Bootstrap methods in econometrics
JL Horowitz - Annual Review of Economics, 2019 - annualreviews.org
The bootstrap is a method for estimating the distribution of an estimator or test statistic by
resampling one's data or a model estimated from the data. Under conditions that hold in a …
resampling one's data or a model estimated from the data. Under conditions that hold in a …
Bootstrap: More than a Stab in the Dark?
GA Young - Statistical Science, 1994 - JSTOR
A critical review is given of recent research activity on bootstrap and related procedures.
Theoretical work has shown the bootstrap approach to be a potentially powerful addition to …
Theoretical work has shown the bootstrap approach to be a potentially powerful addition to …
[图书][B] Quantile regression
R Koenker - 2005 - books.google.com
Quantile regression is gradually emerging as a unified statistical methodology for estimating
models of conditional quantile functions. By complementing the exclusive focus of classical …
models of conditional quantile functions. By complementing the exclusive focus of classical …
[图书][B] Randomization, bootstrap and Monte Carlo methods in biology
BFJ Manly - 2018 - taylorfrancis.com
Modern computer-intensive statistical methods play a key role in solving many problems
across a wide range of scientific disciplines. This new edition of the bestselling …
across a wide range of scientific disciplines. This new edition of the bestselling …
[图书][B] Smoothing methods in statistics
JS Simonoff - 2012 - books.google.com
The existence of high speed, inexpensive computing has made it easy to look at data in
ways that were once impossible. Where once a data analyst was forced to make restrictive …
ways that were once impossible. Where once a data analyst was forced to make restrictive …
[图书][B] The jackknife and bootstrap
The jackknife and bootstrap are the most popular data-resampling meth ods used in
statistical analysis. The resampling methods replace theoreti cal derivations required in …
statistical analysis. The resampling methods replace theoreti cal derivations required in …
The bootstrap
JL Horowitz - Handbook of econometrics, 2001 - Elsevier
The bootstrap is a method for estimating the distribution of an estimator or test statistic by
resampling one's data or a model estimated from the data. Under conditions that hold in a …
resampling one's data or a model estimated from the data. Under conditions that hold in a …
Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood
G González-Rivera, TH Lee, S Mishra - International Journal of forecasting, 2004 - Elsevier
We analyze the predictive performance of various volatility models for stock returns. To
compare their performance, we choose loss functions for which volatility estimation is of …
compare their performance, we choose loss functions for which volatility estimation is of …
Evaluating predictive performance of value‐at‐risk models in emerging markets: a reality check
We investigate the predictive performance of various classes of value‐at‐risk (VaR) models
in several dimensions—unfiltered versus filtered VaR models, parametric versus …
in several dimensions—unfiltered versus filtered VaR models, parametric versus …
Bootstrap methods for median regression models
JL Horowitz - Econometrica, 1998 - JSTOR
The least-absolute-deviations (LAD) estimator for a median-regression model does not
satisfy the standard conditions for obtaining asymptotic refinements through use of the …
satisfy the standard conditions for obtaining asymptotic refinements through use of the …