The use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios

DOI10.1016/j.physa.2016.10.042zbMath1400.91675arXiv1605.09181OpenAlexW2516592679MaRDI QIDQ1620236

Krzysztof Domino

Publication date: 13 November 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.09181

zbMATH Keywords

Hurst exponentfinancial data analysiscumulant tensorsstock exchangeALS-class algorithm

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Financial applications of other theories (91G80) Portfolio theory (91G10)

Related Items (3)

Efficient Computation of Higher-Order Cumulant Tensors ⋮ Multivariate cumulants in outlier detection for financial data analysis ⋮ An algorithm for arbitrary-order cumulant tensor calculation in a sliding window of data streams

Cites Work

• Tensor Decompositions and Applications
• ARCH modeling in finance. A review of the theory and empirical evidence
• Dimensionality reduction in higher-order signal processing and rank-\((R_1,R_2,\ldots,R_N)\) reduction in multilinear algebra
• Quasi-Newton Methods on Grassmannians and Multilinear Approximations of Tensors
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