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Applied Mathematics-A Journal of Chinese Universities  2019, Vol. 34 Issue (2): 205-    DOI: 10.1007/s11766-019-3628-9
    
Econometric modeling of risk measures: A selective review of the recent literature
TIAN Ding-shi, CAI Zong-wu, FANG Ying
1 Wang Yanan Institute for Studies in Economics, Department of Statistics, School of Economics,  Ministry of Education Key Laboratory of Econometrics and Fujian Key Laboratory of Statistical Science,Xiamen University, Xiamen, Fujian 361005, China.
2 Department of Economics, University of Kansas, Lawrence, KS 66045, USA.
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Abstract  Since the financial crisis in 2008, the risk measures which are the core of risk management,
have received increasing attention among economists and practitioners. In this review,
the concentration is on recent developments in the estimation of the most popular risk measures,
namely, value at risk (VaR), expected shortfall (ES), and expectile. After introducing the concept
of risk measures, the focus is on discussion and comparison of their econometric modeling.
Then, parametric and nonparametric estimations of tail dependence are investigated. Finally,
we conclude with insights into future research directions.


Key wordsExpectile      Expected Shortfall      Network Risk      Nonparametric Estimation      Tail Dependence      Value at Risk     
Published: 03 July 2019
CLC:  62-02  
  62M10  
  62G08  
Cite this article:

TIAN Ding-shi, CAI Zong-wu, FANG Ying. Econometric modeling of risk measures: A selective review of the recent literature. Applied Mathematics-A Journal of Chinese Universities, 2019, 34(2): 205-.

URL:

http://www.zjujournals.com/amjcub/10.1007/s11766-019-3628-9     OR     http://www.zjujournals.com/amjcub/Y2019/V34/I2/205


Econometric modeling of risk measures: A selective review of the recent literature

Since the financial crisis in 2008, the risk measures which are the core of risk management,
have received increasing attention among economists and practitioners. In this review,
the concentration is on recent developments in the estimation of the most popular risk measures,
namely, value at risk (VaR), expected shortfall (ES), and expectile. After introducing the concept
of risk measures, the focus is on discussion and comparison of their econometric modeling.
Then, parametric and nonparametric estimations of tail dependence are investigated. Finally,
we conclude with insights into future research directions.

关键词: Expectile,  Expected Shortfall,  Network Risk,  Nonparametric Estimation,  Tail Dependence,  Value at Risk 
[1] LIN Yi-wei, LI Zhen-wei, SONG Yu-ping. Bias Free Threshold Estimation for Jump Intensity Function[J]. Applied Mathematics-A Journal of Chinese Universities, 2019, 34(3): 309-325.