Statistical tests of stochastic process models used in the financial theory of insurance companies

Patrick L. Brockett, Robert C. Witt, Boaz Golany, Naim Sipra, Xiaohua Xia

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a statistical test allowing the analyst to determine if a given time series is statistically incompatible with being modeled as a linear or log-linear process. Since the commonly used models for financial time series of interest to insurance professionals are linear or log-linear, this paper allows the analyst to verify the linearity of the model under investigation, or else points to the necessity of non-linear modeling. We also show how to test for time series Gaussianity using the same type of statistical test statistic. These results are applied to several financial data sets relevant to the financial operations of insurance companies.

Original languageEnglish
Pages (from-to)73-79
Number of pages7
JournalInsurance: Mathematics and Economics
Volume18
Issue number1
DOIs
StatePublished - May 1996

Keywords

  • Financial time series
  • Statistical test
  • Stochastic process model

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

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