Diversification quotients: Quantifying diversification via risk measures
We establish the first axiomatic theory for diversification indices using six intuitive axioms: non-negativity, location invariance, scale invariance, rationality, normalization, and continuity. The unique class of indices satisfying these axioms, called the diversification quotients (DQs), are defined based on a parametric family of risk measures. A further axiom of portfolio convexity pins down DQ based on coherent risk measures. DQ has many attractive properties, and it can address several theoretical and practical limitations of existing indices. In particular, for the popular risk measures Value-at-Risk and Expected Shortfall, the corresponding DQ admits simple formulas and it is efficient to optimize in portfolio selection. Moreover, it can properly capture tail heaviness and common shocks, which are neglected by traditional diversification indices. When illustrated with financial data, DQ is intuitive to interpret, and its performance is competitive against other diversification indices..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
arXiv.org - (2022) vom: 27. Juni Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Han, Xia [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| PPN (Katalog-ID): |
XCH042794129 |
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| 520 | |a We establish the first axiomatic theory for diversification indices using six intuitive axioms: non-negativity, location invariance, scale invariance, rationality, normalization, and continuity. The unique class of indices satisfying these axioms, called the diversification quotients (DQs), are defined based on a parametric family of risk measures. A further axiom of portfolio convexity pins down DQ based on coherent risk measures. DQ has many attractive properties, and it can address several theoretical and practical limitations of existing indices. In particular, for the popular risk measures Value-at-Risk and Expected Shortfall, the corresponding DQ admits simple formulas and it is efficient to optimize in portfolio selection. Moreover, it can properly capture tail heaviness and common shocks, which are neglected by traditional diversification indices. When illustrated with financial data, DQ is intuitive to interpret, and its performance is competitive against other diversification indices. | ||
| 650 | 4 | |a Quantitative Finance - Risk Management |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 510 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Lin, Liyuan |4 aut | |
| 700 | 1 | |a Wang, Ruodu |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t arXiv.org |g (2022) vom: 27. Juni |
| 773 | 1 | 8 | |g year:2022 |g day:27 |g month:06 |
| 856 | 4 | 0 | |u https://arxiv.org/abs/2206.13679 |z kostenfrei |3 Volltext |
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