A COMPARISON OF THE EXTREME VALUE THEORY AND GARCH MODELS IN TERMS OF RISK MEASURES

被引:0
|
作者
Nevruz, Ezgi [1 ]
Sahin, Sule [2 ]
机构
[1] Hacettepe Univ, Dept Actuarial Sci, Ankara, Turkey
[2] Univ Liverpool, Inst Financial & Actuarial Math, Liverpool, Merseyside, England
关键词
Extreme Value Theory; GARCH models; Human Development Index; risk measures; Value-at-risk;
D O I
10.26360/2018_7
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper, we apply extreme value theory (EVT) and time series models to eight developed and emerging stock markets published in the Morgan Stanley Capital International (MSCI) Index. Based on the Human Development Index (HDI) rankings, which are consistent with the MSCI index, we analyse Singapore, Spain, UK and US for devel-oped stock markets and Chile, Russia, Malaysia and Turkey for emerg-ing stock markets. We use the daily prices (in USD) of eight countries for the period from January 2014 to December 2017 and examine the performances of the models based on in-sample testing. Calculating the value-at-risk (VaR) as a risk measure for both right and left tails of the log-returns of the selected models, we compare these countries in terms of their financial risks. The obtained risk measures enable us to discuss the grouping and the ranking of the stock markets and their relative positions.
引用
收藏
页码:149 / 170
页数:22
相关论文
共 50 条
  • [41] An application of extreme value theory for measuring financial risk
    Gilli M.
    Këllezi E.
    [J]. Computational Economics, 2006, 27 (2-3) : 207 - 228
  • [42] The Application of Extreme Value Theory in Operational Risk Management
    Teply, Petr
    [J]. EKONOMICKY CASOPIS, 2012, 60 (07): : 698 - 716
  • [43] Value at risk forecasts by extreme value models in a conditional duration framework
    Herrera, Rodrigo
    Schipp, Bernhard
    [J]. JOURNAL OF EMPIRICAL FINANCE, 2013, 23 : 33 - 47
  • [44] Minimax risk bounds tn extreme value theory
    Drees, H
    [J]. ANNALS OF STATISTICS, 2001, 29 (01): : 266 - 294
  • [45] An application of extreme value theory in estimating liquidity risk
    Benito Muela, Sonia
    Lopez Martin, Carmen
    Arguedas Sanz, Raquel
    [J]. EUROPEAN RESEARCH ON MANAGEMENT AND BUSINESS ECONOMICS, 2017, 23 (03) : 157 - 164
  • [46] Modeling Value at Risk of Agricultural Crops Using Extreme Value Theory
    Gong, Xue
    Sriboonchitta, Songsak
    Rahman, Sanzidur
    Kuson, Siwarat
    [J]. ADVANCED SCIENCE LETTERS, 2015, 21 (05) : 1339 - 1343
  • [47] The new hybrid value at risk approach based on the extreme value theory
    Radivojevic, Nikola
    Cvjetkovic, Milena
    Stepanov, Saga
    [J]. ESTUDIOS DE ECONOMIA, 2016, 43 (01): : 29 - 52
  • [48] Limit Theory for Forecasts of Extreme Distortion Risk Measures and Expectiles
    Hoga, Yannick
    [J]. JOURNAL OF FINANCIAL ECONOMETRICS, 2022, 20 (01) : 18 - 44
  • [49] Forecasting the Risk of Cryptocurrencies: Comparison and Combination of GARCH and Stochastic Volatility Models
    Prueser, Jan
    [J]. JOURNAL OF TIME SERIES ECONOMETRICS, 2024, 16 (02) : 83 - 108
  • [50] Can Multivariate GARCH Models Really Improve Value-at-Risk Forecasts?
    Sia, C. S.
    Chan, F.
    [J]. 21ST INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION (MODSIM2015), 2015, : 1043 - 1049