Early portfolio pruning: a scalable approach to hybrid portfolio selection
CC BY
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| Định dạng: | Sách |
| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s10115-023-01832-7 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8259 |
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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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1764177435587248128 |
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8.891145 |