Fooled by Randomness

Discussion in 'Trading' started by johnny88, Aug 19, 2009.

  1. johnny88

    johnny88

    Only reply if you know what Capital Asset Pricing Model (CAPM) is and have read the book Fooled by Randomness. Thanks.


    Question: How would you use CAPM and the Black Swan Principle to explain the severe decline in equity values in late 2008 and early 2009? One obvious is hidden risk that wasn't included in calculation of projected equity values. What are some others?
     
  2. Isn't it one of Taleb's beliefs that "CAPM is nonsense" (his own words)? He rejects the very assumptions that CAPM is based on.

    So how, pray tell, do you intend to reconcile two contradictory concepts to explain anything?
     
  3. trd

    trd

    I've written a small simulator that shows how it happens.
    The answer is: "GEARING" (similar to leverage).
    Say there are n listed companies, only 1 of them needs to make
    real profits so that its share price rises. The other n-1 companies
    need to just buy before shares of that company or of the other n-1 companies.
    If you orchestrate their chained activity intelligently (ie. who has to buy which shares and when etc.)
    then in the end all n companies will magically have rosen their value.
    But: in reality it is just only 1 company that made real profits, the profits of
    the other n-1 companies are economically seen not real, only shine profits.
    (sorry, for my english, but I think it should be clear what I try to say.)
    And: if one uses options then things are even more scariously "profitable"...
     
  4. But what does this have to do with CAPM?

    I might add that what might be more interesting is to consider the events of 2008 in light of Modigliani-Miller. I think that's a much more interesting line of inquiry, meself.
     
  5. The CAPM assumes that returns are Normally Distributed...
    An assumption which fails under extreme market conditions...
    Like when you get 3 or 4 or 5 Standard Deviation events.

    This is the heart of Taleb's thinking...
    Extreme events are more common than Normal Distribution would imply...
    Therefore one must use a Custom Distribution...
    With "fat tails" = extreme events are more common.

    All this has been common knowledge to options Pros since the early 80s...
    Taleb just rebranded "fat tails" as "Black Swans"...
    And built a Personality Cult around it.
     
  6. johnny88

    johnny88

    I fail to understand what you guys are talking about. But the CAPM equation is as follows. Risk free rate + Beta(Market Risk Premium). So what does this tell you in accordance with the mayhem we saw in 2008?
     
  7. johnny88

    johnny88

    Well for M&M model, we use capm to find return on equity don't we? So it is tied into it.
     
  8. For sure, but let's forget Taleb and the stupid swans when looking at it, shall we?

    Point is that the CAPM equation you're quoting follows from some assumptions that Taleb believes are totally unrealistic. So you can't combine his view of the world with the CAPM equation.

    Personally, I think Taleb's completely useless where constructive analysis of any sort is required. He hates CAPM, but doesn't offer an alternative analytical framework.
     
  9. johnny88

    johnny88

    I know he doesn't believe in CAPM etc. This question was asked in class and have to do a paper on it. I think I know the answer here now. He basically says we don't focus on the unpredictable risk in a firm, and we only focus on things like CAPM and M&M model for finding risk. How you would quantify unpredictable risk is beyond me. What would you say is an alternative to CAPM? Since we live in a imperfect world, capm with its assumptions is useless. We haven't really learned any other models extensively as M&M and CAPM. Thanks.
     
  10. trd

    trd

    "Black Swan" events are considered extreme outliers.
    Taleb himself is an extreme outlier, ie. a black swan himself!... :)
    A mathematician / statistician cannot take him for serious, IMO.
     
    #10     Aug 20, 2009