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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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A joint specification test for response probabilities in unordered multinomial choice models
Iwasawa, Masamune - In: Econometrics : open access journal 3 (2015) 3, pp. 667-697
Estimation results obtained by parametric models may be seriously misleading when the model is misspecified or poorly approximates the true model. This study proposes a test that jointly tests the specifications of multiple response probabilities in unordered multinomial choice models. The test...
Persistent link: https://www.econbiz.de/10011410669
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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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Improved inference on the rank of a matrix
Chen, Qihui; Fang, Zheng - In: Quantitative economics : QE ; journal of the … 10 (2019) 4, pp. 1787-1824
This paper develops a general framework for conducting inference on the rank of an unknown matrix Π0. A defining feature of our setup is the null hypothesis of the form . The problem is of first‐order importance because the previous literature focuses on by implicitly assuming away , which...
Persistent link: https://www.econbiz.de/10012202917
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Nonparametric Bootstrap for Quasi-Likelihood Ratio Tests
Camponovo, Lorenzo - 2011
We introduce a nonparametric block bootstrap approach for Quasi-Likelihood Ratio type tests of nonlinear restrictions. Our method applies to extremum estimators, such as quasi-maximum likelihood and generalized method of moments estimators. Unlike existing parametric bootstrap procedures for...
Persistent link: https://www.econbiz.de/10014178027
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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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Shortcomings of a parametric VaR approach and nonparametric improvements based on a non-stationary return series model
Gürtler, Marc; Rauh, Ronald - 2009 - This Version: 2009-09-09
A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a...
Persistent link: https://www.econbiz.de/10009487233
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Detecting serial dependence in tail events
Diks, Cees G. H. - 2002
A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as...
Persistent link: https://www.econbiz.de/10011327543
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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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Shortcomings of a Parametric VaR Approach and Nonparametric Improvements Based on a Non-Stationary Return Series Model
Gürtler, Marc - 2009
In this paper we first investigate the validity of a general Value at Risk approach, which is widely used for risk management in banking and insurance companies. We discuss and widely reject the conventional assumptions, e.g. independent identically distributed normal returns, and as consequence...
Persistent link: https://www.econbiz.de/10013159079