Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
    data driven risk management in heatlhcare
    How Data Analytics Is Changing Healthcare Risk Management
    17 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Ralph Vince 2009 Leverage Space …
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Ralph Vince 2009 Leverage Space …
Uncategorized

Ralph Vince 2009 Leverage Space …

Editor SDC
Editor SDC
6 Min Read
SHARE

I read Ralph Vince’s new book, The Leverage Space Trading Model, this evening. It was released very recently on May 26th ’09. Previously I read one of his older books, The Handbook of Portfolio Mathematics. Vince writes about money management, i.e. position sizing, which tries to answer the question, “How much of my capital should I bet on any given trade in order to maximize my wealth over time”.

This one is much shorter at under 200 pages which is definitely an advantage over the previous. Overall, it’s an interesting read, but with big issues:
Vince seems to be living in an insulated world. He apparently hasn’t followed recent advances is portfolio optimization, and he is calls Monte Carlo extremely difficult. He is extremely critical of things he shows only a basic understanding of.
For example one of the major justifications he claims for his “new” theory is that mean-variance portfolio optimization (“modern portfolio theory”) doesn’t consider leverage. But in fact MVAR optimization is equivalent to Kelly criterion betting. In all his examples of MVAR he forgets the risk free asset, which allows for leverage to come into the optimization. Furthermore, Monte Carlo simulation …


I read Ralph Vince’s new book, The Leverage Space Trading Model, this evening. It was released very recently on May 26th ’09. Previously I read one of his older books, The Handbook of Portfolio Mathematics. Vince writes about money management, i.e. position sizing, which tries to answer the question, “How much of my capital should I bet on any given trade in order to maximize my wealth over time”.

This one is much shorter at under 200 pages which is definitely an advantage over the previous. Overall, it’s an interesting read, but with big issues:
Vince seems to be living in an insulated world. He apparently hasn’t followed recent advances is portfolio optimization, and he is calls Monte Carlo extremely difficult. He is extremely critical of things he shows only a basic understanding of.
For example one of the major justifications he claims for his “new” theory is that mean-variance portfolio optimization (“modern portfolio theory”) doesn’t consider leverage. But in fact MVAR optimization is equivalent to Kelly criterion betting. In all his examples of MVAR he forgets the risk free asset, which allows for leverage to come into the optimization. Furthermore, Monte Carlo simulation is trivial. Humorously he doesn’t seem to realize that his proposal is essentially equivalent to an approximate Monte Carlo.
He seems to have a tendency to become obsessed with one or two little problems of the mainstream/popular approaches to money management and now he lashes out against them, overdoing the nonconformity. He creates his own notation, metaphors, names for theories (he may simply not be aware of similar work), and as I mentioned above, he doesn’t really understand all the things he lashes out against. Overall it comes across sounding a little bit immature. Academic publishing is a long discourse, not a contest. Also, he sounds like he has a thesaurus on hand while he writes.
The last chapter is simply ridiculous. Basically he recommends that everyone should bet according to the scheme outlined in the St. Petersburg Paradox (Wikipedia). As I was reading it I kept thinking he would say it was a joke or just an idea to think about. But he’s really saying that banks, individuals, and funds should go out and use this strategy, because supposedly humans only care about being profitable with the highest probability (he gives a couple of loose justifications from cherry-picked psychology/econ utility theory works). Essentially he’s saying everyone should follow LTCM‘s strategy.
At the same time, if you can look past these issues, Vince has new ideas. The first few chapters will definitely expand your understanding of position sizing. I’m disappointed that Vince’s creativity couldn’t have illuminated more fruitful paths.
One thing I was thinking he may go into when I read the title of Chapter 6 “A Framework to Satisfy Both Economic Theory and Portfolio Managers” is applying optimal ‘betting’ to everyday non-financial choices. Any choice with an unknown outcome can be considered a bet, but some result non-monetary gains, and maybe he could have analyzed these similarly.
Overall, I was diappointed that he didn’t do more, but happy with the ideas I was able to selectively extract.

More Read

One Hit Wonders
More than a spelling error
Change, Vested Interests, and Creative Destruction
Satisfying Saturday: The Buzz on Google Buzz
Decision Management Event Calendar for June 12 2009
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Comparing 5 Top Compliance Training Providers for Large Businesses -- AI-generated illustration
Comparing 5 Top Compliance Training Providers for Large Businesses
Business Intelligence Exclusive
11 Best AI Tools for Critical Thinking in Research -- AI-generated illustration
11 Best AI Tools for Critical Thinking in Research
Artificial Intelligence Exclusive
Top 7 GTM Intelligence Tools with MCP Integration in 2026 -- AI-generated illustration
Top 7 GTM Intelligence Tools with MCP Integration in 2026
Artificial Intelligence Exclusive News
What Is Fine Tuning AI Models And When Should You Actually Do It? -- AI-generated illustration
What Is Fine Tuning AI Models And When Should You Actually Do It?
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

SQL Server – Drop database, drop current connections first

1 Min Read

Email & the Next Level

3 Min Read

Is Unstructured Collaboration the Key to Business Agility?

5 Min Read

Check out this Screencast on Wolfram Alpha, by the founder of…

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?