This paper examines whether investors with power utility functions choose mean-variance-(MV) efficient portfolios when returns are approximately normally distributed and there is borrowing or lending at a riskless interest rate. The results show that the unlevered portfolios of power utility investors plot very closely to the MV-efficient frontier. However, there are marked differences in the mix of risky assets, regardless of whether the portfolios are highly concentrated or widely diversified. Such differences allow power investors to remain solvent even when they lever their optimal portfolios to a greater extent than “less risk-averse” MV investors who risk bankruptcy. It is concluded that the investment policies of power utility and MV investors with similar risk aversion measures are not as similar as is commonly believed. This is particularly true for high power investors, unless explicit solvency constraints are imposed on the MV problem, and for low power investors when quadratic utility approximations are made to the power utility functions. These differences in the investment policies of power utility and MV investors lead us to question the widely-accepted assertion that the assumptions of homogeneous beliefs, normality, a riskless asset, and risk-averse investors imply the simple MV CAPM where all investors, including power utility investors, hold combinations of the market portfolio and the riskless asset.

We examine the effects of a temporary suspension of short-sale price tests on the options market. Consistent with the notion that put option trading substitutes for short selling, we find a significant reduction in put option volume. In addition, pressure on put option prices significantly declines, violations of the put-call parity become significantly less frequent, and option volume becomes less informed. Our findings add clarity to a long-standing debate on whether investors use options to circumvent equity short-selling restrictions.

The voluntary nature of hedge fund database reporting creates strategic listing opportunities for hedge funds. However, little is known about how managers list funds across multiple databases or whether investors are fooled by funds’ listing decisions. In this paper, we find that hedge funds strategically list their small, best-performing funds in multiple outlets immediately while preserving the option to list their other funds in additional databases later. We generally find that investors react rationally to these fund listings based on the predictability of performance. Finally, our results lead to specific guidelines on handling backfilled returns to minimize biases.

A majority of corporate zero-coupon bonds includes a call provision, giving the firm the right to call the bond at par value. In this paper, we investigate whether or not it is optimal for the firm to call such a bond for refunding purposes, taking into consideration the effect of corporate taxes. We find that it is not optimal to refund the bond as long as the corporate tax rate is less than 50 percent. We find that a significantly higher proportion of callable zero-coupon bonds, compared to noncallables, has restrictive financing covenants, suggesting that the call feature is included to provide flexibility at a low cost for future recapitalizations as the firm's investment opportunities change.

Capital markets perform two distinct functions: provision of capital and facilitation of good governance through information production and monitoring. I argue that the governance function has more impact on the efficiency with which resources are utilized within the firm. Based on industry-level data across 38 countries, I present evidence suggesting a positive relation between market-based governance and improvements in industry efficiency. The measures of governance are also positively correlated with productivity improvements and growth in real output. Furthermore, while governance affects efficiency, the capital provision services induce technological change. The evidence underscores the role of capital markets as a conduit of socially valuable governance services as distinct from capital provision.

The implications for portfolio behavior and asset prices of transaction costs are central to the analysis of numerous issues in economics. For example, questions involving the demand for the financial contracts issued by financial intermediaries are intimately tied to the existence of transaction costs. Thus the analysis of questions involving the nature of the demand for mutual fund shares, insurance contracts, mortgage loans, etc., and the form those contracts take require the explicit inclusion of transaction costs.

In this paper we study the economic value and statistical significance of asset return predictability, based on a wide range of commonly used predictive variables. We assess the performance of dynamic, unconditionally efficient strategies, first studied by Hansen and Richard (1987) and Ferson and Siegel (2001), using a test that has both an intuitive economic interpretation and known statistical properties. We find that using the lagged term spread, credit spread, and inflation significantly improves the risk-return trade-off. Our strategies consistently outperform efficient buy-and-hold strategies, both in and out of sample, and they also incur lower transactions costs than traditional conditionally efficient strategies.

Value and momentum returns and combinations of them across both countries and asset classes are explained by their loadings on global macroeconomic risk factors. These loadings describe why value and momentum have positive return premia, although being negatively correlated. The global macroeconomic risk factors also perform well in capturing the returns on other characteristic-based portfolios. The findings identify a global macroeconomic source of the common variation in returns across countries and asset classes.

It has long been recognized in the literature of finance that the robustness and analytical potential of mathematical programming procedures can be utilized to structure highly complex decision environments and to ascertain quickly and efficiently the dominant set(s) of actions for achieving an explicit objective(s). Although some formulations involve nonlinear relationships (for instance [13] [15]), the vast majority of the models appearing in the finance literature are variants of linear programming, including such identifiable methodologies as linear programming, goal programming, networks, integer programming, mixed integer programming, and chance-constrained programming. The decision processes for capital budgeting ([25] [1] [2] [4] [14] [16] [24]), working capital management ([20] [18] [21] [6]), cash management ([17] [23]), and portfolio selection ([22] [24]), have been structured as linear programs and have contributed significantly to understanding the dynamics of financial systems. Given the potential of these mathematical approaches, the limited industrial use of financial optimization models is disturbing.

We study the effects of accounting losses on chief executive officer (CEO) turnover. If accounting losses provide incremental information about managerial ability, boards can utilize the information in losses to assess CEOs’ stewardship of assets, which is why losses may serve as a heuristic for managerial failure. We find a positive relation between losses and subsequent CEO turnover after controlling for other accounting and stock-performance measures. We also find that losses are associated with an increase in board activity and that losses predict poor operating performance and future financial problems. Our results explain why CEOs manage earnings to avoid losses.

A growing literature documents that various strategies of rotating across equity styles generate significant returns. However, the conventional risk adjustment regression is problematic in evaluating the gains from style rotation. I propose a weight-based multifactor risk adjustment approach as a solution. When interpreted as a performance attribution procedure, this approach extends Sharpe's (1992) classic method by emphasizing factor loading rotation. I use a logit-based timing strategy to show that the conventional procedure produces misleading results and the new method leads to the opposite conclusion.

I develop two new types of portfolio efficiency when returns are predictable. The first type maximizes the unconditional Sharpe ratio of excess returns and differs from unconditional efficiency unless the safe asset return is constant over time. The second type maximizes conditional mean-variance preferences and differs from unconditional efficiency unless, additionally, the maximum conditional Sharpe ratio is constant. Using stock data, I quantify and test their performance differences with respect to unconditionally and fixed-weight efficient returns. I also show the relevance of the two new portfolio strategies to test conditional asset pricing models.

In recent years the expected-utility approach to decision making under risk has gained increasing acceptance among portfolio theorists. On the other hand, the mean-variance (MV) approach of Markowitz [13], which has dominated portfolio theory in the past, continues to enjoy great popularity. In MV theory, the investor is assumed to rank his preferences for risky returns solely in terms of their means and variances, with higher means and lower variances, being preferred. Tobin [20] showed that MV theory is consistent with expected utility theory in the special case of joint-normally distributed asset returns. The MV approach enjoys a ready acceptance among practitioners, and requires only modest informational and computational inputs. Perhaps its most attractive feature is its ability to decompose the overall portfolio problem into a sequence of much simpler problems: first, the “efficient” set of portfolios (which minimize variance for any given mean return) is calculated, and then the investor chooses one of the efficient portfolios in a manner consistent with his personal preferences. This efficient set is the same for all investors having the same mean-variance-covariance estimates of risky-asset returns, and can, in principle, be determined once and for all using parametric quadratic programming [12, 22] Despite these real advantages, the MV theory embodies certain problems of principle in the case of nonnormally distributed asset returns, and this fact has led to increasing emphasis on the presumably more rational expected-utility theory.

In a past issue of the Journal of Financial and Quantitative Analysis, Norstrπm [7] has presented a very simple sufficient condition for detecting whether a given pattern of cash flows over time has a unique nonnegative internal rate of return. Nor strum's condition is now widely cited in the literature and included in stock computer routines for analyses using the internal rate of return. See, e.g., de Faro [5] and Newnan [6].

In business research, firm size is both ubiquitous and readily measured. Complexity, another firm-related construct, is also relevant, but difficult to measure and not well-defined. As a result, complexity is less frequently incorporated in empirical designs. We argue that most extant measures of complexity are one-dimensional, have limited availability, and/or are frequently misspecified. Using both machine learning and an application-specific lexicon, we develop a text solution that uses widely available data and provides an omnibus measure of complexity. Our proposed measure, used in tandem with 10-K file size, provides a useful proxy that dominates traditional measures.

Firms with higher R&D intensity subsequently experience higher stock returns in international stock markets, highlighting the role of intangible investments in international asset pricing. The R&D effect is stronger in countries where growth option risk is more likely priced, but is unrelated to country characteristics representing market sentiments and limits-of-arbitrage. Moreover, we find that R&D intensity is associated with higher future operating performance, return volatility, and default likelihood. Our evidence suggests that the cross sectional relation between R&D intensity and stock returns is more likely attributable to risk premium than to mispricing.

This paper is a selective review of the received theory of financial institutions with some suggestions regarding future research on this topic. The major emphasis is placed on the positive economic theory of these firms. Financial institutions are considered to be firms that supply financial securities and contracts held as assets by other sectors of the economy and that use the proceeds of these sales to finance the purchase of financial securities and contracts which are the liabilities of other economic units. The theory discussed here is stripped of much of the regulatory and legal framework surrounding financial institutions. The primary reason for so limiting the scope of this paper is a conviction that a reasonably complete model of a simple financial institution is a necessary precursor to useful models of the positive economic behavior of financial institutions in any specific legal, regulatory, and operational framework. While recognizing that no tractable model of a financial institution is likely to be so general as to avoid the problem of model specificity, I take the view that many of the questions asked in the literature would be better answered in less specific models, i.e., in models capable of explaining additional important aspects of the behavior of the financial institution in question.

This article demonstrates that rating-based capital requirements, through their impact on insurers’ investment demand, affect corporate bond prices. Consistent with insurers’ low demand for investment-grade bonds with a rating close to noninvestment-grade, these bonds outperform. Consistent with insurers’ high (low) demand for investment-grade bonds with high (low) systematic risk exposure, these bonds underperform (outperform). Insurer demand, measured by insurer holdings, explains most of these pricing effects. We identify rating-based capital requirements as the driver of insurer demand, and thus the pricing effects, by showing that the effects do not exist before these requirements’ implementation in 1993.

In this paper I examine the likelihood of CEO stock option repricing and its alternatives: namely, option grant, stock grant, and “do nothing.” Multinomial logit results suggest that firms reprice options to increase sensitivity of pay to stock price and to temper down sensitivity of pay to volatility. Moreover, repricing firms are younger and more concentrated in industries where human capital is important. Finally, I find no evidence that internal governance or executive conflicts of interest are relevant in explaining repricing. My results indicate that repricing is motivated by incentive alignment and retention, and not by agency cost considerations.

The results obtained for accounts payable contrast with those for accounts receivable. With receivables, it appears that the level is determined more or less automatically by sales, linear trend, and season of the year. In the case of payables, it seems that trend and season are unimportant, and that the level of payables is determined instead by not only the level of purchases, but by capital requirements. Further, the current obligation on bank term-loans plays an important role in determining the response of payables to the need for working capital.

However, it was shown that fairly simple models are sufficient to account for most of the variance in accounts payable. Although it was anticipated that monetary variables would be significant for accounts payable, this was not borne out. As for accounts receivable, most of the variance in accounts payable for the Lumber and Wood Products Industry can be associated with microeconomic (i.e., industry variables) and time variables alone.

Several tentative conclusions concerning trade credit in the Lumber and Wood Products Industry may be listed:

1. Receivables can be accounted for almost entirely by sales, trend, or season.

2. Payables are not directly influenced by trend or season.

3. The direct influences of money supply and interest rates on accounts payable are not significant.

4. The effect of working capital on payables is adequately captured by treating current assets and current liabilities as separate independent variables.

5. The current obligation on long-term bank loans is more important in determining the level of payables than are short-term bank loans or the level of long-term debt.