The value and cost of more stages in stochastic programing: a statistical analysis on a set of portfolio choice problems

DOI10.1080/14697688.2021.1993620zbMath1484.91415OpenAlexW3216043171MaRDI QIDQ5068072

Jonas Ekblom, John R. Birge, Jörgen Blomvall

Publication date: 5 April 2022

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2021.1993620

zbMATH Keywords

portfolio choicesample average approximationmulti-stage stochastic programmingscenario trees

Mathematics Subject Classification ID

Stochastic programming (90C15) Portfolio theory (91G10)

Cites Work

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• Generating Scenario Trees for Multistage Decision Problems
• Optimum consumption and portfolio rules in a continuous-time model
• Bounds in multistage linear stochastic programming
• A stochastic multi-stage fixed charge transportation problem: worst-case analysis of the rolling horizon approach
• On the number of stages in multistage stochastic programs
• Monte Carlo bounding techniques for determinig solution quality in stochastic programs
• Scenario reduction in stochastic programming
• The performance of stochastic dynamic and fixed mix portfolio models
• Models for planning capacity expansion of convenience stores under uncertain demand and the value of information
• Importance sampling in stochastic optimization: an application to intertemporal portfolio choice
• A dynamic stochastic programming model for international portfolio management
• Solving multistage asset investment problems by the sample average approximation method
• The empirical behavior of sampling methods for stochastic programming
• The value of the stochastic solution in multistage problems
• The Sample Average Approximation Method for Stochastic Discrete Optimization
• The value of the stochastic solution in stochastic linear programs with fixed recourse
• An Adaptive Dynamic Programming Algorithm for Dynamic Fleet Management, I: Single Period Travel Times
• Monte Carlo sampling approach to stochastic programming
• Comparison of Sampling Methods for Dynamic Stochastic Programming
• Risk Aversion in the Small and in the Large
• Scenario tree generation for multiperiod financial optimization of optimal discretization
• Scenario generation and stochastic programming models for asset liability management

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