Commonality in Misvaluation, Equity Financing, and the Cross Section of Stock Returns

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. This paper uses equity financing to identify comovement in returns and commonality in misvaluation. A zero-investment portfolio (UMO, Undervalued Minus Overvalued) built from repurchase and new issue stocks captures excess comovement in general stock returns relative to a set of multi-factor models. Adding UMO to the 3-factors makes the alphas insignificant for portfolios with extreme size and book-to-market, or based on M&A, convertible bond issuance, and dividend initiation, resumption, and omission. The loadings on UMO incrementally predict the cross-section of returns on portfolios as well as individual stocks. Further evidence is consistent with the UMO loading proxying for the common component of a stock's misvaluation.Comovement, equity financing, new issue, repurchase, systematic mispricing, return predictability

A Financing-Based Misvaluation Factor and the Cross Section of Expected Returns

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. We use equity and debt financing to identify common misvaluation across firms. A zero-investment portfolio (UMO, Undervalued Minus Overvalued) built from repurchase and new issue firms captures comovement in returns beyond that in some standard multifactor models, and substantially improves the Sharpe ratio of the tangency portfolio. Loadings on UMO incrementally predict the cross-section of returns on both portfolios and individual stocks, even among firms not recently involved in external financing activities. Further evidence suggests that UMO loadings proxy for the common component of a stock's misvaluation.Misvaluation, financing, new issues, repurchase, factor models, market efficiency, behavioral finance

Gambling Preference and the New Year Effect of Assets with Lottery Features

This paper examines whether investors exhibit a New Year's gambling preference and whether such preference impacts prices and returns of assets with lottery features. In January, calls options have higher demand than put options, especially by small investors. In addition, relative to at-the-money calls, out-of-the-money calls are the most expensive and actively traded. In the equity markets, lottery-type stocks in the US outperform their counterparts mainly in January, but tend to underperform in other months. Lottery-type Chinese stocks outperform in the Chinese New Year month, but not in January. This New Year effect provides new insights into the broad phenomena related to the January effect.January effect, Gambling, Preference for skewness, Out-of-the-money options, China

Cross-Sectional Dispersion of Firm Valuations and Expected Stock Returns

This paper develops two competing hypotheses for the relation between the cross-sectional standard deviation of logarithmic firm fundamental-to-price ratios (``dispersion'') and expected aggregate returns. In models with fully rational beliefs, greater dispersion indicates greater risk and higher expected aggregate returns. In models with investor overconfidence, greater dispersion indicates greater mispricing and lower expected aggregate returns. Consistent with the behavioral models, the results show that (1) measures of dispersion are negatively related to subsequent market excess returns, (2) this negative relation is more pronounced among riskier firms, and (3) dispersion is positively related to aggregate trading volume, idiosyncratic volatility, and investor sentiment, and increases after good past market performance.Return predictability, Dispersion, Overconfidence, Idiosyncratic volatility, Investor sentiment

Reference Point Adaptation: Tests in the Domain of Security Trading

According to prospect theory (Kahneman & Tversky, 1979), gains and losses are measured from current wealth, which serves as a reference point. We attempted to ascertain to what extent the reference point shifts following gains or losses. In questionnaire studies we asked subjects what stock price today will generate the same utility as a previous change in a stock price. From participants’ responses we calculated the magnitude of reference point adaptation, which was significantly greater following a gain than following a loss of equivalent size. We also found the asymmetric adaptation of gains and losses persisted when a stock was included within a portfolio rather than being considered individually. In studies using financial incentives within the Becker, DeGroot, and Marschak (1964) procedure, we again noted faster adaptation of the reference point to gains than losses. We related our findings to several aspects of asset pricing and investor behavior.Prospect theory; reference point; asset pricing; security trading

Cross-Sectional Dispersion of Firm Valuations and Expected Stock Returns

This paper develops two competing hypotheses for the relation between the cross-sectional standard deviation of logarithmic firm fundamental-to-price ratios (``dispersion'') and expected aggregate returns. In models with fully rational beliefs, greater dispersion indicates greater risk and higher expected aggregate returns. In models with investor overconfidence, greater dispersion indicates greater mispricing and lower expected aggregate returns. Consistent with the behavioral models, the results show that (1) measures of dispersion are negatively related to subsequent market excess returns, (2) this negative relation is more pronounced among riskier firms, and (3) dispersion is positively related to aggregate trading volume, idiosyncratic volatility, and investor sentiment, and increases after good past market performance

Cross-Sectional Dispersion of Firm Valuations and Expected Stock Returns

This paper develops two competing hypotheses for the relation between the cross-sectional standard deviation of logarithmic firm fundamental-to-price ratios (``dispersion'') and expected aggregate returns. In models with fully rational beliefs, greater dispersion indicates greater risk and higher expected aggregate returns. In models with investor overconfidence, greater dispersion indicates greater mispricing and lower expected aggregate returns. Consistent with the behavioral models, the results show that (1) measures of dispersion are negatively related to subsequent market excess returns, (2) this negative relation is more pronounced among riskier firms, and (3) dispersion is positively related to aggregate trading volume, idiosyncratic volatility, and investor sentiment, and increases after good past market performance

A Financing-Based Misvaluation Factor and the Cross Section of Expected Returns

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. We use equity and debt financing to identify common misvaluation across firms. A zero-investment portfolio (UMO, Undervalued Minus Overvalued) built from repurchase and new issue firms captures comovement in returns beyond that in some standard multifactor models, and substantially improves the Sharpe ratio of the tangency portfolio. Loadings on UMO incrementally predict the cross-section of returns on both portfolios and individual stocks, even among firms not recently involved in external financing activities. Further evidence suggests that UMO loadings proxy for the common component of a stock's misvaluation

Commonality in Misvaluation, Equity Financing, and the Cross Section of Stock Returns

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. This paper uses equity financing to identify comovement in returns and commonality in misvaluation. A zero-investment portfolio (UMO, Undervalued Minus Overvalued) built from repurchase and new issue stocks captures excess comovement in general stock returns relative to a set of multi-factor models. Adding UMO to the 3-factors makes the alphas insignificant for portfolios with extreme size and book-to-market, or based on M&A, convertible bond issuance, and dividend initiation, resumption, and omission. The loadings on UMO incrementally predict the cross-section of returns on portfolios as well as individual stocks. Further evidence is consistent with the UMO loading proxying for the common component of a stock's misvaluation

A Financing-Based Misvaluation Factor and the Cross Section of Expected Returns

Behavioral theories suggest that investor misperceptions and market mispricing will be correlated across firms. We use equity and debt financing to identify common misvaluation across firms. A zero-investment portfolio (UMO, Undervalued Minus Overvalued) built from repurchase and new issue firms captures comovement in returns beyond that in some standard multifactor models, and substantially improves the Sharpe ratio of the tangency portfolio. Loadings on UMO incrementally predict the cross-section of returns on both portfolios and individual stocks, even among firms not recently involved in external financing activities. Further evidence suggests that UMO loadings proxy for the common component of a stock's misvaluation