Home > Research > Publications & Outputs > Modelling extreme-value dependence in internati...
View graph of relations

Modelling extreme-value dependence in international stock markets.

Research output: Contribution to journalJournal article

Published

Standard

Modelling extreme-value dependence in international stock markets. / Poon, Ser-Huang; Rockinger, Michael; Tawn, Jonathan.

In: Statistica Sinica, Vol. 13, 2003, p. 929-953.

Research output: Contribution to journalJournal article

Harvard

Poon, S-H, Rockinger, M & Tawn, J 2003, 'Modelling extreme-value dependence in international stock markets.', Statistica Sinica, vol. 13, pp. 929-953.

APA

Poon, S-H., Rockinger, M., & Tawn, J. (2003). Modelling extreme-value dependence in international stock markets. Statistica Sinica, 13, 929-953.

Vancouver

Poon S-H, Rockinger M, Tawn J. Modelling extreme-value dependence in international stock markets. Statistica Sinica. 2003;13:929-953.

Author

Poon, Ser-Huang; ; Rockinger, Michael; ; Tawn, Jonathan. / Modelling extreme-value dependence in international stock markets. In: Statistica Sinica. 2003 ; Vol. 13. pp. 929-953.

Bibtex

@article{b32b246902d84d4595106bb45a632fce,
title = "Modelling extreme-value dependence in international stock markets.",
abstract = "In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modelled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then current modelling approaches will lead to an over-estimation of the risk of simultaneous extreme events. We use two simple nonparametric measures to identify and quantify the tail dependence among stock returns in five international stock markets. We show that there is strong evidence in favour of asymptotically independent models for the tail structure of stock market returns, and that most of the extremal dependence is due to heteroskedasticity in stock returns processes. Using a range of volatility filters, we find that tail index and tail dependence can be partially captured by models for heteroskedasticity. We find there is no clear reason to prefer one volatility filter over another.",
keywords = "Asymptotic independence, extreme value theory, Hill's estimator, risk management, tail index.",
author = "Ser-Huang; Poon and Michael; Rockinger and Jonathan Tawn",
year = "2003",
language = "English",
volume = "13",
pages = "929--953",
journal = "Statistica Sinica",
issn = "1017-0405",
publisher = "Institute of Statistical Science",

}

RIS

TY - JOUR

T1 - Modelling extreme-value dependence in international stock markets.

AU - Poon, Ser-Huang;

AU - Rockinger, Michael;

AU - Tawn, Jonathan

PY - 2003

Y1 - 2003

N2 - In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modelled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then current modelling approaches will lead to an over-estimation of the risk of simultaneous extreme events. We use two simple nonparametric measures to identify and quantify the tail dependence among stock returns in five international stock markets. We show that there is strong evidence in favour of asymptotically independent models for the tail structure of stock market returns, and that most of the extremal dependence is due to heteroskedasticity in stock returns processes. Using a range of volatility filters, we find that tail index and tail dependence can be partially captured by models for heteroskedasticity. We find there is no clear reason to prefer one volatility filter over another.

AB - In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modelled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then current modelling approaches will lead to an over-estimation of the risk of simultaneous extreme events. We use two simple nonparametric measures to identify and quantify the tail dependence among stock returns in five international stock markets. We show that there is strong evidence in favour of asymptotically independent models for the tail structure of stock market returns, and that most of the extremal dependence is due to heteroskedasticity in stock returns processes. Using a range of volatility filters, we find that tail index and tail dependence can be partially captured by models for heteroskedasticity. We find there is no clear reason to prefer one volatility filter over another.

KW - Asymptotic independence

KW - extreme value theory

KW - Hill's estimator

KW - risk management

KW - tail index.

M3 - Journal article

VL - 13

SP - 929

EP - 953

JO - Statistica Sinica

JF - Statistica Sinica

SN - 1017-0405

ER -