Computing strategies for achieving acceptability: a Monte Carlo approach

DOI10.1016/j.spa.2006.09.012zbMath1133.91033arXivmath/0607617OpenAlexW2122944870MaRDI QIDQ2464857

Soumik Pal

Publication date: 17 December 2007

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0607617

zbMATH Keywords

VC dimensionportfolio optimizationNeyman-Pearson lemmaoptimization algorithmmeasures of risk

Mathematics Subject Classification ID

Uses Software

• BayesDA

Cites Work

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• Bounds for the uniform deviation of empirical measures
• Central limit theorems for empirical measures
• Sharper bounds for Gaussian and empirical processes
• Convex measures of risk and trading constraints
• Satisfying convex risk limits by trading
• Inf-convolution of risk measures and optimal risk transfer
• Coherent Measures of Risk
• Fundamental Theorems of Asset Pricing for Good Deal Bounds
• Stochastic finance. An introduction in discrete time
• Coherent risk measures and good-deal bounds

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