Skip to main content

Main menu

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JFDS
    • Editorial Board
    • Published Ahead of Print (PAP)
  • IPR logos x
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

User menu

  • Sample our Content
  • Request a Demo
  • Log in

Search

  • ADVANCED SEARCH: Discover more content by journal, author or time frame
The Journal of Financial Data Science
  • IPR logos x
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Sample our Content
  • Request a Demo
  • Log in
The Journal of Financial Data Science

The Journal of Financial Data Science

ADVANCED SEARCH: Discover more content by journal, author or time frame

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JFDS
    • Editorial Board
    • Published Ahead of Print (PAP)
  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

Generating Virtual Scenarios of Multivariate Financial Data for Quantitative Trading Applications

Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Jorge Cubero, Maria Planas, Rafael Cobo and Fernando Pablos
The Journal of Financial Data Science Spring 2019, 1 (2) 55-77; DOI: https://doi.org/10.3905/jfds.2019.1.003
Javier Franco-Pedroso
was a research scientist at Audias-UAM in Madrid, Spain, at the time of writing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Joaquin Gonzalez-Rodriguez
is a researcher at Audias-UAM in Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jorge Cubero
is a data scientist at ETS Asset Management Factory in Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maria Planas
was a data scientist at ETS Asset Management Factory at the time of writing
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rafael Cobo
is a data scientist at ETS Asset Management Factory in Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fernando Pablos
is a managing director and head of research and development at ETS Asset Management Factory in Madrid, Spain
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Info & Metrics
  • PDF (Subscribers Only)
Loading

Click to login and read the full article.

Don’t have access? Click here to request a demo 
Alternatively, Call a member of the team to discuss membership options
US and Overseas: +1 646-931-9045
UK: 0207 139 1600

Abstract

In this article, the authors present a novel approach to the generation of virtual scenarios of multivariate financial data of arbitrary length and composition of assets. With this approach, decades of realistic time-synchronized data can be simulated for a large number of assets, producing diverse scenarios to test and improve quantitative investment strategies. The authors’ approach is based on the analysis and synthesis of the time-dependent individual and joint characteristics of real financial time series, using stochastic sequences of market trends to draw multivariate returns from time-dependent probability functions that preserve both distributional properties of asset returns and time-dependent correlation among time series. Moreover, new time-synchronized assets can be arbitrarily generated through a principal component analysis–based procedure to obtain any number of assets in the final virtual scenario. The validation of such a simulation is tested with an extensive set of measurements and shows a significant degree of agreement with the reference performance of real financial series—better than that obtained with other classical and state-of-the-art approaches.

  • © 2019 Pageant Media Ltd
View Full Text

Don’t have access? Click here to request a demo

Alternatively, Call a member of the team to discuss membership options

US and Overseas: +1 646-931-9045

UK: 0207 139 1600

Log in using your username and password

Forgot your user name or password?
PreviousNext
Back to top

Explore our content to discover more relevant research

  • By topic
  • Across journals
  • From the experts
  • Monthly highlights
  • Special collections

In this issue

The Journal of Financial Data Science: 1 (2)
The Journal of Financial Data Science
Vol. 1, Issue 2
Spring 2019
  • Table of Contents
  • Index by author
  • Complete Issue (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on The Journal of Financial Data Science.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Generating Virtual Scenarios of Multivariate Financial Data for Quantitative Trading Applications
(Your Name) has sent you a message from The Journal of Financial Data Science
(Your Name) thought you would like to see the The Journal of Financial Data Science web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Generating Virtual Scenarios of Multivariate Financial Data for Quantitative Trading Applications
Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Jorge Cubero, Maria Planas, Rafael Cobo, Fernando Pablos
The Journal of Financial Data Science Apr 2019, 1 (2) 55-77; DOI: 10.3905/jfds.2019.1.003

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Save To My Folders
Share
Generating Virtual Scenarios of Multivariate Financial Data for Quantitative Trading Applications
Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Jorge Cubero, Maria Planas, Rafael Cobo, Fernando Pablos
The Journal of Financial Data Science Apr 2019, 1 (2) 55-77; DOI: 10.3905/jfds.2019.1.003
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo LinkedIn logo Mendeley logo
Tweet Widget Facebook Like LinkedIn logo

Jump to section

  • Article
    • Abstract
    • ASSESSMENT OF SIMULATED FINANCIAL TIME SERIES
    • EVALUATION OF STOCHASTIC MODELS
    • GENERATION OF VIRTUAL SCENARIOS FOR MULTIVARIATE DATA
    • GENERATION OF NEW ARTIFICIAL ASSETS
    • ANALYSIS OF LONG-TERM HIGH-DIMENSIONAL VIRTUAL SCENARIOS
    • CONCLUSIONS
    • ACKNOWLEDGMENT
    • REFERENCES
  • Info & Metrics
  • PDF (Subscribers Only)
  • PDF (Subscribers Only)

Similar Articles

Cited By...

  • No citing articles found.
  • Google Scholar
LONDON
One London Wall, London, EC2Y 5EA
0207 139 1600
 
NEW YORK
41 Madison Avenue, 20th Floor, New York, NY 10010
646 931 9045
pm-research@pageantmedia.com

Stay Connected

  • Follow IIJ on LinkedIn
  • Follow IIJ on Twitter

MORE FROM PMR

  • Home
  • Awards
  • Investment Guides
  • Videos
  • About PMR

INFORMATION FOR

  • Academics
  • Agents
  • Authors
  • Content Usage Terms

GET INVOLVED

  • Advertise
  • Publish
  • Article Licensing
  • Contact Us
  • Subscribe Now
  • Sign In
  • Update your profile
  • Give us your feedback

© 2021 Pageant Media Ltd | All Rights Reserved | ISSN: 2640-3943 | E-ISSN: 2640-3951

  • Site Map
  • Terms & Conditions
  • Privacy Policy
  • Cookies