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Dynamic modeling under linear-exponential loss

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Author Info
Stanislav Anatolyev () (New Economic School)

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Abstract

We develop a methodology of parametric modeling of time series dynamics when the underlying loss function is linear-exponential (Linex). We propose to directly model the dynamics of the conditional expectation that determines the optimal predictor. The procedure hinges on the exponential quasi maximum likelihood interpretation of the Linex loss and nicely fits the multiple error modeling framework. Many conclusions relating to estimation, inference and forecasting follow from results already available in the econometric literature. The methodology is illustrated using data on United States GNP growth and Treasury bill returns.

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Publisher Info
Paper provided by Center for Economic and Financial Research (CEFIR) in its series Working Papers with number w0092.

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Length: 20 pages
Date of creation: Dec 2006
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Handle: RePEc:cfr:cefirw:w0092

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Related research
Keywords: Linear-exponential loss; optimal predictor; quasi maximum likelihood; multiple error model; autoregressive conditional durations;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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