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Author: Sahbi Farhani Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
This paper considers tests of parameters instability and structural change with known, unknown or multiple breakpoints. The results apply to a wide class of parametric models that are suitable for estimation by strong rules for detecting the number of breaks in a time series. For that, we use Chow, CUSUM, CUSUM of squares, Wald, likelihood ratio and Lagrange multiplier tests. Each test implicitly uses an estimate of a change point. We conclude with an empirical analysis on two different models (ARMA model and simple linear regression model 'SLRM').
Author: Xu Han Publisher: ISBN: Category : Languages : en Pages : 67
Book Description
We develop tests for structural breaks of factor loadings in dynamic factor models. We focus on the joint null hypothesis that all factor loadings are constant over time. Because the number of factor loading parameters goes to infinity as the sample size grows, conventional tests cannot be used. Based on the fact that the presence of a structural change in factor loadings yields a structural change in second moments of factors obtained from the full sample principal component estimation, we reduce the infinite-dimensional problem into a finite-dimensional one and our statistic compares the pre- and post-break subsample second moments of estimated factors. Our test is consistent under the alternative hypothesis in which a fraction of or all factor loadings have structural changes. The Monte Carlo results show that our test has good finite-sample size and power.
Author: Francesco Calvori Publisher: ISBN: Category : Languages : en Pages : 40
Book Description
We develop a new parameter stability test against the alternative of observation driven generalized autoregressive score dynamics. The new test generalizes the ARCH-LM test of Engle (1982) to settings beyond time-varying volatility and exploits any autocorrelation in the likelihood scores under the alternative. We compare the test's performance with that of alternative tests developed for competing time-varying parameter frameworks, such as structural breaks and observation driven parameter dynamics. The new test has higher and more stable power against alternatives with frequent regime switches or with non-local parameter driven time-variation. For parameter driven time variation close to the null or for infrequent structural changes, the test of Muller and Petalas (2010) performs best overall. We apply all tests empirically to a panel of losses given default over the period 1982-2010 and find significant evidence of parameter variation in the underlying beta distribution.
Author: Dong Jin Lee Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
This article examines asymptotically point optimal tests for parameter instability in realistic circumstances when little information about the unstable parameter process and error distribution is available. We first show that, under a correctly specified error distribution, if the unstable parameter processes converge weakly to a Wiener process, then any asymptotic optimal tests for structural breaks and time-varying parameters are asymptotically equivalent. Our finding is then extended to a semi-parametric set-up in which the error distribution is treated as an unknown infinite-dimensional nuisance parameter. We find that semi-parametric tests can be adaptive without further restrictive conditions on the error distribution.
Author: Sahbi Farhani Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
This paper considers tests of parameters instability and structural change with known, unknown or multiple breakpoints. The results apply to a wide class of parametric models that are suitable for estimation by strong rules for detecting the number of breaks in a time series. For that, we use Chow, CUSUM, CUSUM of squares, Wald, likelihood ratio and Lagrange multiplier tests. Each test implicitly uses an estimate of a change point. We conclude with an empirical analysis on two different models (ARMA model and simple linear regression model 'SLRM').
Author: Torben G. Andersen Publisher: ISBN: Category : Languages : en Pages :
Book Description
This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all - or a subset - of the variables may be fractionally integrated and the predictive relation may feature cointegration, we provide sup-Wald break tests that are constructed using the Local speCtruM (LCM) approach. The new tests cover both parameter variation and multiple structural changes with unknown break dates, and the number of breaks being known or unknown. We establish asymptotic limit theory for the tests, showing that it coincides with standard testing procedures. As a consequence, existing critical values for tied-down Bessel processes may be applied, without modification. We implement the new structural change tests to explore the stability of the fractionally cointegrating relation between implied- and realized volatility (IV and RV). Moreover, we assess the relative efficiency of IV forecasts against a challenging time-series benchmark constructed from high-frequency data. Unlike existing studies, we find evidence that the IV-RV cointegrating relation is unstable, and that carefully constructed time-series forecasts are more efficient than IV in capturing low-frequency movements in RV.
Author: Robert N.N. Holtzman Publisher: Springer Science & Business Media ISBN: 1461393264 Category : Medical Languages : en Pages : 537
Book Description
In this volume, world authorities on spinal surgery from the fields of Neurosurgery, Orthopaedic Surgery, and Neuroscience present current data on the basic science and clinical management of the unstable spine. Unique to this book: a frank presentation of controversies in the field.
Author: Sahbi Farhani
Author: Dong Jin Lee
Author: Xu Han
Author: Donald W. K. Andrews
Author: Francesco Calvori
Author: Dong Jin Lee
Author: Michael J. Harrison
Author: James F. Cotter
Author: Sahbi Farhani
Author: Torben G. Andersen
Author: Robert N.N. Holtzman