Qian, Hang (2009): Estimating SUR Tobit Model while errors are gaussian scale mixtures: with an application to high frequency financial data.
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This paper examines multivariate Tobit system with Scale mixture disturbances. Three estimation methods, namely Maximum Simulated Likelihood, Expectation Maximization Algorithm and Bayesian MCMC simulators, are proposed and compared via generated data experiments. The chief finding is that Bayesian approach outperforms others in terms of accuracy, speed and stability. The proposed model is also applied to a real data set and study the high frequency price and trading volume dynamics. The empirical results confirm the information contents of historical price, lending support to the usefulness of technical analysis. In addition, the scale mixture model is also extended to sample selection SUR Tobit and finite Gaussian regime mixtures.
|Item Type:||MPRA Paper|
|Original Title:||Estimating SUR Tobit Model while errors are gaussian scale mixtures: with an application to high frequency financial data|
|English Title:||Estimating SUR Tobit Model while Errors are Gaussian Scale Mixtures: with an Application to High Frequency Financial Data|
|Keywords:||Tobit; Gaussian mixtures; Bayesian|
|Subjects:||C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models; Multiple Variables > C34 - Truncated and Censored Models; Switching Regression Models
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics
|Depositing User:||Hang Qian|
|Date Deposited:||13. Jun 2011 19:54|
|Last Modified:||15. Feb 2013 10:44|
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