A threshold stochastic volatility model
By Mike K. P. So, Wai Keung Li, K. Lam. 2002
122 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/28a7fc4f3565ca0eee303ec6a6b963f6acad6a08
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Michael Mcaleer
- Manabu Asai
- Marcelo C. Medeiros
- Yasuhiro Omori
- Siddhartha Chib
- Esther Ruiz
- Carmen Broto
- Jun Yu
In Finance
- Michael Mcaleer
- Manabu Asai
- Marcelo C. Medeiros
- Yasuhiro Omori
- Siddhartha Chib
- Esther Ruiz
- Carmen Broto
- Jun Yu
Citations in the corpus
- Estimation methods for stochastic volatility models: a survey (2004, methodology): “Later, Jacquier et al. (2004) propose an ARSV model with leverage effect where "t and t are correlated.”
- Multivariate Stochastic Volatility: A Review (2006, background): “In the univariate SV literature, So et al. (2002) proposed a threshold SV model, in which the constant term and the autoregressive parameter in the SV equation changed according to the sign of the previous return.”
- A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries (2008, background): “So, Lam, and Li (1998) and Kalimipalli and Susmel (2007) discussed SV models with Markovian regime switches, while So, Li, and Lam (2002) considered a threshold SV specification.”
- Alternative Asymmetric Stochastic Volatility Models (2009, unknown): “Recently, So et al. (2002) considered a threshold effects model in which the breaks in the constant and autoregressive parameter in the SV equation depend on the signs of the previous returns.”
- Multivariate stochastic volatility (2009, background): “In the univariate SV literature, So et al. (2002) proposed a threshold SV model, in which the constant term and the autoregressive parameter in the SV equation changed according to the sign of the previous return.”
- A comprehensive review of Value at Risk methodologies (2014, methodology): “…alternative and more complex models have been developed for the stochastic volatility models to allow for the pattern of both the large memory (see the model of Harvey (1998) and Breidt et al. (1998)) and the leverage effect (see the models of Harvey and Shephard (1996) and So et al. (2002)).”