Predicting Stock and Portfolio Returns Using Mixtures of Truncated Exponentials

DOI10.1007/978-3-642-02906-6_67zbMath1245.91103OpenAlexW1495474494MaRDI QIDQ3638198

Antonio Salmerón, Barry R. Cobb, Rafael Rumí

Publication date: 2 July 2009

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-642-02906-6_67

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15) Financial applications of other theories (91G80)

Cites Work

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• Approximate probability propagation with mixtures of truncated exponentials
• Bayesian network classifiers
• Operations for inference in continuous Bayesian networks with linear deterministic variables
• Learning hybrid Bayesian networks using mixtures of truncated exponentials
• Symbolic and Quantitative Approaches to Reasoning with Uncertainty

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