Short- and Long-Horizon Behavioral Anomalies and Institutional Investors’ Nudge Behavior: Based on the Data of Listed Chinese Tobacco Companies

We use the data of listed tobacco companies in China to study the existence of short- and long-horizon behavioral anomalies and the impact of institutional investors’ behavior on them. We found that the existing asset pricing models cannot explain the short- and long-horizon behavioral anomalies based on tobacco enterprise data. Conversely, the short- and long-horizon behavioral anomalies can explain the exciting asset pricing factors. Compared with existing asset pricing models, behavioral anomalies have a stronger ability to explain anomalies. Behavioral anomalies could pass the cross-sectionally test and strengthened over time. The above results indicate that behavioral anomalies exist in China tobacco enterprisest significantly and are time-varying. We found that the limits to arbitrage and cognitive bias lead to the existence of behavioral anomalies through mechanism tests. Institutional investors did not play the role of price discovery. Instead, their nudge behavior strengthens the short- and long-horizon behavioral anomalies. Therefore, tobacco regulatory agencies should guide listed tobacco companies to broaden information channels to reduce information asymmetry in the market through relevant policies, strengthen the supervision of institutional investors’ bubble riding behavior, and promote the healthy development of the tobacco market.

The Distress Anomaly is Deeper than you Think: Evidence from Stocks and Bonds

The distress anomaly reflects the abnormally low returns of high credit risk stocks during financial distress. Evidence from stocks and corporate bonds reinforces the anomaly and challenges rationales based on shareholders’ ability to extract value from bondholders, time-varying betas, lottery-type preferences, biased earnings expectations, and limits-to-arbitrage. Moreover, mispricing of distressed stocks and bonds is associated with excess investment and excess external financing. Potential real distortions are materially understated when assessed based only on equity mispricing. We emphasize the important role of corporate bonds in dissecting the distress anomaly, and show that the anomaly is an unresolved puzzle.

Limits of arbitrage and mispricing: evidence from mergers and acquisitions

PurposeThis paper examines the extent to which noise demand and limits of arbitrage affect the pricing of acquirer stocks both at the announcement period and over the longer horizon.Design/methodology/approachAn event study approach was adopted to measure announcement-period cumulative abnormal returns. Long-horizon returns are measured using buy-and-hold abnormal returns (BHARs), calendar time portfolios (CTPRs), and subsequent earnings announcement period abnormal returns. Main methodologies include ordinary least squared (OLS) regressions, Logit regressions, and portfolio analysis.Findings(1) Acquirer stocks with high idiosyncratic volatility (the proxy for the security level characteristic most directly associated with limits to arbitrage) earn higher announcement-period abnormal returns. (2) The return pattern reverses over the subsequent longer horizon, resembling news-driven transitory mispricing. (3) The mispricing is greater when deal and firm characteristics exacerbate the limits of arbitrage, and it weakens over time. (4) Transactions by higher idiosyncratic volatility acquirers are more likely to fail.Originality/valueLimits of arbitrage theory have been tested mostly in information-free circumstances. The findings in this paper extend the supporting evidence for limits of arbitrage explaining mispricing beyond the boundaries of information-free circumstances.

Can Limits to Arbitrage Explain Stock Price Idiosyncratic Volatility Premium Puzzle in China’s A-Share Market?

Investigating the existence and causes of idiosyncratic volatility premium puzzle in developing stock market can enrich the research on this asset pricing puzzle. To investigate the existence and whether limits to arbitrage in China’s A-share market can explain the idiosyncratic volatility premium puzzle, this paper uses listed stocks in China’s A-share market from 2002 to 2019 as a sample. We calculate three individual measures and one comprehensive measure of limits to arbitrage based on Chinese specific regulations. After that, we conduct univariate portfolios analysis, regression analysis, and bivariate portfolios analysis to obtain evidence. We prove that idiosyncratic volatility premium puzzle exists in China’s A-share market and is robust and that limits to arbitrage in this market can partly explain this asset pricing puzzle. This paper enriches research on asset pricing anomaly and can help us evaluate the effect of China’s A-share market reform.

LIMIT-TO-ARBITRAGE FACTORS AND IVOL RETURNS PUZZLE: EMPIRICAL EVIDENCE FROM TAIWAN BEFORE AND DURING COVID-19

This paper examines the impacts of limit-to-arbitrage factors on the returns of the idiosyncratic volatility (IVOL) puzzle in Taiwan before and during the Covid-19 pandemic. Although various studies explore the relationship between stock returns and IVOL, the empirical findings are mixed. We are motivated by unique market microstructures in Taiwan, such as individual investors’ aggressive trading volume and low transaction costs in Taiwan, discouraging arbitrary trading activities. Our empirical results indicate a negative relationship between IVOL and stock returns by using data from the Taiwan stock market. However, the IVOL anomaly does not exist during the Covid-19 pandemic, even in the small stocks sample. Besides, our findings suggest that four proxies of limits-to-arbitrage, such as reversal, transaction costs, turnover and Amihud’s Illiquidity, have statistically significant impacts on the return of IVOL anomaly in Taiwan except for the pandemic period. Finally, our finding suggests that the stock turnover is the only limit-to-arbitrage factor that helps investors earn arbitrary profits during the COVID-19 period.

Are individual stock returns predictable?

We show that the previously documented predictability of macroeconomic and technical variables for market returns is also evident in individual stock returns. Technical variables generate better predictability on firms with high limits to arbitrage (small, illiquid, volatile firms), while macroeconomic variables better predict firms with low limits to arbitrage. Technical predictors show a stronger predictive power for high limits to arbitrage firms across the business cycle, whereas macroeconomic variables capture more predictive information for firms with low limits to arbitrage during recessions. JEL Classification: C58, E32, G11, G12, G17

Why Do Firms Fail to Engage Diversity? A Behavioral Strategy Perspective

The persistent failure of organizations to engage diversity—to employ a diverse workforce and fully realize its potential—is puzzling, as it creates labor-market inefficiencies and untapped opportunities. Addressing this puzzle from a behavioral strategy as arbitrage perspective, this paper argues that attractive opportunities tend to be protected by strong behavioral and social limits to arbitrage. I outline four limits—cognizing, searching, reconfiguring, and legitimizing (CSRL)—that deter firms from sensing, seizing, integrating, and justifying valuable diversity. The case of Moneyball is used to illustrate how these CSRL limits prevented mispriced human resources from being arbitraged away sooner, with implications for engaging cognitive diversity that go beyond sports. This perspective describes why behavioral failures as arbitrage opportunities can persist and prescribes strategists, as contrarian theorists, a framework for formulating relevant behavioral and social problems to solve in order to search for and exploit these untapped opportunities.

Behavioral Finance Research in 2020: Cui Bono et Quo Vadis?

Emanating from the influential survey of Barberis and Thaler (2003), this systematic literature review examines the significant volume of studies on behavioral finance from 36 reputable finance journals published be-tween 2009 and 2019. The findings are clustered into eight prominent research streams, which indicate the current developments in behavioral finance. Findings show that research intensively focuses on behavioral biases and their influence on economic phenomena. Driven by the impetus to understand the human mind, significant findings originated in the relatively new field of Neurofinance. Additionally, the analysis addresses the influence of market sentiment and its correlation with some of the other findings. Furthermore, implications on the limits to arbitrage in connection with some financial anomalies complete the holistic picture.