scholarly journals EMD Copula based Value at Risk Estimates for Electricity Markets

2015 ◽  
Vol 55 ◽  
pp. 1318-1324 ◽  
Author(s):  
Xuan Wang ◽  
Junling Cai ◽  
Kaijian He
Keyword(s):  
At Risk ◽  
Electricity Markets ◽  
Value At Risk ◽  
Risk Estimates

scholarly journals Asymptotic Value-at-Risk Estimates for Sums of Dependent Random Variables

2003 ◽  
Vol 33 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Mario V. Wüthrich
Keyword(s):  
At Risk ◽  
Asymptotic Behaviour ◽  
Value At Risk ◽  
Random Variables ◽  
Important Application ◽  
Archimedean Copulas ◽  
Dependent Random Variables ◽  
Asymptotic Value ◽  
Risk Estimates

We estimate Value-at-Risk for sums of dependent random variables. We model multivariate dependent random variables using archimedean copulas. This structure allows one to calculate the asymptotic behaviour of extremal events. An important application of such results are Value-at-Risk estimates for sums of dependent random variables.

Evaluating Value-at-Risk Estimates: A Cross-Section Approach

2007 ◽  
pp. 213-225
Author(s):  
Raffaele Zenti ◽  
Massimiliano Pallotta ◽  
Claudio Marsala
Keyword(s):  
At Risk ◽  
Cross Section ◽  
Value At Risk ◽  
Risk Estimates

scholarly journals Generating Volatility Forecasts from Value at Risk Estimates

2005 ◽  
Vol 51 (5) ◽  
pp. 712-725 ◽  
Author(s):  
James W. Taylor
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Estimates

Value at Risk Estimates for Brady Bond Portfolios

2000 ◽  
Vol 10 (3) ◽  
pp. 7-23 ◽  
Author(s):  
Ron D′Vari ◽  
Juan C. Sosa
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Estimates ◽  
Bond Portfolios

USING EXTREME VALUE THEORY TO EVALUATE CONDITIONAL VAR FOR RISK MANAGEMENT IN ELECTRICITY MARKETS

2016 ◽  
Vol 78 (10) ◽  
Author(s):  
M. T. Askari ◽  
Z. Afzalipor ◽  
A. Amoozadeh
Keyword(s):  
At Risk ◽  
Electricity Markets ◽  
Extreme Value Theory ◽  
Value At Risk ◽  
Risk Model ◽  
Test System ◽  
Value Theory ◽  
Extreme Value ◽  
Conditional Value At Risk ◽  
Bidding Strategy

In a deregulated power market, generation companies attempt to maximize their profits and minimize their risks. This paper proposes a risk model for bidding strategy of generation companies based on EVT-CVaR method. Extreme Value Theory can overcome shortcomings of traditional methods in computing financial risk based on value-at-risk and conditional value-at-risk method. Also, generalized Pareto distribution is suggested to model tail of an unknown distribution and parameters of the GPD are estimated by likelihood moment method. Numerical results for risk assessment using the proposed approach are presented for IEEE 30-bus test system. According to the findings, this method can be used as a robust technique to calculate the risk for bidding strategy of generation companies.

Sign in / Sign up

Export Citation Format

Share Document