Optimization algorithms and investment portfolio analytics with machine learning techniques under time-varying liquidity constraints

Purpose This paper aims to examine from commodity portfolio managers’ perspective the performance of liquidity adjusted risk modeling in assessing the market risk parameters of a large commodity portfolio and in obtaining efficient and coherent portfolios under different market circumstances. Design...

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Vydáno v:	Journal of modelling in management Ročník 17; číslo 3; s. 864 - 895
Hlavní autor:	Al Janabi, Mazin A.M.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Bradford Emerald Publishing Limited 22.08.2022 Emerald Group Publishing Limited
Témata:	Artificial intelligence Commodity prices Design optimization Financial institutions Institutional investments International finance Internet of Things Liquidity Machine learning Mathematical programming Optimization algorithms Optimization techniques Portfolio management Portfolio performance Securities markets Supply & demand Volatility C13 G20 Business analysis Finance Risk analysis G28 Analytics Optimization Liquidity-adjusted value-at-risk Stress testing Commodity JEL Classifications C10 Portfolio analysis Machine learning Liquidity risk Portfolio management Artificial intelligence
ISSN:	1746-5664, 1746-5664, 1746-5672
On-line přístup:	Získat plný text
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