A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector

2015 ◽  
Vol 32 ◽  
pp. 98-123 ◽  
Author(s):  
Juan C. Reboredo ◽  
Andrea Ugolini
2019 ◽  
Vol 8 (1) ◽  
pp. 15
Author(s):  
NI WAYAN UCHI YUSHI ARI SUDINA ◽  
KOMANG DHARMAWAN ◽  
I WAYAN SUMARJAYA

Conditional value at risk (CVaR) is widely used in risk measure that takes into account losses exceeding the value at risk level. The aim of this research is to compare the performance of the EVT-GJR-vine copula method and EVT-GARCH-vine copula method in estimating CVaR of the portfolio using backtesting. Based on the backtesting results, it was found that the EVT-GJR-vine copula method have better performance when compared to the EVT-GARCH-vine copula method in estimating the CVaR value of the portfolio. This can be seen from the statistical values ??, and  of EVT-GJR-vine copula method which is generally smaller than the statistical values , and of the EVT-GARCH-vine copula method.


2018 ◽  
Vol 30 (4) ◽  
pp. 641-661
Author(s):  
Mahuya Basu ◽  
Tanupa Chakraborty

This paper aims to assess the weather risk exposure of Indian power sector from both generation and demand sides. The study considers two representative firms – firstly, Damodar Valley Corporation (DVC), a hydro-generator, to assess its rainfall exposure, and secondly, Calcutta Electric Supply Corporation (CESC), a retail power supplier, to assess the temperature sensitivity of power demand. The study opts for ‘Value at Risk’ approach, which combines both the sensitivity of power variables towards weather variable and the probability of weather change. The sensitivity is measured using regression analysis with autoregressive distributed lag (ARDL). Parametric distributions are fitted to weather data to assess probabilities. Due to the ‘fat-tail’ characteristic of the fitted distribution, a ‘conditional value-at-risk’ model is considered more effective. The study reveals that the hydroelectricity generation is highly exposed to monsoon rainfall fluctuation and hence the hydro-generator may experience substantial loss of revenue due to insufficient monsoon, whereas the revenue of retail power distributor is moderately exposed to fluctuation of daily surface temperature.


2019 ◽  
Vol 146 ◽  
pp. 201-210 ◽  
Author(s):  
Lili Wei ◽  
Yudong Shen ◽  
Zuwei Liao ◽  
Jingyuan Sun ◽  
Binbo Jiang ◽  
...  

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