Frank T. Magiera

Bio: Frank T. Magiera is an academic researcher. The author has contributed to research in topics: Equity (finance) & Stock (geology). The author has an hindex of 29, co-authored 162 publications receiving 4734 citations.

The Cross-section of Expected Stock Returns

Abstract: This paper studies the cross-sectional properties of return forecasts derived from Fama-MacBeth regressions. These forecasts mimic how an investor could, in real time, combine many firm characteristics to obtain a composite estimate of a stock’s expected return. Empirically, the forecasts vary substantially across stocks and have strong predictive power for actual returns. For example, using ten-year rolling estimates of Fama- MacBeth slopes and a cross-sectional model with 15 firm characteristics (all based on low-frequency data), the expected-return estimates have a cross-sectional standard deviation of 0.87% monthly and a predictive slope for future monthly returns of 0.74, with a standard error of 0.07.

Review: information technology and organizational performance: an integrative model of it business value

Abstract: Despite the importance to researchers, managers, and policy makers of how information technology (IT) contributes to organizational performance, there is uncertainty and debate about what we know and don't know. A review of the literature reveals that studies examining the association between information technology and organizational performance are divergent in how they conceptualize key constructs and their interrelationships. We develop a model of IT business value based on the resource-based view of the firm that integrates the various strands of research into a single framework. We apply the integrative model to synthesize what is known about IT business value and guide future research by developing propositions and suggesting a research agenda. A principal finding is that IT is valuable, but the extent and dimensions are dependent upon internal and external factors, including complementary organizational resources of the firm and its trading partners, as well as the competitive and macro environment. Our analysis provides a blueprint to guide future research and facilitate knowledge accumulation and creation concerning the organizational performance impacts of information technology.

Home Bias at Home: Local Equity Preference in Domestic Portfolios

Abstract: The strong bias in favor of domestic securities is a well-documented characteristic of international investment portfolios, yet we show that the preference for investing close to home also applies to portfolios of domestic stocks. Specifically, U.S. investment managers exhibit a strong preference for locally headquartered firms, particularly small, highly levered firms that produce nontraded goods. These results suggest that asymmetric information between local and nonlocal investors may drive the preference for geographically proximate investments, and the relation between investment proximity and firm size and leverage may shed light on several well-documented asset pricing anomalies.

Understanding Earnings Quality: A Review of the Proxies, Their Determinants and Their Consequences

Abstract: Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work.

Giving Content to Investor Sentiment: The Role of Media in the Stock Market

Abstract: I quantitatively measure the nature of the media's interactions with the stock market using daily content from a popular Wall Street Journal column. I find that high media pessimism predicts downward pressure on market prices followed by a reversion to fundamentals, and unusually high or low pessimism predicts high market trading volume. These results and others are consistent with theoretical models of noise and liquidity traders. However, the evidence is inconsistent with theories of media content as a proxy for new information about fundamental asset values, as a proxy for market volatility, or as a sideshow with no relationship to asset markets.