Automated Variable Selection in Vector Multiplicative Error Models
AbstractMultiplicative Error Models (MEM) can be used to trace the dynamics of non–negative valued processes. Interactions between several such processes are accommodated by the vector MEM and estimated by maximum likelihood (Gamma marginals with copula functions) or by Generalized Method of Moments. In choosing the relevant variables one can follow an automated procedure where the full specification is successively pruned in a general–to–specific approach. An efficient and fast algorithm is presented in this paper and evaluated by means of a simulation and a real world example of volatility spillovers in European markets.
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Bibliographic InfoPaper provided by Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" in its series Econometrics Working Papers Archive with number wp2009_02.
Date of creation: Feb 2009
Date of revision:
Multiplicative Error Model; GMM; Simultaneous Equations; Volatility; Market Activity;
Other versions of this item:
- Cipollini, Fabrizio & Gallo, Giampiero M., 2010. "Automated variable selection in vector multiplicative error models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2470-2486, November.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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