The mean-risk stochastic mixed-integer programs can better model complex decision problems under uncertainty than usual stochastic (integer) programming models. In order to derive theoretical results in a numerically tractable way, the contamination technique is adopted in this paper for the...

The mean-risk stochastic mixed-integer programs can better model complex decision problems under uncertainty than usual stochastic (integer) programming models. In order to derive theoretical results in a numerically tractable way, the contamination technique is adopted in this paper for the...

We propose a new class of risk measures which satisfy convexity and monotonicity, two well-accepted axioms a reasonable and realistic risk measure should satisfy. Through a nonlinear weight function, the new measure can flexibly reflect the investor's degree of risk aversion, and can control the...

For our introduced mixed-integer quadratic stochastic program with fixed recourse matrices, random recourse costs, technology matrix and right-hand sides, we study quantitative stability properties of its optimal value function and optimal solution set when the underlying probability...

In this paper, an optical analysis on the end loss effect of parabolic trough solar collector (PTC) with horizontal north–south axis (PTC-HNSA) is performed, and a method to compensate its end loss effect is presented. The calculation formulae for the optical end loss ratio and the increased...

General multiperiod optimal consumption and investment problems with proportional transaction costs are investigated in this paper, a <Emphasis Type="Bold">GARCH-type process is used to model the risky asset’s return series so that its time-varying moments and conditional heteroskedasticity can be properly...</emphasis>

The optimal investment policy for a standard multi-period mean–variance model is not time-consistent because the variance operator is not separable in the sense of the dynamic programming principle. With a nested conditional expectation mapping, we develop an investment model with time...

A Poisson process with stochastic intensity is utilized to model changes of a benchmark interest rate set by a Central Bank. We propose explicit formulas for estimators of parameters and the expectation of the intensity, based on observations of the process. Through comparing the intensity and...

Aimed at better modeling stock returns and finding robustly optimal investment decisions, a new portfolio selection model is proposed in this paper. The model differs from existing ones in following ways: multiple market frictions are taken into account simultaneously; the adopted multivariate...

The data envelopment analysis (DEA) method is a mathematical programming approach to evaluate the relative performance of portfolios. Considering that the risk input indicators of existing DEA performance evaluation indices cannot reflect the pervasive fat tails and asymmetry in return...