Time-Series Variation in Dividend Pricing

Ex-dividend day returns vary over time. The ex-day returns of high-yield stocks are persistently positive for some time periods and negative for others; in contrast, ex-day returns of low-yield stocks are always positive and less variable. We are unable to explain the variation with changes in the tax code, but we do find a strong effect for the introduction of negotiated commissions. We find evidence that corporate dividend capturing is affecting ex-day returns and confirm the findings of Gordon and Bradford (1980) that the price of dividends is countercyclical.     

The Conditional CAPM and the Cross-Section of Expected Returns

Most empirical studies of the static CAPM assume that betas remain constant over time and that the return on the value-weighted portfolio of all stocks is a proxy for the return on aggregate wealth. The general consensus is that the static CAPM is unable to explain satisfactorily the cross-section of average returns on stocks. We assume that the CAPM holds in a conditional sense, i.e., betas and the market risk premium vary over time. We include the return on human capital when measuring the return on aggregate wealth. Our specification performs well in explaining the cross-section of average returns.     

Institutional Trade Persistence and Long‐Term Equity Returns

Recent studies show that single‐quarter institutional herding positively predicts short‐term returns. Motivated by the theoretical herding literature, which emphasizes endogenous persistence in decisions over time, we estimate the effect of multiquarter institutional buying and selling on stock returns. Using both regression and portfolio tests, we find that persistent institutional trading negatively predicts long‐term returns: persistently sold stocks outperform persistently bought stocks at long horizons. The negative association between returns and institutional trade persistence is not subsumed by past returns or other stock characteristics, is concentrated among smaller stocks, and is stronger for stocks with higher institutional ownership.     

Optimal Number of Stock Holdings in Mutual Fund Portfolios Based on Market Performance

Among the decisions that most mutual fund portfolio managers make is the number of stocks to hold. We posit that there is an optimal number of stocks for each mutual fund, reflecting the trade‐off between diversification benefits versus transactions and monitoring costs. We find a significant quadratic relation between number of stock holdings and risk‐adjusted returns for U.S. equity mutual fund portfolios during 1992–2000. Moreover, we find that changes in the number of stocks held over time are more highly correlated with mutual fund flows than with funds' investment returns.     

New ESG rating drivers in the cross-section of European stock returns

We assess the performance of two quantitative signals based on ESG scores across a large, multi-national cross-section of European stock returns. We test whether the cost of equity capital is more influenced by the upward momentum (measured over time) of the ESG scores of the firms issuing stocks or by their stability (identified as the volatility of the scores over time), measured around a changing mean level. We find that short-term ESG momentum over 1 month has a significant impact on the cross-section of stock returns, lowering the anticipated cost of capital and leading to positive average abnormal returns. This suggests that short-term ESG momentum may represent a novel, priced systematic risk factor. Furthermore, we find strong evidence that an ESG volatility spread strategy which buys low ESG score volatility stocks and sells high volatility ones, generates a substantial alpha and affects the ex-ante cost of capital. Both quantitative ESG signals result in portfolio sorting and long-short strategies that enhance the overall sustainability profile of the issuing firms without compromising the raw average of their ESG scores.     

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.     

A network perspective of the stock market

Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 to May 2009). The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices, price returns and trading volumes within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. So far, no previous work has attempted to construct a full network of US stock prices that gives full information about their interdependence. We report that all networks based on connecting stocks of highly correlated stock prices, price returns and trading volumes, display a scalefree degree distribution. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in a stock index and compare it with existing indexes. From the composition of the highly connected stocks, it can be concluded that the market is heavily dominated by stocks in the financial sector.     

Institutional trading and stock returns

In this study, we explore the dynamics of the relation between institutional trading and stock returns. We find that stock returns Granger-cause institutional trading (especially purchases) on a quarterly basis. The robust and significant causality from equity returns to institutional trading can be largely explained by the time-series variation of market returns, that is, institutions buy more popular stocks after market rises. Stock returns appear to be negatively related to lagged institutional trading. A further analysis of the behavior of trading and the returns of the traded stocks reveals evidence that stocks with heavy institutional buying (selling) experience positive (negative) excess returns over the previous 12 months.     

Volatility and market structure

This study examines volatility within three related intra-day series – transaction returns, quote midpoint returns, and limit order book midpoint returns – for a set of NYSE-listed stocks. We document statistically significant GARCH effects both overall and surrounding earnings announcements in all three series for the majority of stocks in the sample. We then compare the extent of volatility clustering among the series. In addition, the relation between volatility and market structure is examined via a set of cross-sectional regressions, and relations among the series over time are studied in a vector autoregressive framework.     

STOCK PRICES AND INFLATION

Numerous empirical studies establish that inflation has a negative short‐run effect on stock returns but few studies report a positive, long‐run Fisher effect for stock returns. Using stock price and goods price data from six industrial countries, we show that long‐run Fisher elasticities of stock prices with respect to goods prices exceed unity and range from 1.04 to 1.65, which tends to support the Fisher effect. We also find that the time path of the response of stock prices to a shock in goods prices exhibits an initial negative response, which turns positive over longer horizons. These results help reconcile previous short‐run and long‐run empirical evidence on stock returns and inflation. Also, they reveal that stock prices have a long memory with respect to inflation shocks, such that investors should expect stocks to be a good inflation hedge over a long holding period. JEL Classification: G12     

The Role of Beta and Size in the Cross-Section of European Stock Returns

This paper examines the ability of beta and size to explain cross-sectional variation in average returns in 12 European countries. We find that average stock returns are positively related to beta and negatively related to firm size. The beta premium is in part due to the fact that high beta countries outperform low beta countries. Within countries high beta stocks outperform low beta stocks only in January, not in other months. We reject the hypothesis that differences in average returns on size- and beta-sorted portfolios can be explained by market risk and exposure to the excess return of small over large stocks (SMB). Consistent with recent US evidence, we find that after controlling for size, there is no association between average returns and exposure to SMB.     

Returns and option activity over the option-expiration week for S&P 100 stocks

For S&P 100 stocks, we find that the weekly returns over option-expiration (OE) weeks (a month’s third-Friday week) tend to be high, relative to: (1) the third-Friday weekly returns of other stocks with less option activity, (2) the own stock’s other weekly returns, (3) the risk, based on asset-pricing alphas. For these same stocks, a month’s fourth-Friday weekly returns underperform modestly. We suggest the following two avenues are likely partial contributors towards understanding these return patterns: (1) delta-hedge rebalancing by option market makers, with a reduction in short-stock hedge positions over the OE week, and (2) declining risk perceptions over the OE week, as measured by option-derived implied volatilities. Our findings suggest option activity can induce reliable patterns in the weekly returns of option-active large-cap stocks.     

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.     

Stock Returns in Thinly Traded Markets

We examine the share price behavior of thinly traded NASDAQ National Market System stocks during periods when financial markets are open but the individual stocks do not trade. The absence of trade allows us to isolate the effect of nontrading from that of market closure. We find that nontrading stocks have negative mean returns and lower variances regardless of whether markets are open or closed. Two-day returns that include one nontrading day have a mean daily return of -0.226% compared to +0.164% for two-day returns over consecutive trading days. Two-day returns that include one nontrading day have only 3.8% higher variance than one-day returns. We conclude that the relation between transaction arrival, mean returns, and volatility depends on whether a stock is trading and not simply on whether the market is open.     

The return impact of realized and expected idiosyncratic volatility

We show that the negative relation between realized idiosyncratic volatility, measured over the prior month, and returns is robust in non-January months. Controlling for realized idiosyncratic volatility, we show that the relation between returns and expected idiosyncratic volatility is positive and robust. Realized and expected idiosyncratic volatility are separate and important effects describing the cross-section of returns. We find the negative return on a zero-investment portfolio that is long high realized idiosyncratic volatility stocks and short low realized idiosyncratic volatility stocks is dependent on aggregate investor sentiment. In cross-sectional tests, we find the negative relation is weaker for stocks with a large analyst following and stronger for stocks with high dispersion of analyst forecasts. The positive relation between expected idiosyncratic volatility and returns is not due to mispricing.     

Style drift: Evidence from small-cap mutual funds

This paper documents that small-cap mutual funds allocate on average 27% of their portfolio to mid- and large-cap stocks. We find that larger and older small-cap funds are more likely to hold mid- and large-cap stocks, consistent with funds straying from their objective over time. Funds that invest heavily in mid- and large-cap stocks expose their investors to unanticipated risks but investors do not experience higher abnormal returns or performance persistence overall. These funds did outperform their peers by 3% annually in the most recent period between January 2003 and March 2010.     

Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns

We document that purchasing (selling short) stocks with the most (least) favorable consensus recommendations, in conjunction with daily portfolio rebalancing and a timely response to recommendation changes, yield annual abnormal gross returns greater than four percent. Less frequent portfolio rebalancing or a delay in reacting to recommendation changes diminishes these returns; however, they remain significant for the least favorably rated stocks. We also show that high trading levels are required to capture the excess returns generated by the strategies analyzed, entailing substantial transactions costs and leading to abnormal net returns for these strategies that are not reliably greater than zero.     

Delayed Reaction to Good News and the Cross-Autocorrelation of Portfolio Returns

We document a directional asymmetry in the small stock concurrent and lagged response to large stock movements. When returns on large stocks are negative, the concurrent beta for small stocks is high, but the lagged beta is insignificant. When returns on large stocks are positive, small stocks have small concurrent betas and very significant lagged betas. That is, the cross-autocorrelation puzzle documented by Lo and MacKinlay (1990a) is associated with a slow response by some small stocks to good, but not to bad, common news. Time series portfolio tests and cross-sectional tests of the delay for individual securities suggest that existing explanations of the cross-autocorrelation puzzle based on data mismeasurement, minor market imperfections, or time-varying risk premiums fail to capture the directional asymmetry in the data.     

The predictability of real estate returns and market timing

Recent evidence suggests that all asset returns are predictable to some extent with excess returns on real estate relatively easier to forecast. This raises the issue of whether we can successfully exploit this level of predictability using various market timing strategies to realize superior performance over a buy-and-hold strategy. We find that the level of predicability associated with real estate leads to moderate success in market timing, although this is not necessarily the case for the other asset classes examined in general. Besides this, real estate stocks typically have higher trading profits and higher mean risk-adjusted excess returns when compared to small stocks as well as large stocks and bonds even though most real estate stocks are small stocks.     

Option Momentum

This paper investigates the performance of option investments across different stocks by computing monthly returns on at-the-money straddles on individual equities. We find that options with high historical returns continue to significantly outperform options with low historical returns over horizons ranging from 6 to 36 months. This phenomenon is robust to including out-of-the-money options or delta-hedging the returns. Unlike stock momentum, option return continuation is not followed by long-run reversal. Significant returns remain after factor risk adjustment and after controlling for implied volatility and other characteristics. Across stocks, trading costs are unrelated to the magnitude of momentum profits.