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Sufficient Forecasting Using Factor Models
Fan, Jianqing - 2015
method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that …
Persistent link: https://www.econbiz.de/10013022529
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Modeling Intraday Momentum and Reversal by a Parsimonious Diffusion Process
Ling, Shiqing - 2019
We extend the double-well potential process to a three-parameter version in order to model intraday price dynamics, with a focus on the intraday momentum and reversal. The proposed process has a parsimonious form of three parameters controlling momentum, reversal, and volatility respectively. By...
Persistent link: https://www.econbiz.de/10012868934
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Generalized reduced rank tests using the singular value decomposition
Kleibergen, Frank; Paap, Richard - 2003
statistic of Robin and Smith [Econometric Theory (2000), 16, 151–175] usage of numerical optimization for the objective function … singular values in Ratsimalahelo [2002, Rank test based on matrix perturbation theory. Unpublished working paper, U …
Persistent link: https://www.econbiz.de/10011332818
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Generalized Method of Trimmed Moments
Cizek, Pavel - 2009
High breakdown-point regression estimators protect against large errors and data contamination. We adapt and generalize the concept of trimming used by many of these robust estimators so that it can be employed in the context of the generalized method of moments. The proposed generalized method...
Persistent link: https://www.econbiz.de/10012718043
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The method of moments for multivariate random sums
Javed, Farrukh; Loperfido, Nicola; Mazur, Stepan - 2024
Multivariate random sums appear in many scientific fields, most notably in actuarial science, where they model both the number of claims and their sizes. Unfortunately, they pose severe inferential problems. For example, their density function is analytically intractable, in the general case,...
Persistent link: https://www.econbiz.de/10014575595
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A Doubly Corrected Robust Variance Estimator for Linear GMM
Hwang, Jungbin - 2019
We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including the one-step, two-step, and iterated estimators. Our formula additionally corrects for the over-identification bias in variance estimation on top of the commonly used finite...
Persistent link: https://www.econbiz.de/10012863983
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Inference for Iterated GMM Under Misspecification and Clustering
Hansen, Bruce E.; Lee, Seojeong - 2019
This paper develops a new distribution theory and inference methods for over-identified Generalized Method of Moments … with heterogeneous and growing cluster sizes. This paper is the first to provide a rigorous theory for the iterated GMM … asymptotic theory allows the moments to be possibly misspecified, which is a general feature of approximate over …
Persistent link: https://www.econbiz.de/10014033687
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Assessing multivariate predictors of financial market movements : a latent factor framework for ordinal data
Huber, Philippe; Scaillet, Olivier; Victoria-Feser, … - 2008
Much of the trading activity in Equity markets is directed to brokerage houses. In exchange they provide so-called quot;soft dollarsquot; which basically are amounts spent in quot;researchquot; for identifying profitable trading opportunities. Soft dollars represent about USD 1 out of every USD...
Persistent link: https://www.econbiz.de/10003966616
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Large vector autoregressions with asymmetric priors
Carriero, Andrea; Clark, Todd E.; Marcellino, Massimiliano - 2015 - This draft: November 2015
We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
Persistent link: https://www.econbiz.de/10011389735
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Constrained Principal Components Estimation of Large Approximate Factor Models
Ouysse, Rachida - 2020
This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are crosssectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components...
Persistent link: https://www.econbiz.de/10012854370