Predicting VaR for China's stock market : a score-driven model based on normal inverse Gaussian distribution
Year of publication: |
2022
|
---|---|
Authors: | Song, Shijia ; Li, Handong |
Published in: |
International review of financial analysis. - Amsterdam [u.a.] : Elsevier, ISSN 1057-5219, ZDB-ID 1133622-5. - Vol. 82.2022, p. 1-20
|
Subject: | Dynamic conditional score | Intraday return | Normal inverse Gaussian | Realized GARCH | Value-at-risk | ARCH-Modell | ARCH model | China | Statistische Verteilung | Statistical distribution | Risikomaß | Risk measure | Aktienmarkt | Stock market | Zeitreihenanalyse | Time series analysis | Volatilität | Volatility | Kapitaleinkommen | Capital income | Theorie | Theory |
-
Wang, Tianyi, (2022)
-
Naimoli, Antonio, (2022)
-
Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics
Gerlach, Richard, (2020)
- More ...
-
A new model for forecasting VaR and ES using intraday returns aggregation
Song, Shijia, (2023)
-
Song, Shijia, (2023)
-
Research on the effects of liquidation strategies in the multi-asset artificial market
Luo, Qixuan, (2023)
- More ...