Bayesian inference for the hazard term structure with functional predictors using Bayesian predictive information criteria

Tomohiro Ando

研究成果: Article査読

2 被引用数 (Scopus)

抄録

A Bayesian method for estimation of a hazard term structure is presented in a functional data analysis framework. The hazard terms structure is designed to include the effects of changes in economic conditions, as well as trends in stock prices and accounting variables from financial statements. The hazard function contains time-varying parameters that are modelled using splines. To estimate the model parameters, a Markov-chain Monte Carlo sampling algorithm is developed. The Bayesian predictive information criterion is employed to assess the default predictive power of the estimated model. The method is then applied to a Japanese firm's default data listed on the Japanese Stock Exchange. The results demonstrate that the proposed method performs well.

本文言語English
ページ(範囲)1925-1939
ページ数15
ジャーナルComputational Statistics and Data Analysis
53
6
DOI
出版ステータスPublished - 2009 4 15

ASJC Scopus subject areas

  • 統計学および確率
  • 計算数学
  • 計算理論と計算数学
  • 応用数学

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