This paper examines the role of focus versus diversification in explaining the economic impact of corporate capital investments. I find that the stock market's responses to announcements of capital investments are more favorable for focused firms than for diversified firms. I also show that focused firms exhibit significantly better post-investment operating performance than diversified firms. The overall findings in this study suggest that the investment opportunities hypothesis dominates the internal capital markets hypothesis in terms of the net economic impact of capital investments on the investing firms.

Security behavior in bull and bear markets has received some attention in recent years. Fabozzi and Francis [5] first documented evidence that security betas are not influenced by the alternating forces of bull and bear markets. Their subsequent study of mutual fund betas also indicated that mutual funds generally respond indifferently to bull and bear market conditions. Using the concept of bull and bear market variations, Kim and Zumwa1t [9] developed and tested the risk premiums associated with the upside and the downside portions of returns variation. They concluded that investors expect to receive a risk premium for downside risk and pay a premium for upside variation of returns. From their results, Kim and Zumwalt [9] suggested that the down-market beta measuring downside risk (downside variation of returns) may be a more appropriate measure of portfolio risk than the single beta in the market model.

Over the past years the beta coefficient has been widely used as a measure of systematic risk in investment and portfolio analysis. The validity of using the beta coefficient as the proper measure of systematic risk is dependent upon the assumption that the beta coefficient is stationary over time. Unfortunately, this assumption has been challenged by a number of empirical studies which have found the beta coefficient to be unstable over time. Examples of such empirical investigations are those documented by Blume [4], Levy [12], Levitz [11], Baesel [2], Altman, Jacquillat, and Levasseur [1], and Roenfelt, Griepentrong, and Pflaum [16]. Most recently, Fabozzi and Francis [9] reported that some security beta coefficients tend to be random over time. Their findings also support the regression tendency of the beta coefficients towards the mean over time, as found by Blume [4]. Thus, because the beta coefficient is changing over time, the use of the ordinary least-squares (OLS) method in investment and portfolio analysis will yield an inefficient estimate of systematic risk. Furthermore, the OLS estimates of security and portfolio residual risks will be influenced by the variability of beta coefficient. Therefore, the purpose of this paper is to investigate the relationship between the variability of the beta coefficient and portfolio residual risk, and hence to provide a real picture of the process of portfolio diversification under the condition of beta nonstationarity. It is shown that the use of the OLS method to estimate security and portfolio residual risks will produce an incorrect conclusion that larger residual risks tend to be associated with higher variability in the beta coefficient.

The problems associated with the investment horizon and systematic risk estimation have been investigated in some detail. Jensen [7] has shown that investment horizon has some impact on the estimated systematic risk; Cheng and Deets [1] have raised some questions about Jensen's instantaneous systematic risk estimation method; Lee [9] has derived the relationship between the estimated instantaneous systematic risk and the estimated finite systematic risk; Levhari and Levy [11] have shown that there exist some relationships between the magnitude of estimated systematic risk and the length of investment horizon; based upon Zellner and Montimarquette's [19] time aggregation technique, Lee and Morimune [10] have shown that the investment horizon problem can be treated either as a time aggregation problem or as a specification problem. However, systematic risk estimates in terms of additive and multiplicative rates of return have not been investigated in detail. The purpose of this paper is to employ the time aggregation technique proposed by Zellner and Montimarquette [19] to investigate the impact of time aggregation on systematic risk associated with the market model. It is shown that autocorrelation and variation in market rates of return are two important factors in determining the magnitude of the estimated systematic risk associated with additive as well as multiplicative models.

The problem of the portfolio demand for money was first rigorously studied by Tobin [22]. It has been analyzed since then, by Hicks [8] and Arrow [1], among many others. Many interesting results and implications regarding liquidity preference and risk-taking are derived in these studies. However, the effect of purchasing power risk on liquidity preference has been overlooked in these studies.

We have formulated the mean-variance models of portfolio selection with stochastic cash demand. The results of the general model have indicated that the characteristic of the investor's stochastic cash demand, the liquidity risks of assets (measured by the covariance between an asset's return and the cash demand), and the structure of transfer costs also play important roles in the determination of the investor's optimal portfolio. We have also shown that the model of portfolio selection with stochastic cash demand can be greatly simplified if the assumption of symmetric transfer costs is invoked. Furthermore, it has been shown that the simplified model can be reformulated and solved by the LP techniques. Thus, LP formulation of portfolio selection with stochastic cash demand should have practical usefulness.Finally, along the line of works by Chen, Jen and Zionts [3, 4], Pogue [14, 15] and Stone and Reback [20], one can extend the analysis in this paper to the problem of dynamic portfolio management with stochastic cash demand and transfer costs.

Broadly speaking there are two models to the problem of asset valuation under uncertainty and aversion to risk. Under one, the certaintyequivalent method, each future return is converted to its certainty equivalent and discounted at the pure rate of interest. Under the other, the risk-adjusted discount rate method, each future return is discounted at an appropriate discount rate. The interrelation and validity of these models of asset valuation have come under discussion in two important works on stock valuation.

We investigate the effect of information asymmetry on corporate tax avoidance. Using a difference-in-differences matching estimator to assess the effects of changes in analyst coverage caused by broker closures and mergers, we find that firms avoid tax more aggressively after a reduction in analyst coverage. We further find that this effect is mainly driven by firms with higher existing tax-planning capacity (e.g., tax-haven presence), smaller initial analyst coverage, and a smaller number of peer firms. Moreover, the effect is more pronounced in industries where reputation matters more and in firms subject to less monitoring from tax authorities.

This article studies buybacks with two informed parties: a manager and an outside speculator. Buybacks introduce two countervailing forces. A competition effect reduces speculator profits when buybacks compete against speculative trades. A dispersion effect increases speculator profits: buying undervalued shares generates gains, while buying overvalued shares generates losses, widening the dispersion in per-share value across states. Sufficiently informed buybacks benefit shareholders; uninformed buybacks harm them. These effects vary with shareholders’ liquidity exposures. The desirability of informed buybacks depends on the prevalence of speculation. Authorization depends on ownership, governance, and market conditions. Shareholders might welcome informed buybacks—not merely tolerate them.

I show that cash distributions through cash mergers, dividend payments, and stock buybacks are, in principle, similar to investor fund flows in generating demand for investable assets. Abnormal returns on certain assets can be forecasted because delegated investors predictably reinvest cash returns toward certain holdings. Novel measures of stock-level demand constructed using proportional reinvestments by mutual funds predict abnormal returns and issuances in noncash-paying stocks. These results highlight an alternative and substantial source of price fluctuations in the cross section of equities.