Results 21 to 30 of about 45,340 (210)
Semiparametric Estimation of Risk–Return Relationships [PDF]
Journal of Business & Economic Statistics, 2017 This article proposes semiparametric generalized least-squares estimation of parametric restrictions between the conditional mean and the conditional variance of excess returns given a set of parametric factors. A distinctive feature of our estimator is that it does not require a fully parametric model for the conditional mean and variance.
Escanciano, J.C. +2 more
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Semiparametric counterfactual density estimation
Biometrika, 2023 AbstractCausal effects are often characterized with averages, which can give an incomplete picture of the underlying counterfactual distributions. Here we consider estimating the entire counterfactual density and generic functionals thereof. We focus on two kinds of target parameters: density approximations and the distance between counterfactual ...
By Kennedy, E. H. +2 more
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The influence function of semiparametric estimators [PDF]
Quantitative Economics, 2015 There are many economic parameters that depend on nonparametric first steps. Examples include games, dynamic discrete choice, average exact consumer surplus, and treatment effects. Often estimators of these parameters are asymptotically equivalent to a sample average of an object referred to as the influence function.
Hidehiko Ichimura, Whitney K. Newey
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Semi- and Nonparametric ARCH Processes
Journal of Probability and Statistics, 2011 ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper surveys the semiparametric and nonparametric methods in univariate and multivariate ARCH/GARCH models.
Oliver B. Linton, Yang Yan
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Mathematics, 2020 Geostatistical interpolation methods, sometimes referred to as kriging, have been proven effective and efficient for the estimation of target quantity at ungauged sites.
Sompop Moonchai, Nawinda Chutsagulprom
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Semiparametric Additive Beta Regression Models
Revstat Statistical Journal, 2021 In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit ...
Germán Ibacache-Pulgar +2 more
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Semiparametric Stein estimators
Journal of the Korean Statistical Society, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Department of Statistics, University of Florida, Gainesville, FL 32611-8545, USA ( host institution ) +2 more
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REGION, 2022 This article introduces a new R package (pspatreg) for the estimation of semiparametric spatial autoregressive models. pspatreg fits penalized spline semiparametric spatial autoregressive models via Restricted Maximum Likelihood or Maximum Likelihood ...
Román Mínguez +2 more
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Discrete Dynamics in Nature and Society, 2019 This article aims to investigate the Value at Risk of basis for stock index futures hedging in China. Since the RS-GARCH model can effectively describe the state transition of variance in VaR and the two-state Markov process can significantly reduce the ...
Liang Wang +3 more
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Improving Forecasts of the EGARCH Model Using Artificial Neural Network and Fuzzy Inference System
Journal of Mathematics, 2020 This paper proposes an innovative semiparametric nonlinear fuzzy-EGARCH-ANN model to solve the problem of accurate modeling for forecasting stock market volatility.
Geleta T. Mohammed +2 more
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