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Robust resampling methods for time series
Camponovo, Lorenzo; Scaillet, Olivier; Trojani, Fabio - 2010 - This version: May 9, 2010
We study the robustness of block resampling procedures for time series. We first derive a set of formulas to … applications. This renders inference based on standard resampling methods useless already in simple estimation and testing settings …. To solve this problem, we introduce a robust fast resampling scheme that is applicable to a wide class of time series …
Persistent link: https://www.econbiz.de/10003971115
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How to implement the bootstrap in static or stable dynamic regression models
Giersbergen, Noud P. A. van; Kiviet, J. F. - 2001
By combining two alternative formulations of a test statistic with two alternative resamplingschemes we obtain four different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and power problems, whereas the remaining two areadequate...
Persistent link: https://www.econbiz.de/10011325661
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Nonparametric Inferences on Conditional Quantile Processes
Goh, Chuan - 2007
This paper is concerned with tests of restrictions on the sample path of conditional quantile processes. These tests are tantamount to assessments of lack of fit for models of conditional quantile functions or more generally as tests of how certain covariates affect the distribution of an...
Persistent link: https://www.econbiz.de/10012731947
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On Bootstrapping Tests of Equal Forecast Accuracy for Nested Models
Doko Tchatoka, Firmin; Haque, Qazi - 2020
The asymptotic distributions of the recursive out-of-sample forecast accuracy test statistics depend on stochastic integrals of Brownian motion when the models under comparison are nested. This often complicates their implementation in practice because the computation of their asymptotic...
Persistent link: https://www.econbiz.de/10014101174
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Cluster-robust jackknife and bootstrap inference for binary response models
MacKinnon, James G.; Nielsen, Morten Ørregaard; Webb, … - 2024
We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...
Persistent link: https://www.econbiz.de/10015048740
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Large Dimension Forecasting Models and Random Singular Value Spectra
Bouchaud, Jean-Philippe - 2013
We present a general method to detect and extract from a finite time sample statistically meaningful correlations between input and output variables of large dimensionality. Our central result is derived from the theory of free random matrices, and gives an explicit expression for the interval...
Persistent link: https://www.econbiz.de/10013075383
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A Simple Test for Linearity Against Exponential Smooth Transition Models with Endogenous Variables
Massacci, Daniele - 2017
This paper proposes a test for linearity against exponential smooth transition models with endogenous right-hand-side variables: to the very best of our knowledge, this class of models is new to the literature. By Monte Carlo analysis the test is shown to have good finite sample properties
Persistent link: https://www.econbiz.de/10014176554
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New Solution to Time Series Inference in Spurious Regression Problems
Vinod, Hrishikesh D. - 2010
Phillips (1986) provides asymptotic theory for regressions that relate nonstationary time series including those integrated of order 1, I(1). A practical implication of related literature on spurious regression is that one cannot trust the usual confidence intervals. Therefore it is recommended...
Persistent link: https://www.econbiz.de/10014197508
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Technical trading revisited : false discoveries, persistence tests, and transaction costs
Bajgrowicz, Pierre; Scaillet, Olivier - 2009 - This version: Sept. 2009
We revisit the apparent historical success of technical trading rules on daily prices of the DJIA index from 1897 to 2011, and use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it selects more outperforming rules which allows...
Persistent link: https://www.econbiz.de/10003961414
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The phantom menace of omitted variables : a comment
Ritter, Nolan; Vance, Colin - 2011
This note demonstrates that in applied regression analysis, the variance of a coefficient of interest may decrease from the inclusion of a control variable, contrasting with Clarke's assertion (2005, 2009) that the variance can only increase or stay the same. Practitioners may thus be...
Persistent link: https://www.econbiz.de/10009580263