Scenario tree generation approaches using K-means and LP moment matching methods

DOI10.1016/j.cam.2012.05.020zbMath1245.05106OpenAlexW2095283796MaRDI QIDQ442753

Zhiping Chen, Daobao Xu, Li Yang

Publication date: 3 August 2012

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2012.05.020

zbMATH Keywords

simulationscenario treemoment matchingMGARCHK-means clusteringLP

Mathematics Subject Classification ID

Linear programming (90C05) Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.) (05C70)

Related Items (12)

A copula-based scenario tree generation algorithm for multiperiod portfolio selection problems ⋮ Optimal savings management for individuals with defined contribution pension plans ⋮ Multi-stage portfolio selection problem with dynamic stochastic dominance constraints ⋮ Optimal portfolio choice of couples with tax-deferred accounts and survival-contingent products ⋮ A New Scenario Reduction Method Based on Higher-Order Moments ⋮ Practical arbitrage‐free scenario tree reduction methods and their applications in financial optimization ⋮ Composite time-consistent multi-period risk measure and its application in optimal portfolio selection ⋮ A combined stochastic programming and optimal control approach to personal finance and pensions ⋮ Personalized goal-based investing via multi-stage stochastic goal programming ⋮ Building a stochastic programming model from scratch: a harvesting management example ⋮ A parsimonious model for generating arbitrage-free scenario trees ⋮ Multi-period forecasting and scenario generation with limited data

Uses Software

• OptiRisk

Cites Work

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• Simulation and optimization approaches to scenario tree generation
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• Scenario reduction algorithms in stochastic programming
• Scenario tree reduction for multistage stochastic programs
• A note on scenario reduction for two-stage stochastic programs
• Financial scenario generation for stochastic multi-stage decision processes as facility location problems
• Comment on “Generating Scenario Trees for Multistage Decision Problems”
• GLOBAL CONVERGENCE OF A GENERAL SAMPLING ALGORITHM FOR DYNAMIC NONLINEAR STOCHASTIC PROGRAMS
• The Scenario Generation Algorithm for Multistage Stochastic Linear Programming
• Scenarios for multistage stochastic programs
• Scenario tree generation for multiperiod financial optimization of optimal discretization

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