Residual momentum

Conventional momentum strategies exhibit substantial time-varying exposures to the Fama and French factors. We show that these exposures can be reduced by ranking stocks on residual stock returns instead of total returns. As a consequence, residual momentum earns risk-adjusted profits that are about twice as large as those associated with total return momentum; is more consistent over time; and less concentrated in the extremes of the cross-section of stocks. Our results are inconsistent with the notion that the momentum phenomenon can be attributed to a priced risk factor or market microstructure effects.     

Using industry momentum to improve portfolio performance

Minimum-variance portfolios, which ignore the mean and focus on the (co)variances of asset returns, outperform mean–variance approaches in out-of-sample tests. Despite these promising results, minimum-variance policies fail to deliver a superior performance compared with the simple 1/N rule. In this paper, we propose a parametric portfolio policy that uses industry return momentum to improve portfolio performance. Our portfolio policies outperform a broad selection of established portfolio strategies in terms of Sharpe ratio and certainty equivalent returns. The proposed policies are particularly suitable for investors because portfolio turnover is only moderately increased compared to standard minimum-variance portfolios.     

Sales order backlogs and momentum profits

Winner stocks have higher changes in sales order backlogs and a sales order backlog factor is significant in explaining various winner minus loser returns and often reduces the αs by big margins. We argue that this factor is a proxy for innovation in demand in the economy and it is likely to relate to expected growth risks and future business conditions.     

Risk aversion and skewness preference

Empirically, co-skewness of asset returns seems to explain a substantial part of the cross-sectional variation of mean return not explained by beta. This finding is typically interpreted in terms of a risk averse representative investor with a cubic utility function. This paper questions this interpretation. We show that the empirical tests fail to impose risk aversion and the implied utility function takes an inverse S-shape. Unfortunately, the first-order conditions are not sufficient to guarantee that the market portfolio is the global maximum for this utility function, and our results suggest that the market portfolio is more likely to represent the global minimum. In addition, if we do impose risk aversion, then co-skewness has minimal explanatory power.     

Profitability of momentum strategies in international markets: The role of business cycle variables and behavioural biases

The paper investigates whether business cycle variables and behavioural biases can explain the profitability of momentum trading in three major European markets. Unlike previous studies, the paper nests both risk-based and behavioural-based variables in a two-stage model specification in an attempt to explain momentum profits. The findings show that, although momentum profitability in European markets is unexplained by conditional asset pricing models, it is attributable to asset mispricing that systematically varies with global business conditions. In addition, behavioural variables do not appear to matter much. Thus risk factors, which are undetected thus far and are largely attributable to the business cycle, could explain the momentum payoffs in European stock markets.     

Risk factor and industry effects in the cross-country comovement of momentum returns

This paper examines the sources of cross-country comovement of momentum returns over the 1975–2004 period. Using data on more than 17,000 individual firms across 100 industries from 40 countries, we document the profitability of country-neutral individual firm, industry, and industry-adjusted return momentum. We show that country-neutral momentum returns are significantly correlated across countries, the correlation is time-varying, and that comovement among industries cannot explain the comovement of country-neutral momentum returns. However, we find that standard risk factor models do explain a significant portion of the cross-country comovement of momentum returns, even though they do not explain average momentum returns.     

A careful re-examination of seasonality in international stock markets: Comment on sentiment and stock returns

In questioning Kamstra, Kramer, and Levi’s (2003) finding of an economically and statistically significant seasonal affective disorder (SAD) effect, Kelly and Meschke (2010) make errors of commission and omission. They misrepresent their empirical results, claiming that the SAD effect arises due to a “mechanically induced” effect that is non-existent, labeling the SAD effect a “turn-of-year” effect (when in fact their models and ours separately control for turn-of-year effects), and ignoring coefficient-estimate patterns that strongly support the SAD effect. Our analysis of their data shows, even using their low-power statistical tests, there is significant international evidence supporting the SAD effect. Employing modern, panel/time-series statistical methods strengthens the case dramatically. Additionally, Kelly and Meschke represent the finance, psychology, and medical literatures in misleading ways, describing some findings as opposite to those reported by the researchers themselves, and choosing selective quotes that could easily lead readers to a distorted understanding of these findings.     

EXPECTED VOLATILITY,UNEXPECTED VOLATILITY,AND THE CROSS‐SECTION OF STOCK RETURNS

The existing literature finds conflicting results on the cross‐sectional relation between expected returns and idiosyncratic volatility. We contend that at the firm level, the sample correlation between unexpected returns and expected idiosyncratic volatility can cloud the true relation between the expected return and expected idiosyncratic volatility. We show strong evidence that unexpected idiosyncratic volatility is positively related to unexpected returns. Using unexpected idiosyncratic volatility to control for unexpected returns, we find expected idiosyncratic volatility to be significantly and positively related to expected returns. This result holds after controlling for various firm characteristics, and it is robust across different sample periods.     

Testing conditional factor models: A nonparametric approach

Some recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama-French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.     

Should investors include commodities in their portfolios after all? New evidence

This paper investigates whether an investor is made better off by including commodities in a portfolio that consists of traditional asset classes. First, we revisit the posed question within an in-sample setting by employing mean-variance and non-mean-variance spanning tests. Then, we form optimal portfolios by taking into account the higher order moments of the portfolio returns distribution and evaluate their out-of-sample performance. Under the in-sample setting, we find that commodities are beneficial only to non-mean-variance investors. However, these benefits are not preserved out-of-sample. Our findings challenge the alleged diversification benefits of commodities and are robust across a number of performance evaluation measures, utility functions and datasets. The results hold even when transaction costs are considered and across various sub-periods. Not surprisingly, the only exception appears over the 2005-2008 unprecedented commodity boom period.     

Is it the weather? Comment

This comment discusses some errors in a recent paper by Jacobsen and Marquering [Jacobsen, B., Marquering, W., 2008. Is it the weather? Journal of Banking and Finance 32 (4), 526–540], in which the authors challenge our previous finding that stock market returns exhibit seasonal patterns consistent with the influence of seasonal affective disorder on investor risk aversion. We find that we cannot replicate the authors’ findings, even after corresponding with them. Furthermore, we document several problems with their methodology, including misspecification of their economic model, misspecification of their econometric model, and use of inappropriate data. While we agree that seasonal affective disorder is not an explanation for all variation in equity markets, we do maintain that careful analysis leads to economically and statistically significant evidence of the effect we originally documented.     

TRADE SIZE AND INFORMED TRADING: WHICH TRADES ARE “BIG”?

We find adverse‐selection spread components increase sharply in the ratio of trade size to quoted depth, and spike when trade size equals quoted depth. We find that two previously documented and prominent indicators of informed trading, raw trade size and high‐trading volume half‐hours, offer almost no explanatory power for informed trading measures beyond trade size to quoted depth, and a third indicator, time of day, offers no explanatory power among trades with high trade size to quoted depth. Our results suggest trade size to quoted depth is perhaps the single most important indicator that a trade is informed.     

Information percolation,momentum and reversal

We propose a joint theory of time-series momentum and reversal based on a rational-expectations model. We show that a necessary condition for momentum to arise in this framework is that information flows at an increasing rate. We focus on word-of-mouth communication as a mechanism that enforces this condition and generates short-term momentum and long-term reversal. Investors with heterogeneous trading strategies—contrarian and momentum traders—coexist in the marketplace. Although a significant proportion of investors are momentum traders, momentum is not completely eliminated. Word-of-mouth communication spreads rumors and generates price run-ups and reversals. Our theoretical predictions are in line with empirical findings.     

Dispersion in beliefs among active mutual funds and the cross-section of stock returns

We propose a measure of dispersion in fund managers? beliefs about future stock returns based on their active holdings, i.e., deviations from benchmarks. We find that both the level of and the change in dispersion positively predict subsequent stock returns on a risk-adjusted basis. This effect is particularly pronounced among stocks with high information asymmetry and binding short-sale constraints. These results suggest that a subgroup of informed managers drives up the dispersion in active holdings when they place large bets after receiving positive private information. Binding short-sale constraints, however, prevent them from fully using their negative private information, leading to low dispersion in active holdings.     

Dividends and price momentum

Stock market evidence shows that momentum profits are lower among dividend-paying firms than their non-paying counterparts due to differences in losers’ returns. Additionally, dividend maintenance is associated with higher returns for losers but not for winners. Finally, buying winners that increased their dividends and shorting losers that decreased their dividends enhances momentum profits. Consistent with the evidence, the behavioral models suggest that investors underreact to the losers’ positive dividend-maintaining news, reducing their return momentum and shrinking the payers’ momentum profit. Also, underreaction to positive news from winners’ dividend-increasing announcements as well as to negative news from losers’ dividend-decreasing announcements explains the higher momentum profits for strategies based on these stocks. The results do not appear consistent with risk-based explanations.     

THE DAYLIGHT SAVING TIME ANOMALY IN STOCK RETURNS: FACT OR FICTION?

Stock market returns in 22 markets around the world show no evidence of a daylight saving time effect. Returns on the days following a switch from or to daylight saving time do not behave any differently from stock market returns on any other day of the week or month. These results reject earlier conclusions in the literature—based on less data—that investors’ mood changes induced by changes in sleep patterns significantly affect stock returns.     

The Other January Effect: Evidence against market efficiency?

The Other January Effect (OJE), which suggests positive (negative) equity market returns in January predict positive (negative) returns in the following 11 months of the year, underperforms a simple buy-and-hold strategy before and after risk-adjustment. Even the best modified OJE strategy, which benefits from several ex-post adjustments, does not generate statistically or economically significant excess returns. When the OJE is tested with a method that is consistent with investor experience it is clear the OJE is no more profitable than an 11-month strategy that uses November or December as the conditioning month.     

Firm-specific attributes and the cross-section of momentum

This paper identifies observable firm-specific attributes that drive momentum. We find that a firm's revenues, costs, and growth options combine to determine the dynamics of its return autocorrelation. We use these insights to implement momentum strategies (buying winners and selling losers) with both numerically simulated returns and CRSP/Compustat data. In both sets of data, momentum strategies that use firms with high revenue growth volatility, low costs, or valuable growth options outperform traditional momentum strategies by approximately 5% per year.     

Currency momentum strategies

We provide a broad empirical investigation of momentum strategies in the foreign exchange market. We find a significant cross-sectional spread in excess returns of up to 10% per annum (p.a.) between past winner and loser currencies. This spread in excess returns is not explained by traditional risk factors, it is partially explained by transaction costs and shows behavior consistent with investor under- and overreaction. Moreover, cross-sectional currency momentum has very different properties from the widely studied carry trade and is not highly correlated with returns of benchmark technical trading rules. However, there seem to be very effective limits to arbitrage that prevent momentum returns from being easily exploitable in currency markets.     

Informed trading,information uncertainty,and price momentum

In this paper we investigate the effects of informed trading (PIN) and information uncertainty in determining price momentum. We find that trading strategies based on buying high-uncertainty good-news stocks and shorting high-uncertainty bad-news stocks work well when limited to high-PIN stocks, while stocks with low-PIN do not exhibit price continuations, even when the uncertainty level of those stocks is high. In contrast, momentum returns are always significant for high-PIN stocks, irrespective of information uncertainty. Overall, we show that the informed trading effect is both independent of and stronger than that of information uncertainty in determining price momentum.