ERN: Nonparametric Methods (Topic)最新文献_第5页

Near-Optimal Bisection Search for Nonparametric Dynamic Pricing with Inventory Constraint 库存约束下非参数动态定价的近最优二分搜索

ERN: Nonparametric Methods (Topic) Pub Date : 2014-10-01 DOI: 10.2139/ssrn.2509425

Y. Lei, Stefanus Jasin, Amitabh Sinha

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引用次数: 36

Asymptotic Refinements of a Fully Nonparametric Bootstrap for Quasi-Likelihood Ratio Tests of Extremum Estimators 极值估计的拟似然比检验的完全非参数Bootstrap的渐近改进

ERN: Nonparametric Methods (Topic) Pub Date : 2014-09-01 DOI: 10.2139/ssrn.2442389

Lorenzo Camponovo

引用次数: 0

Bootstrap Methods for the Realized Bipower Variation and for Jump Testing 实现双功率变化和跳跃测试的自举方法

ERN: Nonparametric Methods (Topic) Pub Date : 2014-04-01 DOI: 10.2139/ssrn.2201083

Ana-Maria H. Dumitru

引用次数: 0

Risk Margin Quantile Function via Parametric and Non-Parametric Bayesian Quantile Regression 基于参数和非参数贝叶斯分位数回归的风险边际分位数函数

ERN: Nonparametric Methods (Topic) Pub Date : 2014-02-11 DOI: 10.2139/ssrn.2394063

A. Dong, J. Chan, G. Peters

{"title":"Risk Margin Quantile Function via Parametric and Non-Parametric Bayesian Quantile Regression","authors":"A. Dong, J. Chan, G. Peters","doi":"10.2139/ssrn.2394063","DOIUrl":"https://doi.org/10.2139/ssrn.2394063","url":null,"abstract":"We develop quantile regression models in order to derive risk margin and to evaluate capital in non-life insurance applications. By utilizing the entire range of conditional quantile functions, especially higher quantile levels, we detail how quantile regression is capable of providing an accurate estimation of risk margin and an overview of implied capital based on the historical volatility of a general insurers loss portfolio. Two modelling frameworks are considered based around parametric and nonparametric quantile regression models which we develop specifically in this insurance setting. In the parametric quantile regression framework, several models including the flexible generalized beta distribution family, asymmetric Laplace (AL) distribution and power Pareto distribution are considered under a Bayesian regression framework. The Bayesian posterior quantile regression models in each case are studied via Markov chain Monte Carlo (MCMC) sampling strategies. In the nonparametric quantile regression framework, that we contrast to the parametric Bayesian models, we adopted an AL distribution as a proxy and together with the parametric AL model, we expressed the solution as a scale mixture of uniform distributions to facilitate implementation. The models are extended to adopt dynamic mean, variance and skewness and applied to analyze two real loss reserve data sets to perform inference and discuss interesting features of quantile regression for risk margin calculations.","PeriodicalId":11744,"journal":{"name":"ERN: Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82110840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Functional Coefficient Nonstationary Regression 非平稳回归

ERN: Nonparametric Methods (Topic) Pub Date : 2013-07-31 DOI: 10.2139/ssrn.2303991

Jiti Gao, P. Phillips

{"title":"Functional Coefficient Nonstationary Regression","authors":"Jiti Gao, P. Phillips","doi":"10.2139/ssrn.2303991","DOIUrl":"https://doi.org/10.2139/ssrn.2303991","url":null,"abstract":"This paper studies a general class of nonlinear varying coefficient time series models with possible nonstationarity in both the regressors and the varying coffiecient components. The model accommodates a cointegrating structure and allows for endogeneity with contemporaneous correlation among the regressors, the varying coefficient drivers, and the residuals. This framework allows for a mixture of stationary and non-stationary data and is well suited to a variety of models that are commonly used in applied econometric work. Nonparametric and semiparametric estimation methods are proposed to estimate the varying coefficient functions. The analytical findings reveal some important differences, including convergence rates, that can arise in the conduct of semiparametric regression with nonstationary data. The results include some new asymptotic theory for nonlinear functionals of nonstationary and stationary time series that are of wider interest and applicability and subsume much earlier research on such systems. The finite sample properties of the proposed econometric methods are analyzed in simulations. An empirical illustration examines nonlinear dependencies in aggregate consumption function behavior in the US over the period 1960-2009.","PeriodicalId":11744,"journal":{"name":"ERN: Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80830486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

A Nonparametric Test of a Strong Leverage Hypothesis 强杠杆假设的非参数检验

ERN: Nonparametric Methods (Topic) Pub Date : 2013-07-01 DOI: 10.2139/ssrn.2145341

O. Linton, Yoon-Jae Whang, Yu-Min Yen

引用次数: 9

A Simple Nonparametric Test for the Existence of Finite Moments 有限矩存在性的一个简单非参数检验

ERN: Nonparametric Methods (Topic) Pub Date : 2013-04-01 DOI: 10.2139/ssrn.2202269

Igor Fedotenkov

引用次数: 3

Simulated Testing of Nonparametric Measure Changes for Hedging European Options 欧洲期权套期保值非参数测度变化的模拟检验

ERN: Nonparametric Methods (Topic) Pub Date : 2013-02-16 DOI: 10.1016/J.FRL.2012.11.002

Godfrey Smith

引用次数: 2

A Distribution-Free Test for Outliers 异常值的无分布检验

ERN: Nonparametric Methods (Topic) Pub Date : 2013-01-01 DOI: 10.2139/ssrn.2796894

B. Candelon, N. Metiu

引用次数: 9

Semi-Parametric Bayesian Partially Identified Models Based on Support Function 基于支持函数的半参数贝叶斯部分识别模型

ERN: Nonparametric Methods (Topic) Pub Date : 2012-12-13 DOI: 10.2139/ssrn.2189030

Yuan Liao, Anna Simoni

{"title":"Semi-Parametric Bayesian Partially Identified Models Based on Support Function","authors":"Yuan Liao, Anna Simoni","doi":"10.2139/ssrn.2189030","DOIUrl":"https://doi.org/10.2139/ssrn.2189030","url":null,"abstract":"Bayesian partially identified models have received a growing attention in recent years in the econometric literature, due to their broad applications in empirical studies. Classical Bayesian approach in this literature has been assuming a parametric model, by specifying an ad-hoc parametric likelihood function. However, econometric models usually only identify a set of moment inequalities, and therefore assuming a known likelihood function suffers from the risk of misspecification, and may result in inconsistent estimations of the identified set. On the other hand, moment-condition based likelihoods such as the limited information and exponential tilted empirical likelihood, though guarantee the consistency, lack of probabilistic interpretations. We propose a semi-parametric Bayesian partially identified model, by placing a nonparametric prior on the unknown likelihood function. Our approach thus only requires a set of moment conditions but still possesses a pure Bayesian interpretation. We study the posterior of the support function, which is essential when the object of interest is the identified set. The support function also enables us to construct two-sided Bayesian credible sets (BCS) for the identified set. It is found that, while the BCS of the partially identified parameter is too narrow from the frequentist point of view, that of the identified set has asymptotically correct coverage probability in the frequentist sense. Moreover, we establish the posterior consistency for both the structural parameter and its identified set. We also develop the posterior concentration theory for the support function, and prove the semi-parametric Bernstein von Mises theorem. Finally, the proposed method is applied to analyze a financial asset pricing problem.","PeriodicalId":11744,"journal":{"name":"ERN: Nonparametric Methods (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86805641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8