Results 31 to 40 of about 6,656,167 (244)
International Journal for Re-Views in Empirical Economics, 2019 This paper aims to replicate the semiparametric Value-At-Risk model by Dias (2014) and to test its legitimacy. The study confirms the superiority of semiparametric estimation over classical methods such as mixture normal and Student-t approximations in ...
Jiahua Xu
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A semiparametric model for cluster data
The Annals of Statistics, 2009 In the analysis of cluster data, the regression coefficients are frequently assumed to be the same across all clusters. This hampers the ability to study the varying impacts of factors on each cluster. In this paper, a semiparametric model is introduced to account for varying impacts of factors over clusters by using cluster-level covariates.
Zhang, Wenyang, Fan, Jianqing, Sun, Yan
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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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International VaR approach: Backtesting for different capital markets
Revista Contabilidade & Finanças, 2019 This article aims to compare distinct metrics of the value at risk (VaR), differing from prior studies with respect about compare three asset categories belonging to seven countries.
Marília Cordeiro Pinheiro +1 more
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Endogeneity in semiparametric binary response models [PDF]
, 2003 This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single index binary response models to the ...
Blundell, R., Powell, J.L.
core
Nonparametric and semiparametric estimation with discrete regressors [PDF]
, 1994 This paper presents and discusses procedures for estimating regression curves when regressors are discrete and applies them to semiparametric inference problems.
Delgado, Miguel A., Mora, Juan
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Flexible semiparametric mixed models [PDF]
, 2005 In linear mixed models the influence of covariates is restricted to a strictly parametric form. With the rise of semi- and nonparametric regression also the mixed model has been expanded to allow for additive predictors.
Reithinger, Florian, Tutz, Gerhard
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Business Strategy and the Environment, EarlyView.ABSTRACT Whether corporate carbon management can enhance productive efficiency is central to firms' long‐term competitiveness and determines whether carbon reduction efforts can be sustained beyond regulatory compliance. This study examines how corporate carbon risk and opportunity management affects firm productivity (measured by total factor ...
Nan Huang, Hanlu Fan, Ruoxin Zhu
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ETAS Space–Time Modeling of Chile Triggered Seismicity Using Covariates: Some Preliminary Results
Applied Sciences, 2021 Chilean seismic activity is one of the strongest in the world. As already shown in previous papers, seismic activity can be usefully described by a space–time branching process, such as the ETAS (Epidemic Type Aftershock Sequences) model, which is a ...
Marcello Chiodi +4 more
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NONPARAMETRIC ESTIMATION OF SEMIPARAMETRIC TRANSFORMATION MODELS [PDF]
Econometric Theory, 2016 In this paper we develop a nonparametric estimation technique for semiparametric transformation models of the form:H(Y) =φ(Z) +X′β+UwhereH,φare unknown functions,βis an unknown finite-dimensional parameter vector and the variables (Y,Z) are endogenous.
Florens, Jean-Pierre, Sokullu, Senay
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