Bayesian estimation of generalized partition of unity copulas
Dependence Modeling, 2020 This paper proposes a Bayesian estimation algorithm to estimate Generalized Partition of Unity Copulas (GPUC), a class of nonparametric copulas recently introduced by [18].
Masuhr Andreas, Trede Mark
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Identification and Estimation of Intensive Margin Effects by Difference-in-Difference Methods
Journal of Causal Inference, 2020 This paper discusses identification and estimation of causal intensive margin effects. The causal intensive margin effect is defined as the treatment effect on the outcome of individuals with a positive outcome irrespective of whether they are treated or
Hersche Markus, Moor Elias
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New fat-tail normality test based on conditional second moments with applications to finance [PDF]
, 2020 In this paper we introduce an efficient fat-tail measurement framework that is based on the conditional second moments. We construct a goodness-of-fit statistic that has a direct interpretation and can be used to assess the impact of fat-tails on central
Jelito, Damian, Pitera, Marcin
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The role of Skorokhod space in the development of the econometric analysis of time series [PDF]
, 2008 This paper discusses the fundamental role played by Skorokhod space, through its underpinning of functional central limit theory, in the development of the paradigm of unit roots and co-integration.
Mc CRORIE, J. Roderick
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Orthogonal Polynomials for Seminonparametric Instrumental Variables Model [PDF]
, 2014 We develop an approach that resolves a {\it polynomial basis problem} for a class of models with discrete endogenous covariate, and for a class of econometric models considered in the work of Newey and Powell (2003), where the endogenous covariate is ...
Kovchegov, Yevgeniy, Yildiz, Nese
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Functional generalized autoregressive conditional heteroskedasticity [PDF]
, 2015 Heteroskedasticity is a common feature of financial time series and is commonly addressed in the model building process through the use of ARCH and GARCH processes. More recently multivariate variants of these processes have been in the focus of research
Aue, Alexander +2 more
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Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
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Prediction of time series by statistical learning: general losses and fast rates
Dependence Modeling, 2013 We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the ...
Alquier Pierre +2 more
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Nonparametric volatility density estimation for discrete time models [PDF]
, 2002 We consider discrete time models for asset prices with a stationary volatility process. We aim at estimating the multivariate density of this process at a set of consecutive time instants.
Spreij, Peter +2 more
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Comparison of imputation methods for handling missing categorical data with univariate pattern [PDF]
, 2014 This paper examines the sample proportions estimates in the presence of univariate missing categorical data. A database about smoking habits (2011 National Addiction Survey of Mexico) was used to create simulated yet realistic datasets at rates 5% and 15%
Torres Munguía, Juan Armando
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