Skip to main content

Main menu

  • Home
  • Current Issue
  • Past Issues
  • Videos
  • Submit an article
  • More
    • About JOI
    • Editorial Board
    • Published Ahead of Print (PAP)
  • IPR Logo
  • 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 Investing
  • IPR Logo
  • About Us
  • Journals
  • Publish
  • Advertise
  • Videos
  • Webinars
  • More
    • Awards
    • Article Licensing
    • Academic Use
  • Sample our Content
  • Request a Demo
  • Log in
The Journal of Investing

The Journal of Investing

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

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

Risk-Constrained Kelly Gambling

Enzo Busseti, Ernest K. Ryu and Stephen Boyd
The Journal of Investing Fall 2016, 25 (3) 118-134; DOI: https://doi.org/10.3905/joi.2016.25.3.118
Enzo Busseti
is a PhD candidate in the Department of Management Science and Engineering at Stanford University in Stanford, CA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: ebusseti@stanford.edu
Ernest K. Ryu
is a PhD candidate in the Institute for Computational and Mathematical Engineering at Stanford University in Stanford, CA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: eryu@stanford.edu
Stephen Boyd
is the Samsung Professor of Engineering, and Professor of Electrical Engineering in the Information Systems Laboratory at Stanford University in Stanford, CA.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: boyd@stanford.edu
  • 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 authors consider the classic Kelly gambling problem with general distribution of outcomes and an additional risk constraint that limits the probability of a drawdown of wealth to a given undesirable level. They develop a bound on the drawdown probability; using this bound instead of the original risk constraint yields a convex optimization problem that guarantees the drawdown risk constraint holds. Numerical experiments show that this bound on drawdown probability is reasonably close to the actual drawdown risk, as computed by Monte Carlo simulation. This method is parametrized by a single parameter that has a natural interpretation as a risk-aversion parameter, allowing the authors to systematically trade-off asymptotic growth rate and drawdown risk. Simulations show that this method yields bets that outperform fractional Kelly bets for the same drawdown risk level or growth rate. Finally, they show that a natural quadratic approximation of the convex problem is closely connected to the classical mean–variance Markowitz portfolio selection problem.

  • © 2016 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 Investing: 25 (3)
The Journal of Investing
Vol. 25, Issue 3
Fall 2016
  • Table of Contents
  • Index by author
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 Investing.

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.
Risk-Constrained Kelly Gambling
(Your Name) has sent you a message from The Journal of Investing
(Your Name) thought you would like to see the The Journal of Investing web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Risk-Constrained Kelly Gambling
Enzo Busseti, Ernest K. Ryu, Stephen Boyd
The Journal of Investing Aug 2016, 25 (3) 118-134; DOI: 10.3905/joi.2016.25.3.118

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
Risk-Constrained Kelly Gambling
Enzo Busseti, Ernest K. Ryu, Stephen Boyd
The Journal of Investing Aug 2016, 25 (3) 118-134; DOI: 10.3905/joi.2016.25.3.118
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
    • KELLY GAMBLING
    • DRAWDOWN
    • DRAWDOWN RISK BOUND
    • RISK-CONSTRAINED KELLY GAMBLING
    • QUADRATIC APPROXIMATION
    • NUMERICAL SIMULATIONS
    • APPENDIX
    • ENDNOTE
    • REFERENCES
  • Info & Metrics
  • PDF (Subscribers Only)
  • PDF (Subscribers Only)

Similar Articles

Cited By...

  • Drawdowns
  • Adaptive Bet-Hedging Revisited: Considerations of Risk and Time Horizon
  • Google Scholar

More in this TOC Section

  • Editor’s Letter
  • COMMENTARY: Last Page
  • Editor’s Letter
Show more Article
LONDON
One London Wall, London, EC2Y 5EA
United Kingdom
+44 207 139 1600
 
NEW YORK
41 Madison Avenue, New York, NY 10010
USA
+1 646 931 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
  • Log In
  • Update your profile
  • Give us your feedback

© 2021 Pageant Media Ltd | All Rights Reserved | ISSN: 1068-0896 | E-ISSN: 2168-8613

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