Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 2, 2026Statistica SinicaOpen Access

Asymmetric Garch Modelling Without Moment Conditions

View Full Paper
Ask AI
Bookmark
Share

Authors

YTYuxin TaoDLDong LiDLDong Li

Discussion

Loading...

Member takes

Overview

Randomized trial applies a new sGARCH model to stock returns, indicating advancements in financial modeling.

Key Points

  • The aim is to develop an asymmetric GARCH model that addresses stability and heavy-tailed distributions in financial time series.
  • Proposed a sAGARCH model with stable innovations to accommodate infinite variance and mean.
  • Established a comprehensive inference framework for both stationary and explosive cases.
  • Performed Monte Carlo simulations to analyze the intercept estimator's performance.
  • Proved strong consistency and asymptotic normality of the maximum likelihood estimator with specified parameters.
  • Demonstrated the model's efficacy through empirical applications with stock returns.
  • Developed a modified Kolmogorov-type test statistic for diagnostic checking, enhancing model verification.

Cite This Study

Tao et al. (2026) studied this question.

synapsesocial.com/papers/6a45fecd9ed134303130f71bhttps://doi.org/10.5705/ss.202025.0271
View Full Paper
Ask AI
Bookmark
Share