[In this article, we derive an analytic expression for the representative agent of a large class of economies populated by agents with "catching up with the Joneses" preferences, but who exhibit heterogeneous risk aversion. As Chan and Kogan (2002) show numerically, the representative agent has stochastic risk that moves countercyclically to the state variable. However, we show that heterogeneity of risk aversion alone is insufficient for explaining empirical regularities—namely the variability of the Sharpe ratio—that Campbell and Cochrane (1999) obtain in a model of a representative agent with stochastic risk aversion.]

We examine the extent to which an investor's tastes and beliefs can be jointly recovered from knowledge of his/her consumption choice. More precisely, we assume that the investor's preferences admit an expected utility representation, but with subjective (unknown) probabilities, and investigate what joint restrictions can be placed on utility functions and beliefs. If the investor draws utility from intertemporal consumption, we show that the set of utility functions and beliefs that are consistent with a given consumption choice can be characterized by a martingale condition. In the Markovian case, this characterization can be restated in terms of a Riccati differential equation that must be satisfied by the investor's relative risk aversion function. To each solution of this differential equation is associated a unique utility function and a unique set of beliefs supporting the given consumption choice. Moreover, we show that the differential equation has at most one solution in the class of utility functions displaying infinite absolute risk aversion at the origin. Thus, preferences (and associated beliefs) can be uniquely recovered within this class.

We examine the extent to which an investor's tastes and beliefs can be jointly recovered from knowledge of his/her consumption choice. More precisely, we assume that the investor's preferences admit an expected utility representation, but with subjective (unknown) probabilities, and investigate what joint restrictions can be placed on utility functions and beliefs. If the investor draws utility from intertemporal consumption, we show that the set of utility functions and beliefs that are consistent with a given consumption choice can be characterized by a martingale condition. In the Markovian case, this characterization can be restated in terms of a Riccati differential equation that must be satisfied by the investor's relative risk aversion function. To each solution of this differential equation is associated a unique utility function and a unique set of beliefs supporting the given consumption choice. Moreover, we show that the differential equation has at most one solution in the class of utility functions displaying infinite absolute risk aversion at the origin. Thus, preferences (and associated beliefs) can be uniquely recovered within this class.

We provide a framework in which we link the valuation and asset allocation policies of defined benefits plans with the lifetime marginal productivity schedule of the worker and the pension plan formula. In turn, we examine the retirement policies that are implied by the primitives of the model and the value of pension obligations. Our model provides an explicit valuation formula for a stylized defined benefits plan. The optimal asset allocation policies consist of the replicating portfolio of the pension liabilities and the growth optimum portfolio independent of the pension liabilities. We show that the worker will retire when the ratio of pension benefits to current wages reaches a critical value which depends on the parameters of the pension plan and the discount rate. Using numerical techniques we analyze the feedback effect of retirement policies on the valuation of plans and on the asset allocation decisions.

[We introduce a model that captures the main properties that characterize employee stock options (ESO). We discuss the likelihood of early voluntary ESO exercise, and the obligation to exercise immediately if the employee leaves the firm, except if this happens before options are vested, in which case the options are forfeited. We derive an analytic formula for the price of the ESO and in a case study compare it to alternative methods.]

Investors delegating their wealth to privately informed managers face not only an intrinsic asymmetric information problem but also a potential misalignment in risk preferences. In this setting, we show that by tying fees symmetrically to the appropriate benchmark investors can tilt a fund portfolio toward their optimal risk exposure and realize nearly all the value of managers’ information. They attain these benefits despite an inherent inefficiency in the choice of the benchmark, and at no extra cost of compensating managers for exposure to relative-performance risk. Under certain conditions, benchmark-adjusted performance fees are necessary to prevent passive alternatives from dominating active management. Our results shed light on a recent debate on the appropriate fee structure of active funds in contexts of high competition from passive funds.

This paper introduces a Monte Carlo simulation method for pricing multidimensional American options based on the computation of the optimal exercise frontier. We consider Bermudan options that can be exercised at a finite number of times and compute the optimal exercise frontier recursively. We show that for every date of possible exercise, any single point of the optimal exercise frontier is a fixed point of a simple algorithm. Once the frontier is computed, we use plain vanilla Monte Carlo simulation to price the option and obtain a low-biased estimator. We illustrate the method with applications to several types of options.

We present an analytical solution for a pure exchange economy featuring a continuum of agents with disagreement, time-varying information quality, and reference-dependent preferences. Our general equilibrium model exhibits stationary dynamics. By examining the implications of the model, we find that the commonly studied asset pricing channels of disagreement have limited quantitative significance. On the other hand, variations in information quality, which affect disagreement levels, lead to substantial excess stock price volatility. This finding contributes significantly to explaining the equity premium and sheds light on empirical relationships between forecast dispersion and asset prices, the upward sloping real yield curve, and long-term yield movements.

Management companies assign some portfolio managers to run funds within a single investment objective (i.e., specialists), and others to run funds across several investment objectives (i.e., generalists). Our results show that funds achieve higher performance when they appoint superior pickers as specialists and market timers as generalists. We argue that these decisions are the result of a better match of manager mandates with the way information is collected and processed in each investment strategy. Overall our results are consistent with decision-making in fund families that add value to their investors by aiming to optimally assign or reassign portfolio managers.

In this article, we derive an analytic expression for the representative agent of a large class of economies populated by agents with “catching up with the Joneses” preferences, but who exhibit heterogeneous risk aversion. As Chan and Kogan (2002) show numerically, the representative agent has stochastic risk that moves countercyclically to the state variable. However, we show that heterogeneity of risk aversion alone is insufficient for explaining empirical regularities—namely the variability of the Sharpe ratio—that Campbell and Cochrane (1999) obtain in a model of a representative agent with stochastic risk aversion.