A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability

We present a simulation-based method for solving discrete-time portfolio choice problems involving non-standard preferences, a large number of assets with arbitrary return distribution, and, most importantly, a large number of state variables with potentially path-dependent or non-stationary dynamics. The method is flexible enough to accommodate intermediate consumption, portfolio constraints, parameter and model uncertainty, and learning. We first establish the properties of the method for the portfolio choice between a stock index and cash when the stock returns are either iid or predictable by the dividend yield. We then explore the problem of an investor who takes into account the predictability of returns but is uncertain about the parameters of the data generating process. The investor chooses the portfolio anticipating that future data realizations will contain useful information to learn about the true parameter values.

The Term Structure of the Risk-Return Tradeoff

Recent research in empirical finance has documented that expected excess returns on bonds and stocks, real interest rates, and risk shift over time in predictable ways. Furthermore, these shifts tend to persist over long periods of time. In this paper we propose an empirical model that is able to capture these complex dynamics, yet is simple to apply in practice, and we explore its implications for asset allocation. Changes in investment opportunities can alter the risk-return tradeoff of bonds, stocks, and cash across investment horizons, thus creating a ``term structure of the risk-return tradeoff.'' We show how to extract this term structure from our parsimonious model of return dynamics, and illustrate our approach using data from the U.S. stock and bond markets. We find that asset return predictability has important effects on the variance and correlation structure of returns on stocks, bonds and T-bills across investment horizons.

Dynamic Portfolio Selection by Augmenting the Asset Space

We present a novel approach to dynamic portfolio selection that is no more difficult to implement than the static Markowitz model. The idea is to expand the asset space to include simple (mechanically) managed portfolios and compute the optimal static portfolio in this extended asset space. The intuition is that a static choice among managed portfolios is equivalent to a dynamic strategy. We consider managed portfolios of two types: "conditional" and "timing" portfolios. Conditional portfolios are constructed along the lines of Hansen and Richard (1987). For each variable that affects the distribution of returns and for each basis asset, we include a portfolio that invests in the basis asset an amount proportional to the level of the conditioning variable. Timing portfolios invest in each basis asset for a single period and therefore mimic strategies that buy and sell the asset through time. We apply our method to a problem of dynamic asset allocation across stocks, bonds, and cash using the predictive ability of four conditioning variables.

Mean-Variance Policy for Discrete-time Cone Constrained Markets: The Consistency in Efficiency and Minimum-Variance Signed Supermartingale Measure

The discrete-time mean-variance portfolio selection formulation, a representative of general dynamic mean-risk portfolio selection problems, does not satisfy time consistency in efficiency (TCIE) in general, i.e., a truncated pre-committed efficient policy may become inefficient when considering the corresponding truncated problem, thus stimulating investors' irrational investment behavior. We investigate analytically effects of portfolio constraints on time consistency of efficiency for convex cone constrained markets. More specifically, we derive the semi-analytical expressions for the pre-committed efficient mean-variance policy and the minimum-variance signed supermartingale measure (VSSM) and reveal their close relationship. Our analysis shows that the pre-committed discrete-time efficient mean-variance policy satisfies TCIE if and only if the conditional expectation of VSSM's density (with respect to the original probability measure) is nonnegative, or once the conditional expectation becomes negative, it remains at the same negative value until the terminal time. Our findings indicate that the property of time consistency in efficiency only depends on the basic market setting, including portfolio constraints, and this fact motivates us to establish a general solution framework in constructing TCIE dynamic portfolio selection problem formulations by introducing suitable portfolio constraints

Modelling Realized Covariances

This paper proposes a new dynamic model of realized covariance (RCOV) matrices based on recent work in time-varying Wishart distributions. The specifications can be linked to returns for a joint multivariate model of returns and covariance dynamics that is both easy to estimate and forecast. Realized covariance matrices are constructed for 5 stocks using high-frequency intraday prices based on positive semi-definite realized kernel estimates. We extend the model to capture the strong persistence properties in RCOV. Out-of-sample performance based on statistical and economic metrics show the importance of this. We discuss which features of the model are necessary to provide improvements over a traditional multivariate GARCH model that only uses daily returns.eigenvalues, dynamic conditional correlation, predictive likelihoods, MCMC

Parametric Immunization in Bond Portfolio Management

In this paper, we evaluate the relative immunization performance of the multifactor parametric interest rate risk model based on the Nelson-Siegel-Svensson specification of the yield curve with that of standard benchmark investment strategies, using European Central Bank yield curve data in the period between January 3, 2005 and December 31, 2011. In addition, we examine the role of portfolio design in the success of immunization strategies, particularly the role of the maturity bond. Considering multiperiod tests, the goal is to assess, in a highly volatile interest rate period, whether the use of the multifactor parametric immunization model contributes to improve immunization performance when compared to traditional single-factor duration strategies and whether durationmatching portfolios constrained to include a bond maturing near the end of the holding period prove to be an appropriate immunization strategy. Empirical results show that: (i) immunization models (single- and multi-factor) remove most of the interest rate risk underlying a naïve or maturity strategy; (ii) duration-matching portfolios constrained to include the maturity bond and formed using a single-factor model outperform the traditional duration-matching portfolio set up using a ladder portfolio and provide appropriate protection against interest rate risk; (iii) the multifactor parametric model outperforms all the other non-duration and duration-matching strategies, behaving almost like a perfect immunization asset; (iv) these results are consistent to changes in the rebalancing frequency of bond portfolios

Multiple Risky Assets, Transaction Costs and Return Predictability: Implications for Portfolio Choice

Our paper contributes to the dynamic portfolio choice and transaction cost literatures by considering a multiperiod CRRA individual who faces transaction costs and who has access to multiple risky assets, all with predictable returns. We numerically solve the individual’s multiperiod problem in the presence of transaction costs and predictability. In particular, we characterize the investor’s optimal portfolio choice with proportional and fixed transaction costs, and with return predictability similar to that observed for the U.S. stock market. We also perform some comparative statics to better understand the nature of the no-trade region with more than one risky asset. Throughout our focus is on the case with two risky assets. We also perform some utility comparisons. The calibration exercise reveals some interesting results about the relative attractiveness of the three equity portfolios calibrated