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A General Quantile Function Model for Economic and Financial Time Series

Yuzhi Cai Orcid Logo

Econometric Reviews, Volume: 35, Issue: 7, Pages: 1173 - 1193

Swansea University Author: Yuzhi Cai Orcid Logo

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...

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Published in: Econometric Reviews
ISSN: 0747-4938 1532-4168
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa21661
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last_indexed 2018-10-02T12:37:32Z
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spelling 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 BAF 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 Accounting and Finance COLLEGE CODE BAF Swansea University 2018-10-02T10:44:15.4816894 2015-05-22T14:34:08.0757839 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
author_id_str_mv eff7b8626ab4cc6428eef52516fda7d6
author_id_fullname_str_mv eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai
author Yuzhi Cai
author2 Yuzhi Cai
format Journal article
container_title Econometric Reviews
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container_issue 7
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publishDate 2016
institution Swansea University
issn 0747-4938
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doi_str_mv 10.1080/07474938.2014.976528
college_str School of Management
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hierarchy_top_title School of Management
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hierarchy_parent_title School of Management
department_str Accounting and Finance{{{_:::_}}}School of Management{{{_:::_}}}Accounting and Finance
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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 2016-03-01T03:32:08Z
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