Risk Analysis Stress Test for Your Personal Portfolio

As anyone who has read a few of my blog entries knows, probably all too well, I believe that Monte Carlo simulation has been unfairly maligned for its role in derailing the economy.   This month in his column for Seeking Alpha, Geoff Considine made this point a lot better than I’ve been able to make it, and he also made it more fun.  Considine, who works for a firm that develops specialized Monte Carlo software for investors, offers a detailed recipe for stress testing your personal investment portfolio.  
Of course, his recipe makes use of his company’s software.  But you could use the same recipe with the same ingredients in any Monte Carlo Excel spreadsheet (and here I don’t see any need to hide my own risk analysis affiliation) and bake up the same pie charts.

What’s good about his recipe is that it walks you through the assumption stages of model building quite carefully.  What’s fun about his recipe is that his hypothetical example, which uses a straw man named Bob, is retrospective, and he constructs a model that begins in 2007 and runs forward from there.  This means Considine has an opportunity to second-guess the assumptions–such as asset value, value-at-risk, and probabilities of worst-case scenarios–that brought down the house in 2008.

Of course, mortality tables being what they are, Bob dies in the end.  But Bob doesn’t fail, he goes out the smart way.   

Join the Conversation


  1. Would have a @Risk model comparable to the model used by Geoff Considine?

    It would be interesting to compare results.

    Thank you

  2. Hi–I just ran across your post. Thanks for the discussion of my article. Yes, my articles do emphasize quantext portfolio planner, our own tool, but the process I laid out can be used with ANY MC software–and @Risk would be a fine choice. The output would vary, of course, depending on the projected asset class returns and risks from the model. I’d be interested in seeing a comparison too. If you are interested, please contact me.



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