian strategies based on past long-term returns and fundamental value-to-price ratios. Using ex post returns as a proxy for expected returns and size-controlled analyst coverage as a proxy for the rate of information diffusion, I show that contrarian portfolio returns decline monotonically with increasing rates of information diffusion. These results are consistent with the predictions of the Hong and Stein model. In addition, I show that analyst coverage is more important among glamour than value stocks, supporting the view that investors are more prone to decision biases when it comes to pricing hard-to-value glamour stocks for which information is relatively more ambiguous.     

Institutional investors' attention to environmental information,trading strategies,and market impacts: Evidence from China

Using a large proprietary database of intraday high‐frequency trading, we investigate the trading strategies of institutional investors in dealing with the negative environmental event disclosure of listed companies and their impact on markets, aiming to reveal the mechanism of the lack of “green efficiency” in China's capital market from the perspective of institutional investors. The results show that institutional investors react to negative environmental events prior to the announcements, indicating premature information leakage in the market; in addition, their trading behaviors mitigate the immediate effect of negative environmental event announcements on stock price. After the event is disclosed, institutional investors engage in short‐term selling and long‐term buy and hold. This trading strategy undermines the irrational selling of individual investors in the event of disclosure, short‐term decline in stock price, and long‐term reversal of market overreaction. In a China context, institutional investors generally take environmental information into consideration. However, they fail to recognize the long‐term value effect of negative environmental events and instead cater to trading strategies towards market volatility.     

Are institutional investors colluding with manipulators?

This paper examines the trading behavior of institutional investors in Taiwan before, during, and after a manipulation event and determines whether institutional investors benefit from their trading behavior during the period from the year 2000 to 2020. We find that stocks with a low turnover and small market capitalization are the main targets of price manipulators. In addition, the stock price of manipulated firms increases from the start date of the manipulation event, peaks at the end of the event, then falls after the event. Foreign institutions collude with manipulators to exaggerate stock prices for self-benefit. In contrast, securities dealers counter the trading behavior of manipulators and act as market stabilizers, causing them to suffer losses. Moreover, foreign institutions earn higher returns on stocks of manipulated firms with a low turnover during and soon after manipulation; however, they earn a higher return on stocks of manipulated firms with a high turnover in the long run after manipulation.     

Tax loss selling and the contrarian investment strategy

Tax loss selling is examined as a possible explanation for the long term price reversal patterns associated with the contrarian investment strategy. Our empirical results are consistent with a tax effect. When we adjust for size and potential tax loss selling, the abnormally high returns previously found in January are eliminated. These results suggest that short term tax effects are associated with the longer term overreaction or contrarian hypothesis, and at this point cannot be dismissed.     

Stock overreaction to extreme market events

The paper investigates the behavior of individual US stocks during the 21 trading days following the event of extreme movement in the market index on a day. We find that stocks tend to overreact after both positive and negative events, but in a more pronounced way in the latter case. This behavior is more intense when the market exhibits clustered extreme swings, indicating that the overreaction and market volatility are related. We also identify that the overreaction is driven by the performance of loser stocks that revert more strongly, even as they exhibit a lower market beta than winners.     

Day trading and stock price volatility

When an investor buys and sells the same stock on the same day, he is said to have made a day trade. Using the trading records of Finnish traders, this paper examines whether day trading is related to volatility of stock prices. I find a strong positive time-series relation between the number of day trades by individual investors and intraday volatility among heavily day traded stocks. This effect is robust after controlling for a previously documented volume–volatility relation. The result suggests that the joint hypothesis of price pressure and volatility induced day trading dominates the liquidity effects of day trading.     

Neighborhood effect on stock price comovement

We investigate how the geographic distance between firms’ headquarters affects their stock price comovement. Our results show that a firm's stock return has stronger comovement with the returns of nearby firms than with those of distant firms. Being in the same state and/or in the same industry strengthens the return comovement, but does not substitute for the negative effect of geographic distance on price comovement. Firms of similar share price and size also show stronger return comovement, but these factors do not mitigate the negative distance impact. Consistent with investor home bias and neighborhood effect literature, our results suggest that investors’ preference for local stocks and their interactions lead to correlated trading in local stocks and therefore stronger local price comovement.     

Investor heterogeneity and commonality in stock return and liquidity

This paper examines how the trading activities of different investor types are related to common return and liquidity movements. Using a unique dataset, we decompose the daily return and liquidity of individual stocks into price impact components attributable to trades of institutional investors and retail investors. We then investigate the variation of each component relative to market-wide return and liquidity. We show that institutional trades contribute more than retail trades to liquidity commonality. However, retail trades contribute more strongly to return co-movement. The incremental contribution of retail trades to the co-variability of stock returns is more pronounced for firms with high information asymmetry.     

Machine over Mind? Stock price clustering in the era of algorithmic trading

Given the rise of automated trading in the post-decimalization era, we examine time trends in price clustering for exchange traded funds (ETFs) and individual stocks during the post decimalization era. There is limited prior evidence on price clustering for portfolio securities such as ETFs. A striking feature of the evidence is the substantial reduction in clustering over the sample period for ETFs as well as for individual stocks. This decline occurs for trades of all sizes. We attribute the decline in clustering to the increasing prominence of algorithmic trading, which is immune to psychological biases.     

Price effects after one-day abnormal returns in developed and emerging markets: ESG versus traditional indices

This paper examines price effects related to one day abnormal returns on the stock market indices of both developed and emerging countries while accounting for differences between environmental, social, governance (ESG), and conventional indices. Using daily data from MSCI family indices from 2007 to 2020 and various methods to avoid methodological bias, the following hypotheses are tested: after one-day abnormal returns, specific price effects (momentum/contrarian) appear (H1) in cases of positive (H1.1) and negative (H1.2) returns, price effects after one-day abnormal returns are stronger in the case of traditional indices as compared to ESG indices (H2), price effects after one-day abnormal returns are stronger during the crisis period (H3), a dynamic trigger approach is more appropriate for defining abnormal returns than a static approach (H4), price effects after one-day abnormal returns are stronger in emerging markets as compared to developed ones (H5). The results are mixed in the case of H1 and provide no evidence in favor of H2-H5. They also show no significant differences between ESG and conventional indices. The types of detected price effects are the same for the cases of ESG and conventional indices; their power is different in some cases. Overall, a strong contrarian effect is observed in the US stock market after one-day abnormal returns; a trading strategy constructed based on this observation could generate profits from trading. The main results offer additional evidence against the Efficient Market Hypothesis and provide implications that can assist practitioners in beating the market.     

Index futures trading and stock price volatility: Evidence from Denmark and France

This study uses an EGARCH methodology to investigate the impact of index futures trading on the price volatility of two European stock markets. The results show that index futures trading has changed the distribution of stock returns in Denmark and France, however, it has not increased stock price volatility. There is evidence that futures trading has dampened stock price fluctuations in France. The results further show that stocks in Denmark and France exhibit strong volatility persistence and asymmetry, especially during the post-futures period.     

Pricing behavior of exchange traded funds

We attempt to determine whether characteristics found to be effective indicators of individual stock price performance are effective indicators of exchange traded fund (ETF) price performance. Specifically, we test the performance of investing strategies based on separately categorizing ETFs into deciles according to size, trading volume, and momentum. When analyzing the entire sample, we find that the indicators can effectively signal differences in future performance. However, the indicators appear to be indirect proxies for the types of ETFs (broad-based, sector, or international). When we isolate each type of ETF, the indicators are not as effective. The indicators are not as useful for signaling unusual stock price performance of ETFs as they have been for individual stocks. We attribute the distinctly different results found here for ETFs to the unusual characteristics of ETFs that distinguish them from individual stocks. Investing strategies that rely on these indicators for selecting individual stocks may be indirectly driven by stock-specific fundamentals. However, fundamentals are not as meaningful for stock indexes (represented by ETFs) as for individual stocks.

Asymmetric positive feedback trading and stock pricing in China

Defining asymmetry of feedback trading (AFC) as the difference between buying-winners and selling-losers intensities, the paper investigates if AFC impacts stock pricing. We show that buying stocks with low AFC and selling stocks with high AFC makes significant positive returns after controlling traditional pricing factors. The return mainly comes from the long leg and cannot be simply attributed to either mispricing, liquidity, or risk premium. Further study shows that the negative impact of AFC on future stock return is reinforced with an increase in past returns, maximum daily return, relative valuation level, asset growth rate, or operating profit rate. As AFC represents retail trading intensity, the results imply that the inactiveness of retail investors may make price relative underreaction to good news and thus lead to positive expected stock return.     

Stock volatility and trading

Both, rational and behavioral models predict that stock and market volatility affect trading by investors. Tax-induced trading hypothesis predicts that investors increase realization of capital losses short term and capital gains only long term as volatility increases. Behavioral models predict that disposition biases of holding on to losers and disposing of winners intensifies with volatility. We document that market and stock volatility influence stock trading. Evidence on trading in response to rise in market volatility supports tax-loss harvesting hypothesis – abnormal trading of losers increases and winners decreases. However, evidence on trading patterns conditional on individual stock volatility is in support of both tax-loss-harvesting and behavioral models: trading in both losing stocks (tax-loss-harvesting hypothesis) and winning stocks (disposition effect hypothesis) increases with rise in stock volatility.     

Large price movements and short-lived changes in spreads,volume, and selling pressure

In this paper we examine changes in dollar and relative bid-ask spreads of stocks following large price movements. We investigate large increases and decreases separately and link our results to current market microstructure theories on trading activities and spreads. We also look at changes in volume and selling pressure to interpret the changes in trading activity. Our results show that the market reacts differently to price increases and decreases. For large price decreases, trading increases on the sell side even when spreads have increased. For large price increases, trading increases on the buy side during a period of higher spreads. However, the increases in dollar spreads and price pressure are most pronounced at the end of trading day. Our results are consistent with microstructure models that link trading activities and costs to the level of asymmetric information.     

Long-term reactions to large stock price declines and increases in the European stock market: a note on market efficiency

This study tests for underreaction and overreaction in European large cap markets by examining the abnormal returns of those stocks in the EuroStoxx 50 Index following large price increases and decreases. We find that large price increases and declines tend to be followed by average market returns. Thus, our results support the efficient market theory, rather than any of the behaviour finance hypotheses. This insight is contrary to price patterns found in various national markets.     

Limited attention,salient anchor,and the modified MAX effect: Evidence from Taiwan’s stock market

The literature documents that investors overweighing the right-tail probability pursue positively skewed assets, leading to lottery-like stocks overpriced. We find that the lottery anomaly primarily exists among stocks further away from their 52-week high prices. After attention-grabbing events with gambling features, inattentive retail investors become aware of certain stocks’ gambling traits and then net buy more lottery-like stocks, which further promotes the lottery anomaly. However, when such stocks are near their 52-week high price, retail investors tend to place little weight on the likelihood that the stock price will rise beyond the 52-week high, thereby reducing the skewness preference. Overall, our findings suggest that the perception of the 52-week high price as a price ceiling influences skewness preference, and that investor attention is the main determinant of whether anchoring bias affects skewness preference.     

An Investigation of Stock Price Declines Following Corporate Financing Events: Further Evidence

Prior research documents a large downward drift in stock prices following issuances of debt and equity by US firms. We conduct tests based on both stock price and trading volume to provide evidence on the reasons for this apparent market anomaly. We document evidence of earnings management through accruals prior to external financing and lower operating performance afterward that is associated with the amount of capital raised. The earnings management that precedes external financing and the amount of capital raised are associated with both the post-financing decline in stock price and trading volume around earnings announcements that follow for a period of three years. This evidence is consistent with the proposition that firms raise external capital prior to predictable declines in their operating performance and they release upward biased earnings before these events to manage investor expectations. The failure of many investors to incorporate this information into their trading decisions in a timely manner consistent with limited attention and over-confidence appears to drive stock mispricing. Our evidence does not support the conjecture that the financing anomaly is primarily a statistical artifact or that it is a manifestation of the accrual anomaly.     

Momentum strategies with stock index exchange-traded funds

Previously reported momentum profits may not be available to individual investors who have more trading constraints. Therefore, I examine the profitability of momentum strategies with international iShares and US sector exchange-traded funds (ETFs) traded on the NYSE. The index ETFs provide individual investors easy access to international stock markets and US sectors for asset allocations. Using cross-sectional momentum strategies, in contrast to prior research, I find that momentum profits are insignificant for the late 1990s–2014 period. Few country and industry ETFs yield positive results using time series momentum, and the overall performance is worse than the buy-and-hold strategy. Time series momentum offers significant profits during the 2008 global financial crisis, but the profits decline sharply for the post-crisis period.     

Evolution of price effects after one-day abnormal returns in the US stock market

This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market, using Dow Jones Index over the period 1890–2018. We utilise several statistical tests and econometric methods (the modified cumulative abnormal return approach, regression analysis with dummy variables, R/S analysis (Hurst, 1951), and the trading simulation approach). The results suggest that a strong momentum effect between 1940 and 1980 after a day of positive abnormal returns was present in the US stock market, and it was exploitable for profit. However, after the 1980s this has since disappeared. Overall, price effects after one-day abnormal returns during the analysed period tend to be unstable in terms of their strength and direction (momentum or contrarian effect). Nowadays, the evidence for the price effects after one-day abnormal returns in the US stock market is weak. Our results, therefore, are consistent with the Adaptive Market Hypothesis (Lo, 2004).