[HTML][HTML] Robust portfolio optimization: a categorized bibliographic review
Robust portfolio optimization refers to finding an asset allocation strategy whose behavior
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …
[图书][B] Moment and Polynomial Optimization
J Nie - 2023 - SIAM
Moment and polynomial optimization has received high attention in recent decades. It has
beautiful theory and efficient methods, as well as broad applications for various …
beautiful theory and efficient methods, as well as broad applications for various …
A survey of semidefinite programming approaches to the generalized problem of moments and their error analysis
The generalized problem of moments is a conic linear optimization problem over the convex
cone of positive Borel measures with given support. It has a large variety of applications …
cone of positive Borel measures with given support. It has a large variety of applications …
Utilizing dependence among variables in evolutionary algorithms for mixed-integer programming: A case study on multi-objective constrained portfolio optimization
Abstract Mixed-Integer Non-Linear Programming (MINLP) is not rare in real-world
applications such as portfolio investment. It has brought great challenges to optimization …
applications such as portfolio investment. It has brought great challenges to optimization …
Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphere
E de Klerk, M Laurent - Mathematical Programming, 2022 - Springer
We study the convergence rate of a hierarchy of upper bounds for polynomial minimization
problems, proposed by Lasserre (SIAM J Optim 21 (3): 864–885, 2011), for the special case …
problems, proposed by Lasserre (SIAM J Optim 21 (3): 864–885, 2011), for the special case …
Distributionally robust optimization with moment ambiguity sets
This paper studies distributionally robust optimization (DRO) when the ambiguity set is given
by moments for the distributions. The objective and constraints are given by polynomials in …
by moments for the distributions. The objective and constraints are given by polynomials in …
Improved convergence analysis of Lasserre's measure-based upper bounds for polynomial minimization on compact sets
We consider the problem of computing the minimum value f_\min, K f min, K of a polynomial f
over a compact set K ⊆ R^ n K⊆ R n, which can be reformulated as finding a probability …
over a compact set K ⊆ R^ n K⊆ R n, which can be reformulated as finding a probability …
Peak Value-at-Risk Estimation for Stochastic Differential Equations using Occupation Measures
This paper proposes an algorithm to upper-bound maximal quantile statistics of a state
function over the course of a Stochastic Differential Equation (SDE) system execution. This …
function over the course of a Stochastic Differential Equation (SDE) system execution. This …
A distributionally robust optimization model for batch nonlinear switched time-delay system considering uncertain output measurements
In this paper, we consider a nonlinear switched time-delay (NSTD) system with unknown
switching times and unknown system parameters, where the output measurement is …
switching times and unknown system parameters, where the output measurement is …
Risk-averse stochastic programming: Time consistency and optimal stopping
This paper addresses time consistency of risk-averse optimal stopping in stochastic
optimization. It is demonstrated that time-consistent optimal stopping entails a specific …
optimization. It is demonstrated that time-consistent optimal stopping entails a specific …