On analysis of exponentially decaying pulse signals using stochastic volatility model. Part II: Student-t distribution

2006 ◽  
Vol 120 (4) ◽  
pp. 1783-1786
Author(s):  
C. M. Chan ◽  
S. K. Tang
Keyword(s):  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Student T Distribution ◽  
Volatility Model ◽  
T Distribution

scholarly journals Multiscale Stochastic Volatility Model with Heavy Tails and Leverage Effects

2021 ◽  
Vol 14 (5) ◽  
pp. 225
Author(s):  
Zhongxian Men ◽  
Tony S. Wirjanto ◽  
Adam W. Kolkiewicz
Keyword(s):  
Stochastic Volatility ◽  
Heavy Tails ◽  
Foreign Currency ◽  
Asset Returns ◽  
Stochastic Volatility Model ◽  
Stochastic Volatility Models ◽  
Asymmetric Effects ◽  
Volatility Models ◽  
Volatility Model ◽  
T Distribution

This paper studies multiscale stochastic volatility models of financial asset returns. It specifies two components in the log-volatility process and allows for leverage/asymmetric effects from both components while return innovation terms follow a heavy/fat tailed Student t distribution. The two components are shown to be important in capturing persistent dependence in return volatility, which is often absent in applications of stochastic volatility models which incorporate leverage/asymmetric effects. The models are applied to asset returns from a foreign currency market and an equity market. The model fits are assessed, and the proposed models are shown to compare favorably to the one-component asymmetric stochastic volatility models with Gaussian and Student t distributed innovation terms.

A non-Gaussian stochastic volatility model

1998 ◽  
Vol 2 (2) ◽  
pp. 33-47 ◽  
Author(s):  
Yuichi Nagahara ◽  
Genshiro Kitagawa
Keyword(s):  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Volatility Model ◽  
Non Gaussian
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