کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
416691 681393 2006 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Bayesian testing for non-linearity in volatility modeling
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Bayesian testing for non-linearity in volatility modeling
چکیده انگلیسی

Neural networks provide a tool for describing non-linearity in volatility processes of financial data and help to answer the question “how much” non-linearity is present in the data. Non-linearity is studied under three different specifications of the conditional distribution: Gaussian, Student-tt and mixture of Gaussians. To rank the volatility models, a Bayesian framework is adopted to perform a Bayesian model selection within the different classes of models. In the empirical analysis, the return series of the Dow Jones Industrial Average index, FTSE 100 and NIKKEI 225 indices over a period of 16 years are studied. The results show different behavior across the three markets. In general, if a statistical model accounts for non-normality and explains most of the fat tails in the conditional distribution, then there is less need for complex non-linear specifications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 3, 1 December 2006, Pages 2029–2042
نویسندگان
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