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Supported Intelligence, LLC
Industrydynamic programming, valuation, decision analytics
Founded2012
FounderPatrick L. Anderson and Anderson Economic Group, LLC
HeadquartersEast Lansing, Michigan,
United States
ProductsRapid Recursive™ Toolbox for MATLAB®
Websitewww.supportedintelligence.com

Supported Intelligence is a Michigan-based company that makes valuation, risk assessment and decision support software. Supported Intelligence’s primary product is the Rapid Recursive™ Toolbox for MATLAB®.

Rapid Recursive™ Toolbox

Supported Intelligence’s primary software product is the Rapid Recursive™ Toolbox for MATLAB®. This product allows end users to apply techniques from economics and dynamic programming to value elements of a business’ value, such as real options, that are omitted by traditional valuation methods, such as discounted cash flow. The Rapid Recursive™ Toolbox for MATLAB® also allows end users to analyse risky investment opportunities. For example, it allows users to analyse dynamic asset allocation strategies.[1]

History

Supported Intelligence was founded in 2012 by Patrick L. Anderson and Anderson Economic Group after six years of of research and development by Patrick L. Anderson.[2][3][4]

Patrick L. Anderson had been writing a book that analyzes traditional valuation methods as well as newer methods that use recursive methods and dynamic programming when he came up with the idea of producing commercial valuation and decision support software.[5] http://www.ogfj.com/articles/2012/09/irey-named-president-coo-of-supported-intelligence.html http://www.pitchengine.com/supportedintelligence/supported-intelligence-llc-announces-matthew-t-irey--as-president-and-coo

See also

References

  1. ^ Gerd Infanger. "Dynamic Asset Allocation Using Stochastic Programming and Stochastic Dynamic Programming Techniques".
  2. ^ CBS Detroit. "New Investment Analysis Software From East Lansing Firm".
  3. ^ CapitalGains. "Supported Intelligence To Help With Business Decisions, Creates Six Jobs".
  4. ^ Supported Intelligence. "New Software For Assessing Business and Investment Opportunities".
  5. ^ CBS Detroit. "New Investment Analysis Software From East Lansing Firm".

Further reading

  • R. E. Bellman. Dynamic Programming. Princeton University Press, Princeton, NJ, 1957. Dover paperback edition (2003), ISBN 0-486-42809-5.
  • Ronald A. Howard Dynamic Programming and Markov Processes, The M.I.T. Press, 1960.
  • D. Bertsekas. Dynamic Programming and Optimal Control. Volume 2, Athena, MA, 1995.
  • M. L. Puterman. Markov Decision Processes. Wiley, 1994.
  • H.C. Tijms. A First Course in Stochastic Models. Wiley, 2003.
  • J.A. E. E van Nunen. A set of successive approximation methods for discounted Markovian decision problems. Z. Operations Research, 20:203-208, 1976.
  • S. P. Meyn, 2007. Control Techniques for Complex Networks, Cambridge University Press, 2007. ISBN 978-0-521-88441-9. Appendix contains abridged Meyn & Tweedie.
  • S. M. Ross. 1983. Introduction to stochastic dynamic programming. Academic press
  • M. L. Puterman and Shin M. C. Modified Policy Iteration Algorithms for Discounted Markov Decision Problems, Management Science 24, 1978.
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