EVIDENCE ON THE COMPENSATION OF PORTFOLIO MANAGERS

We surveyed 396 portfolio managers about the structure of their compensation. Overall, more compensation packages are subjective/discretionary than objective/formula based. Firm success factors such as firm profitability have more effect on bonuses than do client success factors such as investment performance. Differences in the structure of compensation across firms, clients, job types, and manager characteristics reflect likely differences in the underlying contracting environments, especially differences in the difficulty of monitoring performance and exerting control.     

APPLICABILITY OF THE FAMA‐FRENCH THREE‐FACTOR MODEL IN FORECASTING PORTFOLIO RETURNS

For the model‐based estimation of the equity cost of capital, evidence shows that the common practice of using the average historical factor premiums as the estimates of the next‐period factor premiums generates inaccurate estimates. I propose an alternative way to estimate factor premiums by using the structural variables that are important predictors of future asset returns. Based on the out‐of‐sample results from a trading strategy with four in‐sample model‐selection criteria, I find that my estimation procedure performs better than the common practice even when transaction costs are considered.     

ROBUSTNESS OF THE HEADQUARTERS‐CITY EFFECT ON STOCK RETURNS

Recent studies report that U.S. firms headquartered near each other experience positive comovement in their stock returns, a finding suggestive of local biases in equity trading activity. We investigate the robustness of these findings and find that including additional pricing factors in models for monthly stock returns materially reduces the magnitude of the headquarters‐city effect in stock returns. Additionally, we find that an implicit null hypothesis of zero local return comovement is inappropriate as there is positive comovement between a stock's return and returns on portfolios of stocks from nonheadquarters cities, on average. Nevertheless, results benchmarked against estimates based on resampling methods indicate a significant and robust headquarters‐city effect in stock returns.     

EXPECTED VOLATILITY,UNEXPECTED VOLATILITY,AND THE CROSS‐SECTION OF STOCK RETURNS

The existing literature finds conflicting results on the cross‐sectional relation between expected returns and idiosyncratic volatility. We contend that at the firm level, the sample correlation between unexpected returns and expected idiosyncratic volatility can cloud the true relation between the expected return and expected idiosyncratic volatility. We show strong evidence that unexpected idiosyncratic volatility is positively related to unexpected returns. Using unexpected idiosyncratic volatility to control for unexpected returns, we find expected idiosyncratic volatility to be significantly and positively related to expected returns. This result holds after controlling for various firm characteristics, and it is robust across different sample periods.     

PORTFOLIO OPTIMIZATION UNDER TRACKING ERROR AND WEIGHTS CONSTRAINTS

The performance of active portfolio managers who must comply with a weights constraint is often assessed against a benchmark. The weights constraint is common as the funds are committed by their own prospectus to a minimum (or maximum) portfolio concentration. We characterize the optimal asset allocation and analyze the implications of the weights constraint on the manager's performance and on the relevance of the information ratio. We obtain that because of the weights constraint, at the optimum, the information ratio often decreases when the manager is free to deviate more from the benchmark.     

KNOW YOUR CLIENT! INVESTOR PROFILE AND TAILOR‐MADE ASSET ALLOCATION RECOMMENDATIONS

We study how the investor profile influences the asset allocation recommendations of professional advisors. We find the investor's perceived risk attitude influences more the mix of risky assets, whereas the socioeconomic variables influence more the cash percentage. The recommendations are consistent with a diversification behavior driven by actual asset correlations. These findings support the utility of investor advisory that may help enhance the risk and return trade‐off. The main drawback of the recommendations may consist in the degree of customization that is limited by the small number of investor characteristics actually influencing the asset allocation.     

ESTIMATING EXPECTED EXCESS RETURNS USING HISTORICAL AND OPTION‐IMPLIED VOLATILITY

We test the relation between expected and realized excess returns for the S&P 500 index from January 1994 through December 2003 using the proportional reward‐to‐risk measure to estimate expected returns. When risk is measured by historical volatility, we find no relation between expected and realized excess returns. In contrast, when risk is measured by option‐implied volatility, we find a positive and significant relation between expected and realized excess returns in the 1994–1998 subperiod. In the 1999–2003 subperiod, the option‐implied volatility risk measure yields a positive, but statistically insignificant, risk‐return relation. We attribute this performance difference to the fact that, in the 1994–1998 subperiod, return volatility was lower and the average return was much higher than in the 1999–2003 subperiod, thereby increasing the signal‐to‐noise ratio in the latter subperiod.     

THE FAMA‐FRENCH MODEL,LEVERAGE, AND THE MODIGLIANI‐MILLER PROPOSITIONS

For a cost‐of‐equity model to conform to the Modigliani‐Miller cost‐of‐capital propositions, any sensitivity coefficients in the model must be related to the firm's leverage. In this paper I apply these principles to the Fama‐French model for the cost of equity and develop the relation between its sensitivity coefficients and firm leverage. I then examine an empirical process developed by Fama and French (1997) to model the evolution through time of their sensitivity coefficients and show that this empirical process is inconsistent with the Modigliani‐Miller propositions. Separable functions are proposed for these sensitivity coefficients that are consistent with the Modigliani‐Miller propositions.     

THE GRAMM‐LEACH‐BLILEY ACT OF 1999: RISK IMPLICATIONS FOR THE FINANCIAL SERVICES INDUSTRY

We document significant risk changes in the financial services industry following the passage of the Gramm‐Leach‐Bliley Act of 1999. Banks experience an increase in risk regardless of whether they have taken steps to participate actively in the investment banking business. Insurance companies also experience an increase in risk, whereas securities firms experience a decrease in risk. We attribute the increase in risk for banks and insurance companies to the fact that the securities business is relatively more risky, and the decline in risk for securities firms to the fact that they can now diversify into relatively less risky banking and insurance businesses.     

IS THE BOOK‐TO‐MARKET RATIO A MEASURE OF RISK?

We develop a leverage‐based alternative to traditional asset pricing models to investigate whether the book‐to‐market ratio acts as a proxy for risk. We argue that the book‐to‐market ratio should act as a proxy because of the expected relations between (1) financial risk and measures of capital structure based on the market value of equity and (2) asset risk and measures of capital structure based on the book value of equity. We find no relation between average stock returns and the book‐to‐market ratio in all‐equity firms after controlling for firm size, and an inverse relation between average stock returns and the book‐to‐market ratio in firms with a negative book value of equity.     

Optimal Mortgage Refinancing: A Closed‐Form Solution

We derive the first closed‐form optimal refinancing rule: refinance when the current mortgage interest rate falls below the original rate by at least In this formula W(.) is (the principal branch of) the Lambert W‐function, where ρ is the real discount rate, λ is the expected real rate of exogenous mortgage repayment, σ is the standard deviation of the mortgage rate, is the ratio of the tax‐adjusted refinancing cost and the remaining mortgage value, and τ is the marginal tax rate. This expression is derived by solving a tractable class of refinancing problems. Our quantitative results closely match those reported by researchers using numerical methods.     

THE INFLUENCE OF FIRM‐ AND CEO‐SPECIFIC CHARACTERISTICS ON THE USE OF NONLINEAR DERIVATIVE INSTRUMENTS

We examine why firms use nonlinear derivatives (e.g., options). Our results suggest that option characteristics in investment opportunities and debt, the payoff structure of incentive compensation, and free cash‐flow agency problems influence the firm's choice. Investment opportunities, internally generated cash flow, business risk, and option compensation positively influence the use of nonlinear currency derivatives. Option feature in bonds positively influence the use of nonlinear interest rate derivatives, whereas bonus and stock compensation, and CEO tenure have a negative influence. In sum, nonlinear cash flow characteristics in investment opportunity, debt, and executive compensation all relate positively to nonlinear derivative usage.     

DAY‐END EFFECT ON THE PARIS BOURSE

We study the day‐end effect on the Paris Bourse, a computerized order‐driven market with competing dealers. The day‐end return is approximately double the magnitude found in U.S. data and is nearly four times larger for stocks trading with a registered dealer. However, this is largely explained by the time between trades and the bid‐ask spread. Unlike the U.S. data, the effect does not decline as stock price increases, probably because of a variable tick size in the Paris market. Finally, a change to a closing call auction in May 1996 for a subset of stocks did not reduce the day‐end effect.     

SOCIALLY RESPONSIBLE INVESTING AND PORTFOLIO DIVERSIFICATION

I use a sample of socially responsible stock mutual funds matched to randomly selected conventional funds of similar net assets to investigate differences in characteristics of assets held, portfolio diversification, and variable effects of diversification on investment performance. I find that socially responsible funds do not differ significantly from conventional funds in terms of any of these attributes. Moreover, the effect of diversification on investment performance is not different between the two groups. Both groups underperform the Domini 400 Social Index and S&P 500 during the study period.     

Determinants of Investor Demand for Cross‐Listed Firms

By focusing on the decisions of investors to invest in cross‐listed stocks, this paper presents new evidence on why we observe striking differences in the percentage of trade in foreign markets for cross‐listed stocks. With a large sample of Toronto Stock Exchange (TSX) stocks cross‐listed in the U.S. and Canada, we document the effect of investor recognition and risk characteristics on the distribution of trading volume. Firms that are more visible to American investors are traded more heavily in the U.S. At the same time, firms that offer diverse risk characteristics are attractive to Americans. While investors understand the benefits of international diversification, as they are attracted to stocks that are different (e.g., the stock of small firms with few assets in the U.S.), they also seek stocks that provide them with high returns.     

THE PRICING OF EQUITY CARVE‐OUTS DURING THE 1990s

We examine the level of underpricing and characteristics of equity carveouts (ECOs) from 1990 to 1998 (the 1990s) and from 1999 to 2000 (the bubble period). For a sample of 458 ECOs, we find a mean initial return of 8.75% for the 1990s and 47.76% for the bubble period. The results suggest that, similar to other initial public offerings (IPOs), ECOs have been more willing to accept underpricing through time because of an increased importance in analyst coverage and the increased use of spinning, the practice where investment bankers allocate IPOs to high‐profile customers to garner potential future business.     

ON THE ROBUSTNESS OF RANGE‐BASED VOLATILITY ESTIMATORS

We empirically examine Parkinson's range‐based volatility estimate in the federal funds market, which is unique because institutional regulations create a predictable pattern in interday volatility. We find that range‐based volatility estimates and standard deviations produce the expected volatility pattern. We also find that at trading pressure points where microstructure noise should be greatest, range‐based estimates are less than the standard deviations. Thus, we support the argument that range‐based volatility estimates remove the upward bias created by microstructure noise. We find that the Parkinson method is the most efficient range‐based volatility measure among a set of alternates in this market.     

“Hot Hands” in bond funds

We investigate persistence in the relative performance of 3549 bond mutual funds from 1990 to 2003. We show that bond funds that display strong (weak) performance over a past period continue to do so in future periods. The out-of-sample difference in risk-adjusted return between the top and bottom decile of funds ranked on past alpha exceeds 3.5 percent per year. We demonstrate that a strategy based on past fund returns earns an economically and statistically significant abnormal return, suggesting that bond fund investors can exploit the observed persistence. Our results are robust to a wide range of model specifications and bootstrapped test statistics.     

THE ECONOMIC GAINS OF TRADING STOCKS AROUND HOLIDAYS

I assess the economic gains of strategies that account for the effect of holiday calendar effects on the daily returns and volatility of the 30 stocks in the Dow Jones Industrial Average index. The dynamic strategies use forecasts from stochastic volatility models that distinguish between regular trading days and different types of holidays. More important, I assess the economic value of conditioning on holiday effects and find that a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy that does not account for the effect of holidays on daily conditional expected returns and volatility to a strategy that does. This result is robust to reasonable transaction costs.     

“KLICing” there and back again: Portfolio selection using the empirical likelihood divergence and Hellinger distance

Stutzer (2000, 2003) proposes the decay-rate maximizing portfolio selection rule wherein the investor selects the asset mix that maximizes the rate at which the probability of shortfall decays to zero. A close examination of this rule reveals that it ranks portfolios by computing the divergence, in the Kullback-Leibler sense, between the unweighted portfolio return distribution and a tilted distribution meaned at the predetermined target or benchmark rate of return selected by or imposed upon the investor. This result implies, in the IID case, that Stutzer's rules can be written as a benchmark constrained Kullback-Leibler-based optimization problem with an endogenous utility interpretation. Here we expand on this idea by introducing two closely related portfolio selection rules based on the empirical likelihood divergence and the Hellinger-Matusita distance. The first of these is the reversed Kullback-Leibler divergence and the second is proportional to the average of the two divergences. The theoretical and in-sample properties of the new criteria suggest them to be competitive with and in some cases better than existing methods, especially in terms of skewness preference.