EconBiz - Find Economic Literature
    • Logout
    • Change account settings
  • A-Z
  • Beta
  • About EconBiz
  • News
  • Thesaurus (STW)
  • Academic Skills
  • Help
  •  My account 
    • Logout
    • Change account settings
  • Login
EconBiz - Find Economic Literature
Publications Events
Search options
Advanced Search history
My EconBiz
Favorites Loans Reservations Fines
    You are here:
  • Home
  • Search: subject:"Robust statistical inference"
Narrow search

Narrow search

Year of publication
Subject
All
Performance measurement 5 Robust statistical inference 5 Cross-sectional dependence 3 Performance-Messung 3 Portfolio-Management 3 Schätzung 3 Estimation 2 Europa 2 Fama-French model 2 Kalendereffekt 2 Portfolio selection 2 2000-2005 1 Calendar effect 1 Europe 1 Measurement 1 Messung 1 Regression analysis 1 Regressionsanalyse 1 Theorie 1 Theory 1
more ... less ...
Online availability
All
Free 4
Type of publication
All
Book / Working Paper 5
Type of publication (narrower categories)
All
Working Paper 3 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2
Language
All
English 3 Undetermined 2
Author
All
Hoechle, Daniel 5 Zimmermann, Heinz 5 Schmid, Markus 1 Schmid, Markus M. 1
Institution
All
School of Finance, Universität St. Gallen 1 Wirtschaftswissenschaftliches Zentrum, Universität Basel 1
Published in...
All
WWZ Working Paper 1 WWZ working paper 1 Working Papers on Finance 1 Working papers / Wirtschaftswissenschaftliches Zentrum, Universität Basel 1 Working papers on finance 1
Source
All
ECONIS (ZBW) 2 RePEc 2 EconStor 1
Showing 1 - 5 of 5
Cover Image
Measuring long-term performance : a regression based generalization of the calendar time portfolio approach
Hoechle, Daniel; Schmid, Markus M.; Zimmermann, Heinz - 2012
Persistent link: https://www.econbiz.de/10010409214
Saved in:
Cover Image
A Generalization of the Calendar Time Portfolio Approach and the Performance of Private Investors
Hoechle, Daniel; Zimmermann, Heinz - 2007
We present a regression-based generalization of the calendar time portfolio approach which allowsfor the inclusion of continuous and multivariate investor or firm characteristics in the analysis. Ourmethod is simple to apply and it ensures that the statistical results are heteroscedasticity...
Persistent link: https://www.econbiz.de/10011390620
Saved in:
Cover Image
A Generalization of the Calendar Time Portfolio Approach and the Performance of Private Investors
Hoechle, Daniel; Zimmermann, Heinz - Wirtschaftswissenschaftliches Zentrum, Universität Basel - 2007
We present a regression-based generalization of the calendar time portfolio approach which allowsfor the inclusion of continuous and multivariate investor or firm characteristics in the analysis. Ourmethod is simple to apply and it ensures that the statistical results are heteroscedasticity...
Persistent link: https://www.econbiz.de/10009025076
Saved in:
Cover Image
A generalization of the calendar time portfolio approach and the performance of private investors
Hoechle, Daniel (contributor); Zimmermann, Heinz (contributor) - 2007
We present a regression-based generalization of the calendar time portfolio approach which allowsfor the inclusion of continuous and multivariate investor or firm characteristics in the analysis. Ourmethod is simple to apply and it ensures that the statistical results are heteroscedasticity...
Persistent link: https://www.econbiz.de/10003666367
Saved in:
Cover Image
Measuring Long-term Performance: a Regression Based Generalization of the Calendar Time Portfolio Approach
Hoechle, Daniel; Schmid, Markus; Zimmermann, Heinz - School of Finance, Universität St. Gallen - 2012
We present a new, regression-based methodology for decomposing the risk-adjusted performance of private investors, firms, and mutual funds. Our technique allows for the inclusion of multivariate and continuous subject characteristics in the analysis and it ensures that the statistical results...
Persistent link: https://www.econbiz.de/10010687533
Saved in:
A service of the
zbw
  • Sitemap
  • Plain language
  • Accessibility
  • Contact us
  • Imprint
  • Privacy

Loading...