Price Change

Supporting:

• Momentum by Narasimhan Jegadeesh and Sheridan Titman (2011): This paper provides a comprehensive review of the momentum effect in stock markets, specifically focusing on the phenomenon where past price movements predict future price movements. The authors present substantial evidence that stocks performing well (or poorly) over a three to twelve-month period tend to continue performing well (or poorly) over the subsequent three to twelve months. This persistence in price trends is identified as the momentum effect. The study also highlights that momentum strategies, which exploit this effect by buying past winners and selling past losers, have historically generated consistent profits in the U.S. and most developed markets, with some exceptions in Asia. The paper discusses various behavioral explanations for this phenomenon, such as investors’ delayed reaction to information, and also examines the limits of these strategies, noting that momentum profits may reverse in the long term.
• Does the Stock Market Overreact? by Werner F. M. De Bondt and Richard Thaler (The Journal of Finance, 1985): This pioneering paper examines whether stock prices overreact to new information, causing significant deviations from their long-term trends. De Bondt and Thaler analyze stock performance following substantial price changes and find evidence of a mean-reversion effect. Specifically, stocks that have experienced sharp declines (termed “losers”) tend to outperform those that have seen significant price increases (“winners”) over the subsequent three to five years. This suggests that prior price movements can be a predictor of future performance, but in the opposite direction, highlighting the tendency of markets to overreact to news, which eventually leads to a correction.

Criticizing:

• Dissecting Anomalies by Eugene F. Fama and Kenneth R. French (Journal of Finance): In this influential paper, Fama and French critique various market anomalies, including the momentum effect. They argue that while momentum strategies have historically generated positive returns, these returns may not be as robust or consistent as previously believed. The authors suggest that the success of momentum strategies could be partially due to data mining or specific market conditions rather than a persistent, exploitable anomaly. They also highlight the risks associated with momentum investing, particularly noting its vulnerability during market downturns, where momentum strategies often experience significant losses. The paper challenges the notion that momentum is a reliable strategy, proposing that its observed profitability might not be sustainable across all market environments.

Price Percentile

Supporting:

• Does the Stock Market Overreact? by Werner F. M. De Bondt and Richard Thaler (The Journal of Finance, 1985): This pioneering paper examines whether stock prices overreact to new information, causing significant deviations from their long-term trends. De Bondt and Thaler analyze stock performance following substantial price changes and find evidence of a mean-reversion effect. Specifically, stocks that have experienced sharp declines (termed “losers”) tend to outperform those that have seen significant price increases (“winners”) over the subsequent three to five years. This suggests that prior price movements can be a predictor of future performance, but in the opposite direction, highlighting the tendency of markets to overreact to news, which eventually leads to a correction.

Criticizing:

• The Cross-Section of Expected Stock Returns by Eugene F. Fama and Kenneth R. French (The Journal of Finance, 1992): In this seminal paper, Fama and French challenge the idea that stock market overreactions, as identified by De Bondt and Thaler, are purely the result of behavioral biases. Instead, they propose that these patterns can be explained by other risk factors, particularly size and book-to-market ratios. Fama and French argue that the observed reversal patterns, where previously underperforming stocks outperform and vice versa, are not necessarily indicative of market inefficiency but rather reflect compensation for risk associated with these factors. Their findings suggest that differences in stock returns across the market can be attributed to systematic risk factors, which better account for the performance variations observed by earlier studies.

Price

Supporting:

• Does the Stock Market Overreact? by Werner F. M. De Bondt and Richard Thaler (The Journal of Finance, 1985): This pioneering paper examines whether stock prices overreact to new information, causing significant deviations from their long-term trends. De Bondt and Thaler analyze stock performance following substantial price changes and find evidence of a mean-reversion effect. Specifically, stocks that have experienced sharp declines (termed “losers”) tend to outperform those that have seen significant price increases (“winners”) over the subsequent three to five years. This suggests that prior price movements can be a predictor of future performance, but in the opposite direction, highlighting the tendency of markets to overreact to news, which eventually leads to a correction.

Criticizing:

• The Cross-Section of Expected Stock Returns by Eugene F. Fama and Kenneth R. French (The Journal of Finance, 1992): In this seminal paper, Fama and French challenge the idea that stock market overreactions, as identified by De Bondt and Thaler, are purely the result of behavioral biases. Instead, they propose that these patterns can be explained by other risk factors, particularly size and book-to-market ratios. Fama and French argue that the observed reversal patterns, where previously underperforming stocks outperform and vice versa, are not necessarily indicative of market inefficiency but rather reflect compensation for risk associated with these factors. Their findings suggest that differences in stock returns across the market can be attributed to systematic risk factors, which better account for the performance variations observed by earlier studies.

Volatility

Supporting:

• The Cross-Section of Volatility and Expected Returns: Then and Now by Andrew Detzel, Jefferson Duarte, Avraham Kamara, Stephan Siegel, Celine Sun (2019): This paper examines the relationship between idiosyncratic volatility (IV) and expected stock returns, revisiting earlier findings by Ang, Hodrick, Xing, and Zhang (2006). The authors discover that stocks with high IV generally underperform those with lower IV, a trend observed across various time periods and asset-pricing models. The study also highlights that more modern models, such as the Stambaugh-Yuan four-factor model and the Barillas-Shanken six-factor model, better account for the IV anomaly. This research underscores the significance of considering IV in asset pricing, as traditional models may overlook its impact, leading to mispricing and affecting future returns.

Criticizing:

• Idiosyncratic Volatility and the Cross Section of Expected Returns by Turan G. Bali and Nusret Cakici (2009): This paper explores the relationship between idiosyncratic volatility and expected stock returns across different portfolios. The study finds that the relationship between idiosyncratic volatility and expected returns is highly dependent on several factors, including the data frequency used to estimate volatility, the weighting scheme for average portfolio returns, the breakpoints used to sort stocks, and the screening criteria for size, price, and liquidity. By analyzing portfolios using different measures of idiosyncratic volatility, weighting schemes, and breakpoints, the authors conclude that there is no consistently significant relationship between idiosyncratic volatility and expected returns. This challenges the notion that higher idiosyncratic risk should be associated with higher expected returns, suggesting that this relationship may not be as robust as previously thought.

Volume

Supporting:

• The Relationship Between Trading Volume and Stock Returns by Chandrapala Pathirawasam (2011): This study investigates the relationship between trading volume and stock returns on the Colombo Stock Exchange (CSE) during the period from 2000 to 2008. The research reveals a positive relationship between trading volume changes and stock returns in the contemporary period. However, the study also finds a negative relationship when past trading volume is correlated with future stock returns. This suggests that stocks with low trading volume in the past tend to outperform those with high trading volume in the future. The study attributes this phenomenon to investor misperceptions about future earnings and the illiquidity of low-volume stocks. These findings highlight the predictive power of trading volume changes and challenge the weak-form efficiency of the CSE.

Criticizing:

• None currently available.