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

The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach

Gueorgui Konstantinov and Mario Rusev
The Journal of Financial Data Science Winter 2020, 2 (1) 24-44; DOI: https://doi.org/10.3905/jfds.2019.1.017
Gueorgui Konstantinov
is senior portfolio manager of fixed income and currencies at LBBW Asset Management in Stuttgart, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mario Rusev
is senior consultant at d-fine Austria GmbH, in Vienna, Austria, and a graduate student at the Mathematical Institute at the University of Oxford in Oxford, UK
  • 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

The main goal of this article is to show the relation between global equity and bond funds from a network perspective. The authors demonstrate the advantages of graph theory to explain the collective fund dynamics. The results show that equity and bond funds have a significant exposure to the Fama–French–Carhart factors. The authors argue that the network is dynamically driven by equity funds with their centrality scores and risk factor exposure and can transmit and amplify system-wide stress or inefficiencies in the factor bets. Using graph theory, the authors demonstrate that the return-based relationships between bond and equity funds are asymmetrical and the network is sufficiently clustered. Specifically, equity funds connect the different clusters. The HML factor is significant both on a single-fund level and as a web determinant. Therefore, investors should pay close attention to it when managing funds and deriving asset allocations. Finally, the authors provide a machine learning approach to how fund managers, plan sponsors, and analysts can derive equity–bond allocations, based on centrality scores, factor exposure, and hierarchical clustering of asymmetrically connected assets.

TOPICS: Equity portfolio management, statistical methods, simulations, big data/machine learning

Key Findings

  • • The authors use topology and a concept from physics to show strong–weak return- and factor-based relationships between global equity and bond funds using a directed network approach.

  • • The Fama–French–Carhart factors determine an asymmetrical bond–equity fund relation and different fund clusters. The network exhibits a structure that differs according to the market cycle. Equity funds play the most central role in the market and connect the different clusters.

  • • Investors can use the bond–equity interconnectedness and network topology in multiple ways. The authors show that simple passive allocations, fund-of-funds solutions, and cluster-wise control for risk factors are some of the possible applications.

  • © 2020 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: 2 (1)
The Journal of Financial Data Science
Vol. 2, Issue 1
Winter 2020
  • 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.
The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach
(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
The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach
Gueorgui Konstantinov, Mario Rusev
The Journal of Financial Data Science Jan 2020, 2 (1) 24-44; DOI: 10.3905/jfds.2019.1.017

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
The Bond–Equity–Fund Relation Using the Fama–French–Carhart Factors: A Practical Network Approach
Gueorgui Konstantinov, Mario Rusev
The Journal of Financial Data Science Jan 2020, 2 (1) 24-44; DOI: 10.3905/jfds.2019.1.017
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
    • DATA
    • HOW TO MEASURE EQUITY AND BOND FUNDS’ CONNECTIVITY?
    • THE NETWORK, RISK FACTORS, AND FUND DYNAMICS
    • THE FAMA–FRENCH–CARHART FACTOR-BASED CONNECTEDNESS AND BEYOND
    • IMPLICATIONS FOR INVESTMENT MANAGERS
    • ADDITIONAL TESTS AND ROBUSTNESS
    • CONCLUSION
    • ADDITIONAL READING
    • ACKNOWLEDGMENTS
    • APPENDIX
    • ENDNOTES
    • REFERENCES
  • Info & Metrics
  • PDF (Subscribers Only)
  • PDF (Subscribers Only)

Similar Articles

Cited By...

  • Interactions and Interconnectedness Shape Financial Market Research
  • 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