Next Article in Journal
Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta
Previous Article in Journal
Oil Prices, Credit Risks in Banking Systems, and Macro-Financial Linkages across GCC Oil Exporters
Article Menu

Export Article

Open AccessArticle
Int. J. Financial Stud. 2016, 4(4), 24; doi:10.3390/ijfs4040024

Model Selection Test for the Heavy-Tailed Distributions under Censored Samples with Application in Financial Data

Department of Mathematics and Statistics, Lahijan Branch, Islamic Azad University, Lahijan 4416939515, Iran
Academic Editor: Nicholas Apergis
Received: 19 June 2016 / Revised: 24 November 2016 / Accepted: 1 December 2016 / Published: 13 December 2016
View Full-Text   |   Download PDF [2523 KB, uploaded 13 December 2016]   |  

Abstract

Numerous heavy-tailed distributions are used for modeling financial data and in problems related to the modeling of economics processes. These distributions have higher peaks and heavier tails than normal distributions. Moreover, in some situations, we cannot observe complete information about the data. Employing the efficient estimation method and then choosing the best model in this situation are very important. Thus, the purpose of this article is to propose a new interval for comparing the two heavy-tailed candidate models and examine its suitability in the financial data under complete and censored samples. This interval is equivalent to encapsulating the results of many hypotheses tests. A maximum likelihood estimator (MLE) is used for evaluating the parameters of the proposed heavy-tailed distribution. A real dataset representing the top 30 companies of the Tehran Stock Exchange indices is used to illustrate the derived results. View Full-Text
Keywords: asymptotic distribution; censored sample; heavy-tailed distribution; model selection test; Tehran Stock Exchange asymptotic distribution; censored sample; heavy-tailed distribution; model selection test; Tehran Stock Exchange
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Panahi, H. Model Selection Test for the Heavy-Tailed Distributions under Censored Samples with Application in Financial Data. Int. J. Financial Stud. 2016, 4, 24.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Int. J. Financial Stud. EISSN 2227-7072 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top