Journal article 1444 views 303 downloads
A General Quantile Function Model for Economic and Financial Time Series
Econometric Reviews, Volume: 35, Issue: 7, Pages: 1173 - 1193
Swansea University Author: Yuzhi Cai
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DOI (Published version): 10.1080/07474938.2014.976528
Abstract
This article proposed a general quantile function model that covers both one- and multiple-dimensional models and that takes several existing models in the literature as its special cases. This article also developed a new uniform Bayesian framework for quantile function modelling and illustrated th...
Published in: | Econometric Reviews |
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ISSN: | 0747-4938 1532-4168 |
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2016
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URI: | https://cronfa.swan.ac.uk/Record/cronfa21661 |
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2018-10-02T10:44:15.4816894 v2 21661 2015-05-22 A General Quantile Function Model for Economic and Financial Time Series eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2015-05-22 CBAE This article proposed a general quantile function model that covers both one- and multiple-dimensional models and that takes several existing models in the literature as its special cases. This article also developed a new uniform Bayesian framework for quantile function modelling and illustrated the developed approach through different quantile function models. Many distributions are defined explicitly only via their quanitle functions as the corresponding distribution or density functions do not have an explicit mathematical expression. Such distributions are rarely used in economic and financial modelling in practice. The developed methodology makes it more convenient to use these distributions in analyzing economic and financial data. Empirical applications to economic and financial time series and comparisons with other types of models and methods show that the developed method can be very useful in practice. Journal Article Econometric Reviews 35 7 1173 1193 0747-4938 1532-4168 German DAX, currency exchange rates, quantile functions models, Bayesian 1 3 2016 2016-03-01 10.1080/07474938.2014.976528 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University 2018-10-02T10:44:15.4816894 2015-05-22T14:34:08.0757839 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Yuzhi Cai 0000-0003-3509-9787 1 0021661-22022016103049.pdf CaiGeneralQuantileFunction2014AM.pdf 2016-02-22T10:30:49.7130000 Output 1011413 application/pdf Accepted Manuscript true 2015-10-22T00:00:00.0000000 true |
title |
A General Quantile Function Model for Economic and Financial Time Series |
spellingShingle |
A General Quantile Function Model for Economic and Financial Time Series Yuzhi Cai |
title_short |
A General Quantile Function Model for Economic and Financial Time Series |
title_full |
A General Quantile Function Model for Economic and Financial Time Series |
title_fullStr |
A General Quantile Function Model for Economic and Financial Time Series |
title_full_unstemmed |
A General Quantile Function Model for Economic and Financial Time Series |
title_sort |
A General Quantile Function Model for Economic and Financial Time Series |
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eff7b8626ab4cc6428eef52516fda7d6 |
author_id_fullname_str_mv |
eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai |
author |
Yuzhi Cai |
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Yuzhi Cai |
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Journal article |
container_title |
Econometric Reviews |
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35 |
container_issue |
7 |
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1173 |
publishDate |
2016 |
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Swansea University |
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0747-4938 1532-4168 |
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10.1080/07474938.2014.976528 |
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Faculty of Humanities and Social Sciences |
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Faculty of Humanities and Social Sciences |
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description |
This article proposed a general quantile function model that covers both one- and multiple-dimensional models and that takes several existing models in the literature as its special cases. This article also developed a new uniform Bayesian framework for quantile function modelling and illustrated the developed approach through different quantile function models. Many distributions are defined explicitly only via their quanitle functions as the corresponding distribution or density functions do not have an explicit mathematical expression. Such distributions are rarely used in economic and financial modelling in practice. The developed methodology makes it more convenient to use these distributions in analyzing economic and financial data. Empirical applications to economic and financial time series and comparisons with other types of models and methods show that the developed method can be very useful in practice. |
published_date |
2016-03-01T18:41:55Z |
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1821341400934907904 |
score |
11.04748 |