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Activity Number: 532
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract #314906
Title: Bayesian Analysis of LOT Liquidity Model
Author(s): Wandi Zhao* and Mingjin Wang
Companies: Peking University and Peking University
Keywords: Liquidity ; transaction costs ; Tobit model ; LOT measure ; Gibbs sampling ; data augmentation
Abstract:

LOT liquidity model, which is a kind of Tobit model with two unknown censoring points, is commonly used in the literature of microstructure of financial markets to estimate transaction costs and market liquidity from the observed return series. As far as the estimation is concerned, method based on maximum likelihood is predominated in the applied works of this model. In this paper, a Bayesian approach, based on Gibbs sampling and data augmentation method, is proposed for the estimation of LOT model. Simulation studies are conducted to illustrate its accuracy and to make a comparison with MLE. Both the results from the simulated data and a real data set from the stock markets in China reveal that the Gibbs sampling can achieve a better performance than MLE and therefore is a practical alternative method for the estimation of LOT model.


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