Autoregressive Modeling of Earnings-Investment Causality

The purpose of this paper is to empirically test the relationships between corporate earnings and investment. In particular, the study investigates whether knowledge of past investments improves the prediction of future earnings beyond predictions that are based on past earnings alone. Similarly, it investigates whether knowledge of past earnings improves the prediction of future investments beyond knowledge of past investments alone. This is the empirical definition of Granger causality. The empirical results show that the bivariate past series of earnings and investments is superior to the univariate series in predicting future investments but not in predicting future earnings.     

Dividend Changes and the Persistence of Past Earnings Changes

We examine whether the market interprets changes in dividends as a signal about the persistence of past earnings changes. Prior to observing this signal, investors may believe that past earnings changes are not necessarily indicative of future earnings levels. We empirically investigate whether a change in dividends alters investors' assessments about the valuation implications of past earnings. Results confirm the hypothesis that changes in dividends cause investors to revise their expectations about the persistence of past earnings changes. This effect varies predictably with the magnitude of the dividend change and the sign of the past earnings change.     

Momentum is really short-term momentum

We demonstrate the estimation biases that arise when stock returns from 12 month prior and 2 month prior are included within intermediate and recent past momentum profits. These biases lead to an overestimation of intermediate past momentum but an underestimation of recent past momentum in the US market. There is no significant difference between the predictability of stock performance in the intermediate past and the recent past once we exclude these two months from the construction of momentum strategies in the US and each of the 26 major international markets.     

Asymmetric Price and Volatility Adjustments in Emerging Asian Stock Markets

This paper tests the hypothesis that stock returns in emerging stock markets adjust asymmetrically to past information. The evidence suggests that both the conditional mean and the conditional variance respond asymmetrically to past information. In agreement with studies dealing with developed stock markets, the conditional variance is an asymmetrical function of past innovations, rising proportionately more during market declines. More importantly, the conditional mean is also an asymmetrical function of past returns. Specifically, positive past returns are more persistent than negative past returns of an equal magnitude. This behaviour is consistent with an asymmetric partial adjustment price model where news suggesting overpricing (negative returns) are incorporated faster into current prices than news suggesting underpricing (positive returns). Furthermore, the asymmetric adjustment of prices to past information could be partially responsible for the asymmetries in the conditional variance if the degree of adjustment and the level of volatility are positively related.     

Momentum Strategies

We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk, size, and book–to–market effects do not explain the drifts. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Security analysts' earnings forecasts also respond sluggishly to past news, especially in the case of stocks with the worst past performance. The results suggest a market that responds only gradually to new information.     

Do Industries Explain Momentum?

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.     

Consistency of firms' past financial performance measures and future returns

In this study, I show that growth consistency in firms' past financial performance measures is useful in predicting future stock returns. Firms consistently ranking in the lowest 30 percent of past financial growth measures have greater rates of returns relative to their inconsistent low-growth firm counterparts. The return differential between these two groups increases uniformly with the length of estimation intervals of past performance data. Firms consistently ranking in the top 30 percent of growth rates earn slightly lower returns than inconsistent high-growth firms. These findings indicate that investors overreact to consistency in financial metrics, but this overreaction is more pronounced and persistent for consistent low-growth firms than that for consistent high-performing firms. Regression analyses reveal that consistency of firms' past financial performance predicts subsequent price movement. This association between past growth consistency and future returns is stronger for consistent low-growth firms relative to consistent high-growth firms.     

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.     

Impact of investors’ status on their evaluation of positive and negative,and past and future information

This paper examines the effect of investors’ status (current and prospective) on their evaluation of information varying in valence (negative and positive) and temporality (past and future). Master of Business Administration graduates, proxying for current or prospective investors, rated the relevance of negative, positive, past, and future Management Discussion and Analysis information. Investors’ relevance ratings of information resulted in the following ranking (from highest to lowest): negative‐future, negative‐past, positive‐future, and positive‐past information. Furthermore, prospective investors (relative to current) rated positive and future information as more relevant and negative information as less relevant. Implications for effective disclosure strategies and policies are discussed.     

Market Reactions to Tangible and Intangible Information

The book‐to‐market effect is often interpreted as evidence of high expected returns on stocks of “distressed” firms with poor past performance. We dispute this interpretation. We find that while a stock's future return is unrelated to the firm's past accounting‐based performance, it is strongly negatively related to the “intangible” return, the component of its past return that is orthogonal to the firm's past performance. Indeed, the book‐to‐market ratio forecasts returns because it is a good proxy for the intangible return. Also, a composite equity issuance measure, which is related to intangible returns, independently forecasts returns.     

The Predictive Ability of Direct Method Cash Flow Information

This research examines the predictive ability of direct method cash flow information for firms that use the direct method in their cash flow statements. We use cross sectional and pooled time series regressions to predict operating cash flow data and assess relative predictive ability. Principal findings are: (1) past period direct method cash flow data predict future operating cash flow better than indirect method cash flow data; (2) past period direct method gross operating cash flows predict future net operating cash flow better than past period net operating cash flow; (3) measurement error exists in estimates of direct method operating cash flows from other financial statement data; (4) past operating cash flows predict future operating cash flows better than earnings and accruals.     

The fundamentals of momentum investing: European evidence on understanding momentum through fundamentals

This paper tests Ahmed and Safdar's noise‐related fundamentals‐based explanation for the momentum premium in European equity markets. Consistent with the view that past price changes may be partially driven by noise, the future return behaviour of winners and losers is significantly dependent upon the degree to which past price performance is consistent with fundamentals. European momentum profits are concentrated among those firms where past price performance is congruent with fundamentals, but absent among those firms where past price performance is incongruent with fundamentals. The significantly different momentum premiums on congruent and incongruent fundamentals‐momentum strategies are attributable to the exploitation of existing mispricing among momentum stocks that can be ex ante identified using firm fundamentals.     

Performance Volatility and Wage Elasticity: An Examination of Listed Chinese A-share Enterprises

The management of future financial risk on the part of managers and changes in firm finances are two of the fundamental reasons for upward and downward rigidity of wages. The proxy variable for firm financial risk is volatility, the past performance of which is among the principal indicators of wage rigidity. In firms whose current performance is on the upswing, the greater the volatility in past performance, the smaller the elasticity ratio and the more acute the upward rigidity; the more stable past performance, the larger the elasticity ratio and the more acute the upward elasticity. In firms in which current performance is declining, greater past performance volatility leads to a larger elasticity ratio and more acute downward rigidity, whereas more stable such performance leads to a smaller elasticity ratio and more acute downward rigidity.     

Analysts’ Momentum Recommendations

We document that the likelihood of analyst recommendations following past stock returns decreased abruptly in 2003, coinciding with the Global Settlement and other regulatory changes designed to restrain analysts’ conflicts of interest. We also document that the likelihood of recommendations following past stock returns is abnormally high for recommendations issued after negative stock returns (but not for those issued after positive stock returns), among inexperienced and inaccurate analysts, among large brokerage houses, and for companies with high share turnover. Moreover, the recommendations that are more likely to follow past stock returns are accompanied by earnings forecast revisions that are larger in magnitude and less accurate ex post. Overall, our findings suggest that analysts with conflicts of interest and limited ability are more likely to base their recommendations on past stock returns. Finally, we document that the recommendations that are more likely to follow past stock returns (especially those that were issued before 2003 and those that are issued after negative stock returns) contribute to existing price momentum by generating incrementally stronger short‐term and long‐term stock returns.     

Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency

This paper documents that strategies which buy stocks that have performed well in the past and sell stocks that have performed poorly in the past generate significant positive returns over 3-to 12-month holding periods. We find that the profitability of these strategies are not due to their systematic risk or to delayed stock price reactions to common factors. However, part of the abnormal returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented.     

Information misweighting and the cross-section of stock recommendations

This paper provides evidence that analysts whose earnings forecast revisions showed signs of greater exaggeration in the past make recommendation changes that lead to lower abnormal returns than their peers. Interpreting stock recommendations as a forecast of future abnormal returns, I show that this evidence is consistent with the hypothesis that analysts who typically exaggerate or overstate the weight of their private information when issuing forecasts also do so when making recommendations. The paper also shows that past earnings forecasts provide incremental information about analysts' recommending behavior beyond that contained in past recommendations.     

On the Stability of the Cross‐Section of Expected Stock Returns in the Cross‐Section: Understanding the Curious Role of Share Turnover

In this paper, we shed further light on cross‐sectional predictors of stock return performance. Specifically, we explore whether the cross‐section of expected stock returns is robust within stock groups sorted by past monthly return. We find that the book/market and momentum effects are remarkably robust to sorting on past returns. However, share turnover is negatively related to future returns for stocks with abnormally low stock price performance in the recent past, but postively related to returns for well‐performing stocks. This casts doubt on the use of turnover as a liquidity proxy, but is consistent with turnover being a proxy for momentum trading which pushes prices in the direction of past price movements. Our results are robust to both NYSE/AMEX and Nasdaq stocks, and also robust to stratifying the sample by time period.     

MUTUAL FUNDS SELECTION BASED ON FUNDS CHARACTERISTICS

The popular investment strategy in the literature is to use only past performance to select mutual funds. We investigate whether an investor can select superior funds by additionally using fund characteristics. After considering the fund fees, we find that combining information on past performance, turnover ratio, and ability produces a yearly excess net return of 8.0%, whereas an investment strategy that uses only past performance generates 7.1%. Adjusting for systematic risks, and then using fund characteristics, increases yearly alpha significantly from 0.8% to 1.7%. The strategy that also uses fund characteristics requires less turnover.     

Multifactor Explanations of Asset Pricing Anomalies

Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the CAPM, they are called anomalies. We find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Our results are consistent with rational ICAPM or APT asset pricing, but we also consider irrational pricing and data problems as possible explanations.