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JSS Research Series in Statistics
cover

Asymmetric Kernel Smoothing

Theory and Applications in Economics and Finance

Authors: Hirukawa, Masayuki

  • Provides an accessible collection of recently developed nonparametric smoothing techniques for estimation and testing procedures
  • Explores the statistical properties of estimators and test statistics smoothed by asymmetric kernels, in comparison with those smoothed by conventional symmetric kernels
  • Includes real data analyses in economics and finance, overcoming the methodological issues that cannot be readilyhandled by conventional kernel methods
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Buy this book

eBook 41,64 €
price for Spain (gross)
  • ISBN 978-981-10-5466-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 51,99 €
price for Spain (gross)
  • ISBN 978-981-10-5465-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This is the first book to provide an accessible and comprehensive introduction to a newly developed smoothing technique using asymmetric kernel functions. Further, it discusses the statistical properties of estimators and test statistics using asymmetric kernels. The topics addressed include the bias-variance tradeoff, smoothing parameter choices, achieving rate improvements with bias reduction techniques, and estimation with weakly dependent data. Further, the large- and finite-sample properties of estimators and test statistics smoothed by asymmetric kernels are compared with those smoothed by symmetric kernels. Lastly, the book addresses the applications of asymmetric kernel estimation and testing to various forms of nonnegative economic and financial data.

Until recently, the most popularly chosen nonparametric methods used symmetric kernel functions to estimate probability density functions of symmetric distributions with unbounded support. Yet many types of economic and financial data are nonnegative and violate the presumed conditions of conventional methods. Examples include incomes, wages, short-term interest rates, and insurance claims. Such observations are often concentrated near the boundary and have long tails with sparse data. Smoothing with asymmetric kernel functions has increasingly gained attention, because the approach successfully addresses the issues arising from distributions that have natural boundaries at the origin and heavy positive skewness. Offering an overview of recently developed kernel methods, complemented by intuitive explanations and mathematical proofs, this book is highly recommended to all readers seeking an in-depth and up-to-date guide to nonparametric estimation methods employing asymmetric kernel smoothing.

About the authors

Masayuki Hirukawa, Faculty of Economics, Ryukoku University


Table of contents (6 chapters)

Table of contents (6 chapters)
  • Asymmetric Kernels: An Introduction

    Pages 1-15

    Hirukawa, Masayuki

  • Univariate Density Estimation

    Pages 17-39

    Hirukawa, Masayuki

  • Bias Correction in Density Estimation

    Pages 41-58

    Hirukawa, Masayuki

  • Regression Estimation

    Pages 59-71

    Hirukawa, Masayuki

  • Specification Testing

    Pages 73-101

    Hirukawa, Masayuki

Buy this book

eBook 41,64 €
price for Spain (gross)
  • ISBN 978-981-10-5466-2
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 51,99 €
price for Spain (gross)
  • ISBN 978-981-10-5465-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Asymmetric Kernel Smoothing
Book Subtitle
Theory and Applications in Economics and Finance
Authors
Series Title
JSS Research Series in Statistics
Copyright
2018
Publisher
Springer Singapore
Copyright Holder
The Author(s)
eBook ISBN
978-981-10-5466-2
DOI
10.1007/978-981-10-5466-2
Softcover ISBN
978-981-10-5465-5
Series ISSN
2364-0057
Edition Number
1
Number of Pages
XII, 110
Number of Illustrations
5 b/w illustrations
Topics