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Early portfolio pruning: a scalable approach to hybrid portfolio selection

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Bibliographic Details
Main Authors: Daniele G., Gioia, Jacopo, Fior, Luca, Cagliero
Format: Book
Language:English
Published: Springer 2023
Subjects:
Early portfolio pruning
Online Access:https://link.springer.com/article/10.1007/s10115-023-01832-7
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8259
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spelling oai:localhost:PNK-82592023-04-25T02:10:00Z Early portfolio pruning: a scalable approach to hybrid portfolio selection Daniele G., Gioia Jacopo, Fior Luca, Cagliero Early portfolio pruning CC BY Driving the decisions of stock market investors is among the most challenging financial research problems. Markowitz’s approach to portfolio selection models stock profitability and risk level through a mean–variance model, which involves estimating a very large number of parameters. In addition to requiring considerable computational effort, this raises serious concerns about the reliability of the model in real-world scenarios. This paper presents a hybrid approach that combines itemset extraction with portfolio selection. We propose to adapt Markowitz’s model logic to deal with sets of candidate portfolios rather than with single stocks. We overcome some of the known issues of the Markovitz model as follows: (i) Complexity: we reduce the model complexity, in terms of parameter estimation, by studying the interactions among stocks within a shortlist of candidate stock portfolios previously selected by an itemset mining algorithm. (ii) Portfolio-level constraints: we not only perform stock-level selection, but also support the enforcement of arbitrary constraints at the portfolio level, including the properties of diversification and the fundamental indicators. (iii) Usability: we simplify the decision-maker’s work by proposing a decision support system that enables flexible use of domain knowledge and human-in-the-loop feedback. 2023-04-25T02:10:00Z 2023-04-25T02:10:00Z 2023 Book https://link.springer.com/article/10.1007/s10115-023-01832-7 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8259 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Early portfolio pruning
spellingShingle Early portfolio pruning
Daniele G., Gioia
Jacopo, Fior
Luca, Cagliero
Early portfolio pruning: a scalable approach to hybrid portfolio selection
description CC BY
format Book
author Daniele G., Gioia
Jacopo, Fior
Luca, Cagliero
author_facet Daniele G., Gioia
Jacopo, Fior
Luca, Cagliero
author_sort Daniele G., Gioia
title Early portfolio pruning: a scalable approach to hybrid portfolio selection
title_short Early portfolio pruning: a scalable approach to hybrid portfolio selection
title_full Early portfolio pruning: a scalable approach to hybrid portfolio selection
title_fullStr Early portfolio pruning: a scalable approach to hybrid portfolio selection
title_full_unstemmed Early portfolio pruning: a scalable approach to hybrid portfolio selection
title_sort early portfolio pruning: a scalable approach to hybrid portfolio selection
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10115-023-01832-7
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8259
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score 8.891145

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