Abstract
EGARCH-VaR model is established for measure the liquidity risk. Meanwhile, liquidity gap is selected as the measurement index. It is tested that logarithmic difference time series of the bank liquidity gap have the characteristics of peak and fat tail distribution and high-order ARCH effect. By using the maximum likelihood estimation method for EGARCH model’s perturbation parameter estimation, the value of VaR is calculated and tested. Comparing with GARCH model, EGARCH-VaR model is more accurate and efficient.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
