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Abstract:
An exclusive focus on bottom-line income misses important information about the quality of earnings. Accruals (the difference between accounting earnings and cash flows) are reliably, negatively associated with future stock returns. Earnings increases that accompanied by high accruals, suggesting low-quality earnings, are associated with poor future returns. We explore various hypotheses - earnings manipulation, extrapolative biases about future growth, and under-reaction to business conditions - to explain accruals' predictive power. Distinctions between the hypotheses are based on evidence from operating performance, the behavior of individual accrual items, and discretionary versus nondiscretionary components of accruals.

Abstract:
We examine whether stock prices fully reflect the value of firms' intangible assets, focusing on research and development (R&D). Since intangible assets are not reported on financial statements under current U.S. accounting standards and R&D spending is expensed, the valuation problem may be especially challenging. Nonetheless we find that historically the stock returns of firms doing R&D on average matches the returns on firms with no R&D. For companies engaged in R&D, high R&D intensity has a distinctive effect on returns for two groups of stocks. Within the set of growth stocks, R&D-intensive stocks tend to out-perform stocks with little or no R&D. Companies with high R&D relative to equity market value (who tend to have poor past returns) show strong signs of mis-pricing. In both cases the market apparently fails to give sufficient credit for firms' R&D investments. Our exploratory investigation of the effects of advertising on returns yields similar results. We also provide evidence that R&D intensity is positively associated with return volatility, everything else equal. Insofar as the association reflects investors' lack of information about firms' R&D activity, increased accounting disclosure may be beneficial.

Abstract:
We examine whether stock prices fully reflect the value of firms? intangible assets, focusing on research and development (R&D). Since intangible assets are not reported on financial statements under current U.S. accounting standards and R&D spending is expensed, the valuation problem may be especially challenging. Nonetheless we find that historically the stock returns of firms doing R&D on average matches the returns on firms with no R&D. For companies engaged in R&D, high R&D intensity has a distinctive effect on returns for two groups of stocks. Within the set of growth stocks, R&D-intensive stocks tend to out-perform stocks with little or no R&D. Companies with high R&D relative to equity market value (who tend to have poor past returns) show strong signs of mis-pricing. In both cases the market apparently fails to give sufficient credit for firms? R&D investments. Our exploratory investigation of the effects of advertising on returns yields similar results. We also provide evidence that R&D intensity is positively associated with return volatility, everything else equal. Insofar as the association reflects investors? lack of information about firms? R&D activity, increased accounting disclosure may be beneficial.

Abstract:
Analysts' earnings forecasts are influenced by their desire to win investment banking clients. We hypothesize that the equity bull market of the 1990s, along with the boom in investment banking business, exacerbated analysts' conflict of interest and their incentives to adjust strategically forecasts to avoid earnings disappointments. We document shifts in the distribution of earnings surprises, the market's response to surprises and forecast revisions, and in the predictability of non-negative surprises. Further confirmation is based on subsamples where conflicts of interest are more pronounced, including growth stocks and stocks with consecutive non-negative surprises; however shifts are less notable for analysts without ties to investment banking and in international markets.

Abstract:
Analysts' earnings forecasts are influenced by their desire to win investment banking clients. We hypothesize that the equity bull market of the 1990s, along with the boom in investment banking business, exacerbated analysts' conflict of interest and their incentives to adjust strategically forecasts to avoid earnings disappointments. We document shifts in the distribution of earnings surprises, the market's response to surprises and forecast revisions, and in the predictability of non-negative surprises. Further confirmation is based on subsamples where conflicts of interest are more pronounced, including growth stocks and stocks with consecutive non-negative surprises; however shifts are less notable in international markets.

Abstract:
Expectations about long-term earnings growth are crucial to valuation models and cost of capital estimates. We analyze historical long-term growth rates across a broad cross section of stocks using several indicators of operating performance. We test for persistence and predictability in growth. While some firms have grown at high rates historically, they are relatively rare instances. There is no persistence in long-term earnings growth beyond chance, and there is low predictability even with a wide variety of predictor variables. Specifically, IBES growth forecasts are overly optimistic and add little predictive power. Valuation ratios also have limited ability to predict future growth.

Abstract:
Expectations about long-term earnings growth are crucial to valuation models and cost of capital estimates. We analyze historical long-term growth rates across a broad cross-section of stocks using several indicators of operating performance. We test for persistence and predictability in growth. While some firms have grown at high rates historically, they are relatively rare instances. There is no persistence in long-term earnings growth beyond chance, and there is low predictability even with a wide variety of predictor variables. Specifically, IBES growth forecasts are overly optimistic and add little predictive power. Valuation ratios also have limited ability to predict future growth.

Abstract:
Expected long-term earnings growth rates are crucial inputs to valuation models and for cost of capital estimates. We analyze historical long-term growth rates across a broad cross-section of stocks using several operating performance indicators. We test whether growth persists, and whether it is forecastable. Cases of very high growth have occurred, but are relatively rare. There is scant persistence in growth beyond chance, and limited ability to identify firms with high future long-term growth. IBES forecasts are too optimistic, and have low predictive power for long-term growth. Regressions using a variety of predictors confirm the low predictability in growth. Valuations that assume persistently high growth over prolonged periods rest on shaky foundations.

Abstract:
Academic and practitioner research yields a proliferation of methods using size and value/growth attributes or factors to evaluate portfolio performance. We assess the relative merits of several of the most widely-used procedures, including variants of matched-characteristic benchmark portfolios and time-series return regressions, by applying them to a sample of active money managers and passive indexes. Estimated abnormal returns display large variation across approaches. The benchmarks most widely used in academic research - attribute-matched portfolios from independent sorts, the conventional three-factor time series model, and cross-sectional regressions of returns on stock characteristics - have poor ability to track returns. Simple alterations are provided that improve the performance of the methods.

Abstract:
Academic and practitioner research yields a proliferation of methods using size and value/growth attributes or factors to evaluate portfolio performance. We assess the relative merits of several of the most widely-used procedures, including variants of matched-characteristic benchmark portfolios and time-series return regressions, by applying them to a sample of active money managers and passive indexes. Estimated abnormal returns display large variation across approaches. The benchmarks most widely used in academic research - attribute-matched portfolios from independent sorts, the conventional three-factor time series model, and cross-sectional regressions of returns on stock characteristics - have poor ability to track returns. Simple alterations are provided that improve the performance of the methods.

Benchmarking, Portfolio Manager, Institutional Investors, Performance Evaluation

Abstract:
We relate the predictability of future returns from past returns to the market's underreaction to information, focusing on past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Market risk, size and book-to- market effects do not explain the drifts. 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.

Abstract:
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 returns and past earnings surprise each and 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.

Abstract:
An exclusive focus on bottom-line income misses important information about the quality of earnings. Accruals (the difference between accounting earnings and cash flow) are reliably, negatively associated with future stock returns. Earnings increases that are accompanied by high accruals, suggesting low-quality earnings, are associates with poor future returns. We explore various hypotheses - earnings manipulation, extrapolative biases about future growth, and under-reaction to changes in business conditions - to explain accruals' predictive power. Distinctions between the hypotheses are based on evidence from operating performance, the behavior of individual accrual items, discretionary versus nondiscretionary components of accruals, and special items. We check for robustness using within-industry comparisons, and data on U.K. stocks.

Abstract:
An exclusive focus on bottom-line income misses important information about the quality of earnings. Accruals (the difference between accounting earnings and cash flow) are reliably, negatively associated with future stock returns. Earnings increases that are accompanied by high accruals, suggesting low-quality earnings, are associated with poor future returns. We explore various hypotheses - earnings manipulation, extrapolative biases about future growth, and under-reaction to business conditions - to explain accruals' predictive power. Distinctions between the hypotheses are based on evidence from operating performance, the behavior of individual accrual items, and discretionary versus nondiscretionary components of accruals.

Abstract:
We provide an exploratory investigation of mutual funds' investment styles. Funds' styles tend to cluster around a broad market benchmark. When funds deviate from the benchmark they are more likely to favor growth stocks with good past performance. There is some consistency in styles, although funds with poor past performance are more likely to change styles. Some evidence suggests that growth funds have better style-adjusted performance than value funds. The results are not sensitive to style identification procedure, but an approach based on fund portfolio characteristics performs better in predicting future fund returns.

Abstract:
We evaluate the performance of models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. We compare the models' forecasts of future covariances and the optimized portfolios' out-of-sample performance. A few factors capture the general covariance structure. Portfolio optimization helps for risk control, and a three-factor model is adequate for selecting the minimum-variance portfolio. Under a tracking error volatility criterion, which is widely used in practice, larger differences emerge across the models. In general more factors are necessary when the objective is to minimize tracking error
volatility.

Abstract:
We evaluate the performance of different models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. Comparisons are based on forecasts of future covariances as well as the out-of-sample volatility of optimized portfolios from each model. A few factors capture the general covariance structure but adding more factors does not improve forecast power. Portfolio optimization helps for risk control, but the different covariance models yield similar results. Using a tracking error volatility criterion, larger differences appear, with particularly favorable results for a heuristic approach based on matching the benchmark's attributes.

Abstract:
The ability to identify which factors best capture systematic return covariation is central to applications of multifactor pricing models. This paper uses a common data set to evaluate the performance of various proposed factors in capturing return comovements. Factors associated with the market, size, past return, book-to-market and dividend yield help explain return comovement on an out-of-sample basis (although they are not necessarily associated with large premiums in average returns). Except for the default premium and the term premium, macroeconomic factors perform poorly. We document regularities in the behavior of the more important factors, and confirm their influence in the Japanese and U.K. markets as well.

Abstract:
The ability to identify which factors best capture systematic return covariation is central to applications of multifactor pricing models. This paper uses a common data set to evaluate the performance of various proposed factors in capturing return comovements. Factors associated with the market, size, past return, book-to-market and dividend yield help explain return comovement on an out-of-sample basis (although they are not necessarily associated with large premiums in average returns). Except for the default premium and the term premium, macroeconomic factors perform poorly. We document regularities in the behavior of the more important factors, and confirm their influence in the Japanese and U.K. markets as well.

Abstract:
We compare execution costs (market impact plus commission) on the New York Stock Exchange (NYSE) and on Nasdaq for institutional investors. The differences in cost generally conform to each market's area of specialization. Controlling for firm size, trade size and the money management firm's identity, costs are lower on Nasdaq for trades in comparatively smaller firms. For the smallest firms, the cost advantage under a pre-execution benchmark is 0.68 percent. However, trading costs for the larger stocks are lower on NYSE. For the largest stocks, costs are lower by 0.48 percent on NYSE. Given the extreme difficulty of controlling for variables other than market structure, however, comparisons of costs should be interpreted with extreme caution.

Abstract:
Investors and the financial media apparently believe that some Wall Street equity analysts research is superior to others. We examine whether such quality differentials exist, in terms of analysts ability to forecast earnings accurately, and whether these differentials are identifiable on an ex ante basis. The results suggest that there is some persistence in analysts forecast accuracy. In particular, forecast accuracy is associated with analyst experience, breadth of coverage, timeliness, and brokerage firm size. Analysts selected for All-Star status by industry publications also tend to have higher forecast accuracy. However, the differences in forecast accuracy do not produce material differences in the dollar magnitudes of forecast errors.

Security analysts, earnings forecasts, forcast accuracy, all-star analysts

Abstract:
A company's industry affiliation is commonly used to construct homogeneous stock groupings for portfolio risk management, relative valuation, and peer-group comparisons. A variety of industry classification systems have been adopted, however, creating disagreements as to companies' industry assignments. This analysis of the Global Industry Classification System (GICS) and Fama-French system indicates that common movement in returns and operating performance resulting from industry effects is stronger for stocks of large companies than for those of small companies. Also, increasingly fine levels of disaggregation improve discrimination up to six-digit GICS codes, after which the benefits tail off. Stock groupings based on industry exhibit stronger out-of-sample homogeneity than groups formed from statistical cluster analysis.

Portfolio Management: Equity Strategies, Asset Allocation

Abstract:
A great deal of academic empirical research has been published on value and growth investing. We review and update this literature, discuss the various explanations for the performance of value versus growth stocks, review the empirical research on the alternative explanations, and provide some new results based on an updated and expanded sample. The evidence suggests that, even after taking into account the experience of the late 1990s, value investing generates superior returns. Common measures of risk do not support the argument that the return differential is a result of the higher riskiness of value stocks. Instead, behavioral considerations and the agency costs of delegated investment management lie at the root of the value-growth spread.

Portfolio Management, Equity Strategies, Investment Theory, Behavioral Finance

Abstract:
All trades executed by 37 large investment management firms from July 1986 to December 1988 are used to study the price impact and execution cost of the entire sequence ("package") of trades that we interpret as an order. We find that market impact and trading cost are related to firm capitalization, relative package size and, most importantly, to the identity of the management firm behind the trade. Money managers with high demands for immediacy tend to be associated with larger market impact.