Volatility Forecasting and Explanatory Variables: A Tractable Bayesian Approach to Stochastic Volatility

2012 ◽  
Author(s):  
Christian Dorion ◽  
Nicolas Chapados
Keyword(s):  
Stochastic Volatility ◽  
Bayesian Approach ◽  
Volatility Forecasting ◽  
Explanatory Variables

scholarly journals Threshold Stochastic Volatility Models with Heavy Tails: A Bayesian Approach

Economía ◽  
2019 ◽  
Vol 42 (83) ◽  
pp. 32-53
Author(s):  
Carlos A. Abanto-Valle ◽  
Hernán B. Garrafa-Aragón
Keyword(s):  
Stochastic Volatility ◽  
Bayesian Approach ◽  
Heavy Tails ◽  
Stochastic Volatility Models ◽  
Volatility Models

Bayesian Inference for Comparative Research

1994 ◽  
Vol 88 (2) ◽  
pp. 412-423 ◽  
Author(s):  
Bruce Western ◽  
Simon Jackman
Keyword(s):  
Regression Analysis ◽  
Comparative Analysis ◽  
Bayesian Inference ◽  
Statistical Inference ◽  
Bayesian Approach ◽  
Comparative Research ◽  
Data Sets ◽  
Explanatory Variables ◽  
Long Run

Regression analysis in comparative research suffers from two distinct problems of statistical inference. First, because the data constitute all the available observations from a population, conventional inference based on the long-run behavior of a repeatable data mechanism is not appropriate. Second, the small and collinear data sets of comparative research yield imprecise estimates of the effects of explanatory variables. We describe a Bayesian approach to statistical inference that provides a unified solution to these two problems. This approach is illustrated in a comparative analysis of unionization.

Sign in / Sign up

Export Citation Format

Share Document