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on Econometric Time Series |
| By: | Jin Seo Cho (Department of Economics, Korea University, Seoul, South Korea); Halbert White (Department of Economics, University of California, San Diego, U.S.A.) |
| Abstract: | We provide a familiy of tests for the IID hypothesis based on generalized runs, powerful against unspecified alternatives, providing a useful complement to test designed for specific alternatives, such as serial correlation, GARCH, or structural breaks. Our tests have appealing computational simplicity in that they do not require kernel density estimation, with the associated challenge of bandwidth selection. Simulations show levels close to nominal asymptotic levels.Our tests have power against both dependent and heterogeneous alternatives, as both theory and simulations demonstrate. |
| Keywords: | IID condition, Runs test, Geometric Distribution, Gaussian process,Dependence, Structural Break |
| JEL: | C12 C23 C80 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:iek:wpaper:0913&r=ets |
| By: | Chirok Han (Korea University); Jin Seo Cho (Korea University); Peter C. B. Phillips (Yale University, University of York, University of Auckland & Singapore Management University) |
| Abstract: | Statistics are developed to test for the presence of an asymptotic discontinuity (or infinite density or peakedness) in a probability density at the median. The approach makes use of work by Knight (1998) on L1 estimation asymptotics in conjunction with non-parametric kernel density estimation methods. The size and power of the tests are assessed, and conditions under which the tests have good performance are explored in simulations. The new methods are applied to stock returns of leading companies across major U.S. industry groups. The results confirm the presence of infinite density at the median as a new significant empirical evidence for stock return distributions. |
| Keywords: | Asymptotic leptokurtosis, Infinite density at the median, Least absolute deviations, Kernel density estimation, Stock returns, Stylized facts |
| JEL: | C12 G11 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:iek:wpaper:0914&r=ets |
| By: | Todd E. Clark; Michael W. McCracken |
| Abstract: | This paper presents analytical, Monte Carlo, and empirical evidence linking in-sample tests of predictive content and out-of-sample forecast accuracy. Our approach focuses on the negative effect that finite-sample estimation error has on forecast accuracy despite the presence of significant population-level predictive content. Specifically, we derive simple-to-use in-sample tests that test not only whether a particular variable has predictive content but also whether this content is estimated precisely enough to improve forecast accuracy. Our tests are asymptotically non-central chi-square or non-central normal. We provide a convenient bootstrap method for computing the relevant critical values. In the Monte Carlo and empirical analysis, we compare the effectiveness of our testing procedure with more common testing procedures. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:rwp09-10&r=ets |
| By: | Todd E. Clark; Michael W. McCracken |
| Abstract: | This paper develops bootstrap methods for testing whether, in a finite sample, competing out-of-sample forecasts from nested models are equally accurate. Most prior work on forecast tests for nested models has focused on a null hypothesis of equal accuracy in population basically, whether coefficients on the extra variables in the larger, nesting model are zero. We instead use an asymptotic approximation that treats the coefficients as non-zero but small, such that, in a finite sample, forecasts from the small model are expected to be as accurate as forecasts from the large model. Under that approximation, we derive the limiting distributions of pairwise tests of equal mean square error, and develop bootstrap methods for estimating critical values. Monte Carlo experiments show that our proposed procedures have good size and power properties for the null of equal finite-sample forecast accuracy. We illustrate the use of the procedures with applications to forecasting stock returns and inflation. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedkrw:rwp09-11&r=ets |