Journal article 1565 views
Forecasting for Financial Stock Returns Using a Quantile Function Model
World Academy of Science, Engineering and Technology, Volume: 9, Issue: 9, Pages: 753 - 756
Swansea University Author: Yuzhi Cai
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DOI (Published version): 10.5281/zenodo.1109383
Abstract
We introduce a newly developed quantilefunction model that can be used for estimating conditionaldistributions of financial returns and for obtaining multi-step aheadout-of-sample predictive distributions of financial returns. Since weforecast the whole conditional distributions, any predictive quan...
Published in: | World Academy of Science, Engineering and Technology |
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2015
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https://zenodo.org/record/1109383#.XZHyWkZKiBY |
URI: | https://cronfa.swan.ac.uk/Record/cronfa24734 |
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<?xml version="1.0"?><rfc1807><datestamp>2019-09-30T13:18:46.1086852</datestamp><bib-version>v2</bib-version><id>24734</id><entry>2015-11-25</entry><title>Forecasting for Financial Stock Returns Using a Quantile Function Model</title><swanseaauthors><author><sid>eff7b8626ab4cc6428eef52516fda7d6</sid><ORCID>0000-0003-3509-9787</ORCID><firstname>Yuzhi</firstname><surname>Cai</surname><name>Yuzhi Cai</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2015-11-25</date><deptcode>BAF</deptcode><abstract>We introduce a newly developed quantilefunction model that can be used for estimating conditionaldistributions of financial returns and for obtaining multi-step aheadout-of-sample predictive distributions of financial returns. Since weforecast the whole conditional distributions, any predictive quantityof interest about the future financial returns can be obtained simplyas a by-product of the method. We also show an application of themodel to the daily closing prices of Dow Jones Industrial Average(DJIA) series over the period from 2 January 2004 - 8 October 2010.We obtained the predictive distributions up to 15 days ahead forthe DJIA returns, which were further compared with the actuallyobserved returns and those predicted from an AR-GARCH model.The results show that the new model can capture the main featuresof financial returns and provide a better fitted model together withimproved mean forecasts compared with conventional methods. Wehope this talk will help audience to see that this new model has thepotential to be very useful in practice</abstract><type>Journal Article</type><journal>World Academy of Science, Engineering and Technology</journal><volume>9</volume><journalNumber>9</journalNumber><paginationStart>753</paginationStart><paginationEnd>756</paginationEnd><publisher/><keywords>DJIA, Financial returns, predictive distribution,</keywords><publishedDay>31</publishedDay><publishedMonth>10</publishedMonth><publishedYear>2015</publishedYear><publishedDate>2015-10-31</publishedDate><doi>10.5281/zenodo.1109383</doi><url>https://zenodo.org/record/1109383#.XZHyWkZKiBY</url><notes/><college>COLLEGE NANME</college><department>Accounting and Finance</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BAF</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2019-09-30T13:18:46.1086852</lastEdited><Created>2015-11-25T09:53:29.3354207</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Accounting and Finance</level></path><authors><author><firstname>Yuzhi</firstname><surname>Cai</surname><orcid>0000-0003-3509-9787</orcid><order>1</order></author></authors><documents/><OutputDurs/></rfc1807> |
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2019-09-30T13:18:46.1086852 v2 24734 2015-11-25 Forecasting for Financial Stock Returns Using a Quantile Function Model eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2015-11-25 BAF We introduce a newly developed quantilefunction model that can be used for estimating conditionaldistributions of financial returns and for obtaining multi-step aheadout-of-sample predictive distributions of financial returns. Since weforecast the whole conditional distributions, any predictive quantityof interest about the future financial returns can be obtained simplyas a by-product of the method. We also show an application of themodel to the daily closing prices of Dow Jones Industrial Average(DJIA) series over the period from 2 January 2004 - 8 October 2010.We obtained the predictive distributions up to 15 days ahead forthe DJIA returns, which were further compared with the actuallyobserved returns and those predicted from an AR-GARCH model.The results show that the new model can capture the main featuresof financial returns and provide a better fitted model together withimproved mean forecasts compared with conventional methods. Wehope this talk will help audience to see that this new model has thepotential to be very useful in practice Journal Article World Academy of Science, Engineering and Technology 9 9 753 756 DJIA, Financial returns, predictive distribution, 31 10 2015 2015-10-31 10.5281/zenodo.1109383 https://zenodo.org/record/1109383#.XZHyWkZKiBY COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2019-09-30T13:18:46.1086852 2015-11-25T09:53:29.3354207 Faculty of Humanities and Social Sciences School of Management - Accounting and Finance Yuzhi Cai 0000-0003-3509-9787 1 |
title |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
spellingShingle |
Forecasting for Financial Stock Returns Using a Quantile Function Model Yuzhi Cai |
title_short |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
title_full |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
title_fullStr |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
title_full_unstemmed |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
title_sort |
Forecasting for Financial Stock Returns Using a Quantile Function Model |
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eff7b8626ab4cc6428eef52516fda7d6 |
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eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi Cai |
author |
Yuzhi Cai |
author2 |
Yuzhi Cai |
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Journal article |
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World Academy of Science, Engineering and Technology |
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9 |
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9 |
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753 |
publishDate |
2015 |
institution |
Swansea University |
doi_str_mv |
10.5281/zenodo.1109383 |
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Faculty of Humanities and Social Sciences |
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facultyofhumanitiesandsocialsciences |
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Faculty of Humanities and Social Sciences |
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Faculty of Humanities and Social Sciences |
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School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Accounting and Finance |
url |
https://zenodo.org/record/1109383#.XZHyWkZKiBY |
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description |
We introduce a newly developed quantilefunction model that can be used for estimating conditionaldistributions of financial returns and for obtaining multi-step aheadout-of-sample predictive distributions of financial returns. Since weforecast the whole conditional distributions, any predictive quantityof interest about the future financial returns can be obtained simplyas a by-product of the method. We also show an application of themodel to the daily closing prices of Dow Jones Industrial Average(DJIA) series over the period from 2 January 2004 - 8 October 2010.We obtained the predictive distributions up to 15 days ahead forthe DJIA returns, which were further compared with the actuallyobserved returns and those predicted from an AR-GARCH model.The results show that the new model can capture the main featuresof financial returns and provide a better fitted model together withimproved mean forecasts compared with conventional methods. Wehope this talk will help audience to see that this new model has thepotential to be very useful in practice |
published_date |
2015-10-31T03:29:24Z |
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1763751141450973184 |
score |
11.0302305 |