The characteristics of the mean-variance, efficient portfolio frontier have been discussed at length in the literature. However, for more than three assets, the general approach has been to display qualitative results in terms of graphs. In this paper, the efficient portfolio frontiers are derived explicitly, and the characteristics claimed for these frontiers are verified. The most important implication derived from these characteristics, the separation theorem, is stated and proved in the context of a mutual fund theorem. It is shown that under certain conditions, the classic graphical technique for deriving the efficient portfolio frontier is incorrect.

Determining the market values of streams of future returns is a task common to many sorts of economic analysis. The literature on this subject is extensive at all levels of abstraction. However, most work has not taken uncertainty into account in a meaningful way.

Many empirical studies find that the distribution of stock returns departs from normality. In such cases, it is desirable to employ a statistical estimation procedure that may be more efficient than ordinary least squares. This paper describes various robust methods, which have attracted increasing attention in the statistical literature, in the context of estimating beta risk. The empirical analysis documents the potential efficiency gains from using robust methods as an alternative to ordinary least squares, based on both simulated and actual returns data.

Abstract I document wage convergence in conglomerates using detailed plant-level data: Workers in low-wage industries collect higher-than-industry wages when the diversified firm also operates in high-wage industries. I confirm this effect by exploiting the implementation of the North American Free Trade Agreement (NAFTA) and changes in minimum wages at the state level as sources of exogenous increases in wages in some plants. I then track the evolution of wages of the remaining workers of the firm, relative to workers of unaffiliated plants. Plants where workers collect higher-than-industry wages operate with higher capital intensity, suggesting that internal labor markets may affect investment decisions in internal capital markets.

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Abstract In this paper, we examine the effect of shareholder rights on reducing the cost of equity and the impact of agency problems from free cash flow (FCF) on this effect. We find that firms with strong shareholder rights have a significantly lower implied cost of equity after controlling for risk factors, price momentum, analysts’ forecast biases, and industry and year effects than do firms with weak shareholder rights. Further analysis shows that the effect of shareholder rights on reducing the cost of equity is significantly stronger for firms with more severe agency problems from FCFs.

Using novel earnings calendar data, we show that firms’ advanced scheduling of earnings announcement dates foreshadows their earnings news. Firms that schedule later-than-expected announcement dates subsequently announce worse news than those scheduling earlier-than-expected announcement dates. Despite scheduling disclosures being observable weeks ahead of earnings announcements, we show that equity markets fail to reflect the information in these disclosures until the announcement itself. By also showing that option markets respond efficiently to volatility-timing information embedded in the same scheduling disclosures, we provide novel evidence that markets fail to react to information about future earnings despite investors immediately trading on the underlying signal.

Scott W. Barnhart, Andrew C. Szakmary, Testing the Unbiased Forward Rate Hypothesis: Evidence on Unit Roots, Co- Integration, and Stochastic Coefficients, The Journal of Financial and Quantitative Analysis, Vol. 26, No. 2 (Jun., 1991), pp. 245-267

Abstract We test for the presence of a systematic tail risk premium in the cross section of expected returns by applying a measure of the sensitivity of assets to extreme market downturns, the tail beta. Empirically, historical tail betas help predict the future performance of stocks in extreme market downturns. During a market crash, stocks with historically high tail betas suffer losses that are approximately 2 to 3 times larger than their low-tail-beta counterparts. However, we find no evidence of a premium associated with tail betas. The theoretically additive and empirically persistent tail betas can help assess portfolio tail risks.

Abstract The trading of shares of the same firm in multiple markets has become common over the last 30 years, but there is little empirical evidence on the extent to which investors actively exploit multimarket environments. We introduce a volume-based measure of multimarket trading to address this question. Analyzing a large set of cross-listed firms, we find higher multimarket trading among markets with similar designs and strong enforcement of insider trading laws and for firms with higher institutional ownership. These findings are important for firms evaluating the benefits of cross listing and for markets competing for order flow.