Dashan Huang

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In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrated into linear programs which can be efficiently solved.(More)
In this paper we provide a survey of recent contributions to robust portfolio strategies from operations research and finance to the theory of portfolio selection. Our survey covers results derived not only in terms of the standard mean-variance objective, but also in terms of two of the most popular risk measures, mean-VaR and mean-CVaR developed recently.(More)
Robust optimization, one of the most popular topics in the field of optimization and control since the late 1990s, deals with an optimization problem involving uncertain parameters. In this paper, we consider the relative robust conditional value-at-risk portfolio selection problem where the underlying probability distribution of portfolio return is only(More)
In this paper we consider the robust portfolio selection problem involving two types of uncertainties; the uncertainty in the distribution of exit time and the uncertainty in the distribution of portfolio return conditional on exit time. To deal with these uncertainties, we propose a tractable approach by applying worst-case VaR strategy to the case where(More)
In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrated into linear programs which can be efficiently solved.(More)
This paper investigates whether the degree of predictability can be explained by existing asset pricing models, and provides two theoretical upper bounds on the R-square of the regression of stock returns on predictors for given classes of models of interest. Empirically, we find that the predictive R-square is significantly larger than the upper bounds(More)
We develop a new approach for estimating mutual fund performance that controls for both factor model betas and stock characteristics in one measure. Our double adjustment procedure shows that fund returns are significantly related to stock characteristics in the cross section after controlling for risk via factor models. Compared to standard mutual fund(More)
This paper presents a model for optimally designing a collateralized mortgage obligation (CMO) with a planned amortization class (PAC)-companion structure using dynamic cash reserve. In this structure, the mortgage pool’s cash flow is allocated by rule to the two bond classes such that PAC bondholders receive substantial prepayment protection, that(More)