[This paper derives and analyzes dynamic timing strategies of a fund manager with private information. Endogenous timing strategies generated by various information structures and skills, and associated fund styles, are identified. Endogenous fund returns are characterized in the public information of an uninformed observer. Timing components are identified. The paper provides foundations for regression analyses of fund returns and tests of market timing.]

[A new decomposition of the optimal portfolio, in dynamic models with von Neumann-Morgenstern preferences and Ito prices, is established. The formula rests on a change of numéraire that uses pure discount bonds as units of account. The dynamic hedging demand has two components. The first hedge insures against fluctuations in an optimally designed bond with a maturity date matching the investor's horizon. The second hedge immunizes against fluctuations in the market price of risk in the bond numéraire. Various applications are examined. New results concerning the behavior of extremely risk-averse individuals, the demand for bonds and its long-horizon limit, and the optimal portfolio in incomplete marles are derived.]

This paper derives and analyzes dynamic timing strategies of a fund manager with private information. Endogenous timing strategies generated by various information structures and skills, and associated fund styles, are identified. Endogenous fund returns are characterized in the public information of an uninformed observer. Timing components are identified. The paper provides foundations for regression analyses of fund returns and tests of market timing.

A new decomposition of the optimal portfolio, in dynamic models with von Neumann–Morgenstern preferences and Ito prices, is established. The formula rests on a change of numéraire that uses pure discount bonds as units of account. The dynamic hedging demand has two components. The first hedge insures against fluctuations in an optimally designed bond with a maturity date matching the investor's horizon. The second hedge immunizes against fluctuations in the market price of risk in the bond numéraire. Various applications are examined. New results concerning the behavior of extremely risk-averse individuals, the demand for bonds and its long-horizon limit, and the optimal portfolio in incomplete markets are derived.

This paper compares two recent Monte Carlo methods advocated for the computation of optimal portfolio rules. The candidate methods are the approach based on Monte Carlo with Malliavin Derivatives (MCMD) proposed by Detemple, Garcia and Rindisbacher [Detemple et al., 2003. A Monte-Carlo method for optimal portfolios. Journal of Finance 58, 401–406] and the approach based on Monte Carlo with regression (MCR) of Brandt, Goyal, Santa-Clara and Stroud [Brandt et al., 2003. A simulation approach to dynamic portfolio choice with an application to learning about return predictability. Working paper, Wharton School]. Our comparisons are carried out in the context of various intertemporal portfolio choice problems with two assets, a risky asset and a riskless asset, and different configurations of the state variables. The specifications studied include a linear model with a single state variable admitting an exact solution and a non-linear model with two state variables that requires a purely numerical resolution. The accuracies of the candidate methods are compared. We provide, in particular, efficiency plots displaying the speed–accuracy trade-off for various selections of the relevant simulation and discretization parameters. MCMD is shown to dominate in all the settings considered.

This paper proposes a new simulation‐based approach for optimal portfolio allocation in realistic environments with complex dynamics for the state variables and large numbers of factors and assets. A first illustration involves a choice between equity and cash with nonlinear interest rate and market price of risk dynamics. Intertemporal hedging demands significantly increase the demand for stocks and exhibit low volatility. We then analyze settings where stock returns are also predicted by dividend yields and where investors have wealth‐dependent relative risk aversion. Large‐scale problems with many assets, including the Nasdaq, SP500, bonds, and cash, are also examined.

This paper studies equilibrium in a pure exchange economy with unobservable Markov switching growth regimes and beliefs-dependent risk aversion (BDRA). Risk aversion is stochastic and depends nonlinearly on consumption and beliefs. Equilibrium is obtained in closed form. The market price of risk, the interest rate, and the stock return volatility acquire new components tied to fluctuations in beliefs. A three-regime specification is estimated using the generalized method of moments (GMM). Model moments match their empirical counterparts for a variety of unconditional moments, including the equity premium, stock returns volatility, and the correlations between stock returns and consumption and dividends. Dynamic features of the data, such as the countercyclical behaviors of the equity premium and volatility, are also captured. Model volatility provides a good fit for realized volatility. A new factor, the information risk premium, is found to be a strong predictor of future excess returns. These results are obtained with an estimated risk aversion fluctuating between 1.44 and 1.93.

The representative-agent Lucas model stresses aggregate risk and hence does not allow us to study the impact of agents’ heterogeneity on the dynamics of equilibrium trading volume. In this paper, we investigate under what conditions non-informational heterogeneity, i.e., differences in preferences and endowments, leads to nontrivial trading volume in equilibrium. We present a non-informational no-trade theorem that provides necessary and sufficient conditions for zero equilibrium trading volume in a continuous-time Lucas market model with heterogeneous agents, multiple goods, and multiple securities. We explain in detail how no-trade equilibria are related to autarky equilibria, portfolio autarky equilibria, and peculiar financial market equilibria, which play an important role in the literature on international risk sharing.

We study equilibria in multi‐asset and multi‐agent continuous‐time economies with asymmetric information and bounded rational noise traders. We establish the existence of two equilibria. First, a full communication equilibrium where the informed agents' signal is disclosed to the market and static policies are optimal. Second, a partial communication equilibrium where the signal disclosed is affine in the informed and noise traders' signals, and dynamic policies are optimal. Here, information asymmetry creates demand for two public funds, as well as a dark pool where private information trades can be implemented. Markets are endogenously complete and equilibrium returns have a three factor structure with stochastic factors and loadings. Results are valid for constant absolute risk averse investors, general vector diffusions for fundamentals, nonlinear terminal payoffs, and non‐Gaussian noise trading. Asset price dynamics and public information flows are endogenous, and rational expectations equilibria are special cases of the general results.