Distributional Bounds for Portfolio Risk with Tail Dependence
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| 008 | 210128e20150901xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s11009-014-9396-5 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s11009-014-9396-5 | ||
| 245 | 0 | 0 | |a Distributional Bounds for Portfolio Risk with Tail Dependence |h [Elektronische Daten] |c [Kunio So, Junichi Imai] |
| 520 | 3 | |a The present paper proposes a new method for estimating portfolio risk by applying the concept of bounds to a dependence structure. We introduce four tail dependence measures as partial dependence information and derive bounds on the distribution of a non-decreasing function to obtain bounds on risk measures. We show that bounds on risk measures can be tightened significantly in the probability levels with which we are concerned, those for financial risk management. In the present paper, we provide theorems describing the distributional bounds of the proposed method and prove that these bounds are pointwise best-possible bounds. Furthermore, we calculate risk measures, i.e., value at risk and expected shortfall, from empirical return data and compare the effectiveness of the proposed model with that of typical parametric copula models. | |
| 540 | |a Springer Science+Business Media New York, 2014 | ||
| 690 | 7 | |a Risk management |2 nationallicence | |
| 690 | 7 | |a Market risks |2 nationallicence | |
| 690 | 7 | |a Tail dependence |2 nationallicence | |
| 690 | 7 | |a Copulas |2 nationallicence | |
| 690 | 7 | |a Fréchet bounds |2 nationallicence | |
| 700 | 1 | |a So |D Kunio |u Graduate School of Science and Technolog, Keio University, 3-14-1 Hiyoshi, Kohoku, 223-8522, Yokohama, Japan |4 aut | |
| 700 | 1 | |a Imai |D Junichi |u Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku, 223-8522, Yokohama, Japan |4 aut | |
| 773 | 0 | |t Methodology and Computing in Applied Probability |d Springer US; http://www.springer-ny.com |g 17/3(2015-09-01), 795-816 |x 1387-5841 |q 17:3<795 |1 2015 |2 17 |o 11009 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s11009-014-9396-5 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s11009-014-9396-5 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a So |D Kunio |u Graduate School of Science and Technolog, Keio University, 3-14-1 Hiyoshi, Kohoku, 223-8522, Yokohama, Japan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Imai |D Junichi |u Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku, 223-8522, Yokohama, Japan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Methodology and Computing in Applied Probability |d Springer US; http://www.springer-ny.com |g 17/3(2015-09-01), 795-816 |x 1387-5841 |q 17:3<795 |1 2015 |2 17 |o 11009 | ||