Pincheira, Pablo (2017): A Power Booster Factor for OutofSample Tests of Predictability.

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Abstract
In this paper we introduce a “power booster factor” for outofsample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another smaller nested model. Although our factor can be used to improve the power of many outofsample tests of predictability, in this paper we focus on boosting the power of the widely used test developed by Clark and West (2006, 2007). Our new test multiplies the Clark and West tstatistic by a factor that should be close to one under the null hypothesis that the short nested model is the true model, but that should be greater than one under the alternative hypothesis that the big nesting model is more adequate. We use Monte Carlo simulations to explore the size and power of our approach. Our simulations reveal that the new test is well sized and powerful. In particular, it tends to be less undersized and more powerful than the test by Clark and West (2006, 2007). Although most of the gains in power are associated to size improvements, we also obtain gains in sizeadjusted power. Finally we present an empirical application in which more rejections of the null hypothesis are obtained with our new test.
Item Type:  MPRA Paper 

Original Title:  A Power Booster Factor for OutofSample Tests of Predictability 
English Title:  A Power Booster Factor for OutofSample Tests of Predictability 
Language:  English 
Keywords:  Timeseries, forecasting, inference, inflation, exchange rates, random walk, outofsample 
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 > C52  Model Evaluation, Validation, and Selection C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C58  Financial Econometrics E  Macroeconomics and Monetary Economics > E1  General Aggregative Models > E17  Forecasting and Simulation: Models and Applications E  Macroeconomics and Monetary Economics > E2  Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E27  Forecasting and Simulation: Models and Applications E  Macroeconomics and Monetary Economics > E3  Prices, Business Fluctuations, and Cycles > E37  Forecasting and Simulation: Models and Applications E  Macroeconomics and Monetary Economics > E4  Money and Interest Rates > E47  Forecasting and Simulation: Models and Applications F  International Economics > F3  International Finance > F37  International Finance Forecasting and Simulation: Models and Applications 
Item ID:  77027 
Depositing User:  Pablo Matías Pincheira 
Date Deposited:  23 Feb 2017 06:44 
Last Modified:  23 Feb 2017 06:45 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/77027 