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High book-to-market stocks earn higher average returns than low book-to-market stocks. This result has been verified using stock returns from the US, developed, and emerging markets. Why B/M explains expected returns is still an open question. In this paper, we use stock returns representing twenty-five emerging markets to test three different theories. Our results differ from papers studying the US stock market. For emerging markets, the component of book-to-market that is related to tangible information (past accounting performance) is significantly related to expected returns while the component related to intangible information (changes in price unrelated to accounting performance) is not. Our evidence is consistent across emerging market regions. We attempt to differentiate between overreaction and risk explanations for the B/M effect. We find some evidence to support overreaction but find no support for the risk explanation.

This paper provides an extensive international analysis of the cross-sectional return predictive power of a variety of firm-level profitability measures, calculated from different combinations of measures of earnings and scaling variables. We show that this cross-sectional predictive relation is more pronounced when profit is measured by gross profit and when profits are scaled by enterprise value or market value of equity. Our findings support the hypotheses that the predictive power of “profits-to-market price” factor is partly attributable to stock mispricing arising from systematic behavioral biases and partly to the choice of a “clean” measure of earnings.

Using data on 65,000 stocks from 23 countries, the authors reevaluate the performance of the Fama–French (2015) factors in global markets. The results provide convincing evidence that the value, profitability, and investment factors are far less reliable than commonly thought. Their performance depends strongly on the geographical region and period examined. Furthermore, most factor returns are driven by the smallest firms. Virtually no value or investment effects are present among the big firms representing most of the total market capitalization worldwide. Given that the smallest firms are typically not investable by major financial institutions, these findings cast doubt on the five-factor model’s applicability in international markets. TOPICS: Security analysis and valuation, global markets, factor-based models, performance measurement Key Findings ▪ Using data on 65,000 stocks from 23 countries, the authors reevaluate the performance of the Fama–French (2015) factors in global markets. ▪ The value, profitability, and investment factors are far less reliable than commonly thought—their performance depends strongly on the geographical region and period examined. ▪ The smallest firms drive most factor returns; virtually no value or investment effects are present among the big firms representing most of the total market capitalization worldwide.

Stocks with large increases in call (put) implied volatilities over the previous month tend to have high (low) future returns. Sorting stocks ranked into decile portfolios by past call implied volatilities produces spreads in average returns of approximately 1% per month, and the return differences persist up to six months. The cross section of stock returns also predicts option implied volatilities, with stocks with high past returns tending to have call and put option contracts that exhibit increases in implied volatility over the next month, but with decreasing realized volatility. These predictability patterns are consistent with rational models of informed trading.

This paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that i) the data frequency used to estimate idiosyncratic volatility, ii) the weighting scheme used to compute average portfolio returns, iii) the breakpoints utilized to sort stocks into quintile portfolios, and iv) using a screen for size, price, and liquidity play critical roles in determining the existence and significance of a relation between idiosyncratic risk and the cross section of expected returns. Portfoliolevel analyses based on two different measures of idiosyncratic volatility (estimated using daily and monthly data), three weighting schemes (value-weighted, equal-weighted, inverse volatility-weighted), three breakpoints (CRSP, NYSE, equal market share), and two different samples (NYSE/AMEX/NASDAQ and NYSE) indicate that no robustly significant relation exists between idiosyncratic volatility and expected returns.

Goyal and Santa-Clara (2003) find a significantly positive relation between the equal-weighted average stock volatility and the value-weighted portfolio returns on the NYSE/AMEX/Nasdaq stocks for the period of 1963:08 to 1999:12. We show that this result is driven by small stocks traded on the Nasdaq, and is in part due to a liquidity premium. In addition, their result does not hold for the extended sample of 1963:08 to 2001:12 and for the NYSE/AMEX and NYSE stocks. More importantly, we find no evidence of a significant link between the value-weighted portfolio returns and the median and value-weighted average stock volatility.

This paper proposes a generalized measure of riskiness that nests the original measures pioneered by Aumann and Serrano (Aumann, R. J., R. Serrano. 2008. An economic index of riskiness. J. Political Econom. 116 (5) 810-836) and Foster and Hart (Foster, D. P., S. Hart. 2009. An operational measure of riskiness. J. Political Econom. 117 (5) 785-814). The paper introduces the generalized options' implied measure of riskiness based on the risk-neutral return distribution of financial securities. It also provides asset allocation implications and shows that the forward-looking measures of riskiness successfully predict the cross section of 1-, 3-, 6-, and 12-month-ahead risk-adjusted returns of individual stocks. The empirical results indicate that the generalized measure of riskiness is able to rank equity portfolios based on their expected returns per unit of risk and hence yields a more efficient strategy for maximizing expected return of the portfolio while minimizing its risk. This paper was accepted by Wei Xiong, finance.

Employing the portfolio method and cross-sectional regressions, this paper provides a comprehensive analysis of stock return predictability in Turkey from January 1997 to July 2011. In the risk-related predictors, we found predictive power for beta, total volatility, and idiosyncratic volatility. The \"cheapness\" variable, book-to-market ratio, is the most important return predictor for the stocks traded on the Istanbul Stock Exchange (now part of the Borsa Istanbul). Grouping the stocks as small and large according to the median value of the market capitalization of the stocks adds important insights to the analysis. Our results show the set of large stocks on the Istanbul Stock Exchange to be the least predictable set of stocks.

The Securities and Exchange Commission's 2008 emergency order introduced a shorting ban of some 800 financials traded in the US. This paper provides an empirical analysis of the options market around the ban period. Using transaction level data from OPRA (The Options Price Reporting Authority), we study the options volume, spreads, pricing measures and option trade volume informativeness during the ban. We also consider the put-call parity relationship. While mostly statistically significant, economic magnitudes of our results suggest that the impact of the ban on the equity options market was likely not as dramatic as initially thought.

Examining the frontier markets in the regions of Europe, Africa, Middle East, and Asia by using factor-mimicking portfolios based on market capitalization (SMB), book-to-market equity (HML), and momentum (WML), this study reveals significant returns to value and momentum for all size groups. Local asset pricing models that use locally derived factors and global asset pricing models that use globally derived factors are rejected in nearly all cases. Although local SMB, HML, and WML demonstrate some ability to explain average frontier portfolio returns, global SMB, HML, and WML show no such ability. The evidence suggests that frontier and developed markets are segmented. TOPICS: Frontier markets, factor-based models, portfolio theory, portfolio construction Key Findings • Local factors perform better than global factors in explaining average frontier market portfolio returns. • Frontier and developed markets are segmented. • Significant momentum and value cross-sectional return patterns are observed in frontier markets.