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This paper explores the relationship between size, book-to-market, beta, and expected stock returns in the U.S. Information Technology sector over the July 1990–June 2001 period. Two models, the multivariate model and the three-factor model, are employed to test these relationships. The risk-return tests confirm the relationship between size, book-to-market, beta and stock returns in IT stocks is different from that in other non-financial stocks. However, the sub-period results (the periods before and after the technology crash in April 2000) show that the nature of the relationship between stock returns, size, book-to-market, and market factors, or the magnitude of the size, book-to-market, and market premiums, is on average unchanged for both sub-periods. This result suggests the technology stock crash in April 2000 was not a correction of stock prices.

Whether the risk factors or firm characteristics cause the value premium of stocks still needs further investigation. This paper shows that the factor‐based models are significant but not sufficient for the stock returns in Taiwan. Size or book‐to‐market ratio alone cannot influence the stock returns under a factor‐based model. However, size along with book‐to‐market is significant under a factor‐based model. Furthermore, the risk characteristics are more influential than the factor load in stock return behavior. We conclude that employing only a factor‐based model or only risk characteristics will not consider some important content in stock returns.

We would like to thank C. Y. Chen, Wenchih Lee, two anonymous referees and the seminar participants at the 2000 FMA annual meeting for their helpful comments and encouragement. All of the remaining errors are our responsibility.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

This study examines the five-factor model of Fama and French (2015) on the French stock market by comparing it to the Fama and French (1993)’s base model. The new Fama and French five-factor model directed at capturing two new factors, profitability and investment in addition to the market, size and book to market premiums. The pricing models are tested using a time-series regression and the Fama and Macbeth (1973) methodology. The regularities in the factor’s behavior related to market conditions and to the sovereign debt crisis in Europe are also examined. The findings of Fama and French (2015) for the US market are confirmed on the Paris Bourse. The results show that both models help to explain some of the stock returns. However, the five-factor model is better since it has a marginal improvement over the widely used three-factor model of Fama and French (1993). In addition, the investment risk premium seems to be better priced in the French stock market than the profitability factor. The results are robust to the Fama and Macbeth (1973) methodology. Moreover, profitability and investment premiums are not affected by market conditions and the European sovereign debt crisis.

The purpose of the study was to provide empirical support for the Miller model. The paper proposes the use of the ratio of individual to institutional holdings as a proxy for heterogeneous expectations of security returns.

Both bivariate t‐tests and regression analysis were used to test whether optimistic valuations existed for stocks with high levels of institutional ownership. Data on open short positions were collected and hypothesized to decrease with the level of institutional holdings. High ratio stocks were compared to glamor stocks and low ratio stocks to value stocks.

For stocks with higher institutional ownership, optimistic valuations dominated resulting in significantly lower future security returns than for stocks with higher individual ownership thereby supporting the Miller model. The results were not sensitive to variations in size, momentum, and book‐to‐market ratios. Further support for the Miller model was provided by the finding that open short positions decreased with the level of institutional holdings. High ratio stocks resembled glamor stocks and low ratio stocks corresponded to value stocks.

This study is limited to the ultra‐short term period of one month after portfolio creation. Future research should extend it to the three‐to‐five year time horizon.

Ultra‐short term investors should hold value stocks, intermediate three‐12 month investors should hold glamor stocks, and long‐term investors should hold value stocks.

The finding of a new proxy for heterogeneous expectations. The paper also establishes a new methodology for testing the Miller model.

Past studies have shown that investment strategy using two popular metrics, the earnings‐price ratio (EP) and book‐to‐market ratio (BM) enable investors to reap abnormal returns. More recent development of another ratio, economic value‐added‐to‐market value (EVAM) can be seen as a hybrid of EP and BM ratios. The purpose of this study is to examine whether portfolios created by utilizing the EVAM ratio will generate higher returns than portfolios formed with EP or BM ratios.

Utilizing the EVA data obtained from Stern Stewart & Co. and financial data from COMPUSTAT and center for research in security prices (CRSP), portfolios are created following the Fama and French portfolio formation methodology. The authors form separate portfolios using EP, BM or EVAM ratios where firms are ranked by a ratio in year t, then split into deciles. Then portfolios are constructed in year t + 1 for each decile and equally weighted portfolio returns are calculated. The cumulative ten‐year returns are compared between portfolios formed with EP, BM and EVAM ratios.

There are three interesting findings. One, the EP portfolios depict results that have long been documented. That is, value stock (low price‐to‐earnings ratio firms) and growth stocks (high price‐to‐earnings ratio) exhibit the highest returns. Two, the ten BM portfolio performances are not statistically different. Three, the EVAM ratios indicate that the negative EVAM (lowest decile) portfolio exhibit the highest return and the second highest return is generated by the highest EVAM portfolio. The general results of the thirty portfolios show that the highest EVAM ratio (EVAM10) performs the best. However, the pairwise mean differences between EP, BM and EVAM portfolios do not show statistical differences over the 1995–2004 period.

Although investment strategies using EP ratio and BM ratio have been thoroughly studied, investment strategy using EVAM ratio has not. Given that it has been documented that EVA is a better conceptual measure of value, portfolio managers or investors would be interested to know whether utilizing EVA for investment strategy would earn a higher return than strategies that use EP or BM ratios.

The purpose of this paper is to empirically examine whether investor attention is a significant risk pricing factor.

Using investor attention data from Eastmoney.com, which provides for each stock the number of investors whose watch list includes that stock on a daily basis, this paper constructs a “heat” factor based on the change in investor attention and a “market exposure” factor based on the proportion of attention on a given stock over the attention to all stocks. Using the Fama−MacBeth two-step regression and a rolling analysis, this study examines the ability of the investor attention factor to explain market returns.

The empirical results show that there exists a risk premium for the “heat” factor and “market exposure” factor that is significantly different from zero. This finding shows that investor attention can systematically influence stock returns, making it a significant risk pricing factor.

This paper’s research on the risk pricing factors of investor attention can help investors to rationally build investment portfolios, avoid risks and form a sound investment concept, which will further reveal the information recognition mechanism of the capital market and standardize the information disclosure behavior of listed companies.

This paper provides evidence that investor attention is a risk pricing factor for the stock market. There are “heat” factors and “market exposure” factors in the Chinese stock market that significantly affect the purchasing behavior of individual investors.

The purpose of this paper is to examine the operating performance of Indian using difference-in-difference (DD) methodology. It, further, examines whether there is a difference in the operating performance of acquirers doing partial and full acquisitions.

Four different benchmark criteria are used to select control firms, namely, size, size and industry, size and leverage, and size and book-to-market ratio. To measure the operating performance, return on assets (ROA) is calculated as the ratio between earnings before depreciation, interest, tax and amortization (EBDITA) and total assets (TA), expressed in percentage. This paper examines the ROA of event and control firms for three years in each pre- and post-acquisition period and finally compares them using the DD method.

Using a sample of Indian acquirers, the results show that the operating performance of Indian acquirers neither improves nor deteriorates after accounting for an appropriate benchmark. Operating performance of event firms significantly reduces in the post-acquisition period. However, non-acquiring firms of similar size and pre-operating performance also exhibit similar results. Finally results show that, the operating performance of acquirers making full acquisitions deteriorates.

It provides insights into the operating performance of Indian acquirers with an improved methodology, which accounts for the performance of control firms. The author also uses multiple matching criteria to find control firms to overcome the possible bias of the results dependent on the matching criteria. To the best of the author’s knowledge, the author could not find other studies comparing the operating performance of acquirers making partial and full acquisitions.

The purpose of the paper is to investigate the relation between the value/growth anomaly and the external financing anomaly by considering an expanded value/growth indicator: free cash flow yield (free cash flows scaled by price).

The paper utilizes portfolio‐level tests and cross‐sectional regressions.

In line with the literature on contrarian portfolios, this paper finds that firms with low (high) free cash flow yield are experiencing low (high) returns. However, only when an investor buys (sells) stocks of firms with high (low) free cash flow yield that distribute (raise) capital, his zero‐cost portfolio is significant. These findings are robust, irrespective of the financing vehicle (equity or debt). Overall, their evidence suggests that distinctions between the value/growth anomaly and the external financing anomaly partially disappear, if one is willing to employ free cash flow yield as a proxy of the former anomaly.

The paper enhances one's understanding of the relation between asset pricing anomalies.

To test the Miller Price Optimism Model using a new proxy for heterogenous expectations and to examine if high differential stocks behave like glamour stocks and low differential stocks behave like value stocks.

Whisper/analyst forecast differentials were measured for a sample of stocks, combined into portfolios and held for one month. If the Miller model was supported, high differential stocks were expected to have lower portfolio returns than low differential stocks due to the greater divergence between optimistic whisper forecasts and rational analysts consensus forecasts.

High differential quintiles had significantly lower future returns than low differential quintiles supporting the Miller model. High differential stocks resembled glamour stocks while low differential stocks behaved like value stocks.

These results pertain to the ultra‐short time horizon of two months prior to the earnings announcement. Future research should replicate this study for a longer 3‐12 month time horizon.

Ultra short‐term investors should hold glamour stocks and long term investors should hold value stocks. Rising volatility suggests that investors should define the time horizon for holding assets.

It is one of only two studies that directly uses earnings forecasts as a proxy for heterogenous expectations. It adds to the sparse literature on whisper forecasts. It may be used by academicians studying price optimism effects and institutional investors following stock returns during earnings announcements.