We study the effects of imposing repeated short-horizon regulatory constraints on long-term investors. We show that Value-at-Risk and Expected Shortfall constraints, when imposed dynamically, lead to similar optimal portfolios and wealth distributions. We also show that, in utility terms, the costs of imposing these constraints can be sizeable. For a 96% funded pension plan, both an annual Value-at-Risk constraint and an annual Expected Shortfall constraint can lead to an economic cost of about 2.5–3.8% of initial wealth over a 15-year horizon.

This paper presents an alternative method to derive the limiting distribution of residual-based statistics. Our method does not impose an explicit assumption of (asymptotic) smoothness of the statistic of interest with respect to the model's parameters and thus is especially useful in cases where such smoothness is difficult to establish. Instead, we use a locally uniform convergence in distribution condition, which is automatically satisfied by residual-based specification test statistics. To illustrate, we derive the limiting distribution of a new functional form specification test for discrete choice models, as well as a runs-based tests for conditional symmetry in dynamic volatility models.

[We study the importance of time-varying bond risk premia in a consumption and portfoliochoice problem for a life-cycle investor facing short-sales and borrowing constraints. Tilts in the optimal asset allocation in response to changes in bond risk premia exhibit pronounced life-cycle patterns. We find that the investor is willing to pay an annual fee up to 1% to implement a strategy that optimally conditions on prevailing bond risk premia in addition to her age and wealth. To solve our model, we extend recently developed simulation-based techniques to life-cycle problems featuring multiple state variables and multiple risky assets.]

This paper studies the life-cycle consumption and portfolio choice problem taking account of annuity risk at retirement. The study allows for government-provided annuity income. Optimally, households allocate retirement wealth to nominal, inflation-linked and variable annuities, and condition this choice on the state of the economy. The case in which there are limitations in the types of annuities that are available is also considered and the costs of annuity market incompleteness are quantified. Subsequently, the paper determines how investors optimally anticipate annuitization before retirement. The conclusion is that ignoring annuity risk before and at retirement can be economically costly.

We study the importance of time-varying bond risk premia in a consumption and portfolio-choice problem for a life-cycle investor facing short-sales and borrowing constraints. Tilts in the optimal asset allocation in response to changes in bond risk premia exhibit pronounced life-cycle patterns. We find that the investor is willing to pay an annual fee up to 1% to implement a strategy that optimally conditions on prevailing bond risk premia in addition to her age and wealth. To solve our model, we extend recently developed simulation-based techniques to life-cycle problems featuring multiple state variables and multiple risky assets. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: [email protected], Oxford University Press.

We test whether hedging currency risk improves the performance of international stock portfolios.We show that an auxiliary regression provides a wealth of information about the optimal portfolio holdings for non-mean–variance investors, analogous to the information provided by the Jensen regression about optimal portfolio holdings for the mean–variance case. We find that static hedging with currency forwards does not lead to significant improvements in portfolio performance for a US-Dollar based stock portfolio from the G5 countries, whereas dynamic hedges that are conditional on the interest rate spread do. These conclusions hold for both mean–variance and power utility investors and show up both in-sample and out-of-sample. However, the optimal forward positions can differ significantly for both types of investors.

We solve a flexible model that captures transactions costs and infrequencies of trading opportunities for illiquid assets to better understand the shadow costs of illiquidity for different origins of asset illiquidity and heterogeneous investor types. We show that illiquidity that results in suboptimal asset allocation carries low shadow costs, whereas these costs are high when illiquidity restricts consumption. As a result, the shadow costs are high for short-term investors, investors who face substantial liquidity shocks, and investors who desire to allocate a large fraction of their wealth to illiquid assets.

We propose regression‐based tests for mean‐variance spanning in the case where investors face market frictions such as short sales constraints and transaction costs. We test whether U.S. investors can extend their efficient set by investing in emerging markets when accounting for such frictions. For the period after the major liberalizations in the emerging markets, we find strong evidence for diversification benefits when market frictions are excluded, but this evidence disappears when investors face short sales constraints or small transaction costs. Although simulations suggest that there is a possible small‐sample bias, this bias appears to be too small to affect our conclusions.

This paper investigates the effect of closed overnight exchanges on option prices. During the trading day, asset prices follow the literature's standard affine model that allows for stochastic volatility and random jumps. Independently, the overnight asset price process is modeled by a single jump. We find that the overnight component reduces the variation in the random jump process significantly. However, neither the random jumps nor the overnight jumps alone are able to empirically describe all features of option prices. We conclude that both random jumps during the day and overnight jumps are important in explaining option prices, where the latter account for about one quarter of total jump risk.