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Post by tickingmask on Jul 16, 2017 15:41:18 GMT
For example, they assume that returns are normally distributed but prices are log-normally distributed. The book explained that it is because prices are never negative and bounded by zero from left. I think there's an even simpler explanation: asset values/prices, like virus or human populations, or any other self-perpetuating entity whose absolute rate of increase or decrease depends on the existing value, tend to vary exponentially rather than linearly. The book's 'never negative and bounded by zero' explanation is simply a result of that, not an underlying cause! That also ties in with the continuous compounded rates of return that you mention, since (1 + R/n) n tends to e R as n tends to infinity. (R = Effective annual rate, n = number of compounding periods per year).
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Post by Aj_June on Dec 3, 2018 14:00:37 GMT
log-normal distribution still gives me some trouble. Log-normal distributions tend to be used a lot in calculation of derivatives values where it is assumed (fairly dodgily, I might add) that market volatilities cause values of the underlying assets to do a time-based random walk abour a log-normal distribution. This is used as a basis for pricing methods like the Black Scholes model, for example. What else do you need to know? Hi....Where are you tickingmask? Hope you are doing well!
I am on to the Black Scholes model now! It's great to finally switch from discrete time models like binomial options pricing models to continuous time BSM model. This seems to be fascinating experience.
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