Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk
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DOI: 10.1016/j.frl.2021.102143
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- repec:eme:jalpps:jal-02-2023-0023 is not listed on IDEAS
- Young Shin Kim & Frank J. Fabozzi, 2024. "Portfolio optimization with relative tail risk," Annals of Operations Research, Springer, vol. 341(2), pages 1023-1055, October.
- Jing, Ruixue & Rocha, Luis E.C., 2023.
"A network-based strategy of price correlations for optimal cryptocurrency portfolios,"
Finance Research Letters, Elsevier, vol. 58(PC).
- Ruixue Jing & Luis Enrique Correa Rocha, 2023. "A network-based strategy of price correlations for optimal cryptocurrency portfolios," Papers 2304.02362, arXiv.org.
- Young Shin Kim, 2023. "Portfolio Optimization with Relative Tail Risk," Papers 2303.12209, arXiv.org, revised Mar 2023.
- Tong Liu & Yanlin Shi, 2022. "Innovation of the Component GARCH Model: Simulation Evidence and Application on the Chinese Stock Market," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
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More about this item
Keywords
Cryptocurrencies; Foster-Hart risk; GARCH modeling; Multivariate normal tempered stable process; Portfolio optimization; Value at risk;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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