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A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
This paper presents a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic. This estimator does not depend on a formalExpand
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Multilayer feedforward networks are universal approximators
TLDR
We show that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available. Expand
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Maximum Likelihood Estimation of Misspecified Models
This paper examines the consequences and detection of model misspecification when using maximum likelihood techniques for estimation and inference. The quasi-maximum likelihood estimator (QMLE)Expand
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Asymptotic theory for econometricians
  • H. White
  • Economics, Mathematics
  • 1 December 1985
The Linear Model and Instrumental Variables Estimators. Consistency. Laws of Large Numbers. Asymptotic Normality. Central Limit Theory. Estimating Asymptotic Covariance Matrices. Functional CentralExpand
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Tests of Conditional Predictive Ability
TLDR
We argue that the current framework for predictive ability testing (e.g., West, 1996) is not necessarily useful for real-time forecast selection, i.e., for assessing which of two competing forecasting methods will perform better in the future. Expand
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A Reality Check for Data Snooping
Data snooping occurs when a given set of data is used more than once for purposes of inference or model selection. When such data reuse occurs, there is always the possibility that any satisfactoryExpand
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Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties☆
We examine several modified versions of the heteroskedasticity-consistent covariance matrix estimator of Hinkley and White. On the basis of sampling experiments which compare the performance of quasiExpand
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Estimation, inference, and specification analysis
  • H. White
  • Computer Science, Mathematics
  • 1 September 1996
TLDR
This book examines the consequences of misspecifications ranging from the fundamental to the nonexistent for the interpretation of likelihood-based methods of statistical estimation and interference, and the conditions under which parameters of interest can be consistently estimated despite misspecification. Expand
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Can Mutual Fund 'Stars' Really Pick Stocks? New Evidence from a Bootstrap Analysis
We apply an innovative bootstrap statistical technique to examine the performance of the U.S. equity mutual fund industry during the 1962 to 1994 period. Using this new method, we bootstrap theExpand
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Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap
In this paper we utilize Whites Reality Check bootstrap methodology (White (1997)) to evaluate simple technical trading rules while quantifying the data-snooping bias and fully adjusting for itsExpand
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