Diversification for infinite-mean Pareto models without risk aversion
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910819455860736 |
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| author | Chen, Yuyu Hu, Taizhong Wang, Ruodu Zou, Zhenfeng |
| author_facet | Chen, Yuyu Hu, Taizhong Wang, Ruodu Zou, Zhenfeng |
| contents | We study stochastic dominance between portfolios of independent and identically distributed (iid) extremely heavy-tailed (i.e., infinite-mean) Pareto random variables. With the notion of majorization order, we show that a more diversified portfolio of iid extremely heavy-tailed Pareto random variables is larger in the sense of first-order stochastic dominance. This result is further generalized for Pareto random variables caused by triggering events, random variables with tails being Pareto, bounded Pareto random variables, and positively dependent Pareto random variables. These results provide an important implication in investment: Diversification of extremely heavy-tailed Pareto profits uniformly increases investors' profitability, leading to a diversification benefit. Remarkably, different from the finite-mean setting, such a diversification benefit does not depend on the decision maker's risk aversion. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_18467 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Diversification for infinite-mean Pareto models without risk aversion Chen, Yuyu Hu, Taizhong Wang, Ruodu Zou, Zhenfeng Portfolio Management Theoretical Economics We study stochastic dominance between portfolios of independent and identically distributed (iid) extremely heavy-tailed (i.e., infinite-mean) Pareto random variables. With the notion of majorization order, we show that a more diversified portfolio of iid extremely heavy-tailed Pareto random variables is larger in the sense of first-order stochastic dominance. This result is further generalized for Pareto random variables caused by triggering events, random variables with tails being Pareto, bounded Pareto random variables, and positively dependent Pareto random variables. These results provide an important implication in investment: Diversification of extremely heavy-tailed Pareto profits uniformly increases investors' profitability, leading to a diversification benefit. Remarkably, different from the finite-mean setting, such a diversification benefit does not depend on the decision maker's risk aversion. |
| title | Diversification for infinite-mean Pareto models without risk aversion |
| topic | Portfolio Management Theoretical Economics |
| url | https://arxiv.org/abs/2404.18467 |