Sucarrat, Genaro and Escribano, Alvaro (2013): Unbiased Estimation of LogGARCH Models in the Presence of Zero Returns.
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Abstract
A critique that has been directed towards the logGARCH model is that its logvolatility specification does not exist in the presence of zero returns. A common ``remedy" is to replace the zeros with a small (in the absolute sense) nonzero value. However, this renders estimation asymptotically biased. Here, we propose a solution to the case where the true return is equal to zero with probability zero. In this case zero returns may be observed because of nontrading, measurement error (e.g. due to rounding), missing values and other data issues. The solution we propose treats the zeros as missing values and handles these by combining estimation via the ARMA representation with an ExpectationMaximisation (EM) type algorithm. An extensive number of simulations confirm the conjectured asymptotic properties of the biascorrecting algorithm, and several empirical applications illustrate that it can make a substantial difference in practice.
Item Type:  MPRA Paper 

Original Title:  Unbiased Estimation of LogGARCH Models in the Presence of Zero Returns 
English Title:  Unbiased Estimation of LogGARCH Models in the Presence of Zero Returns 
Language:  English 
Keywords:  ARCH, exponential GARCH, logGARCH, ARMA, ExpectationMaximisation (EM) 
Subjects:  C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics 
Item ID:  59040 
Depositing User:  Dr. Genaro Sucarrat 
Date Deposited:  02 Oct 2014 13:23 
Last Modified:  01 May 2015 23:05 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/59040 
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Unbiased QML Estimation of LogGARCH Models in the Presence of Zero Returns. (deposited 16 Oct 2013 08:20)
 Unbiased Estimation of LogGARCH Models in the Presence of Zero Returns. (deposited 02 Oct 2014 13:23) [Currently Displayed]