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    Tip: Don't take trading advice from HR.

    (ooooh)
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    (Original post by love2learn)
    Lots of the books I've read / flicked through have come to the general conclusion that the financial markets are random, and although assumptions / distributions can be used most of the time, they do not hold enough for it to be true that the markets follow those distributions (ie. normal etc..). Therefore, if a market isn't following a distribution, it is unable to be truely modelled and therefore fully predicted. It then follows that as it is clearly not possible to know what will happen, that trading becomes less about skills / knowledge / football ability / whatever and more about the random factor, which is just luck.

    I'm well aware of certain prevalent trends, and I'm not saying that the markets are truely efficient, but think about recent trends. There are far too many crashes for it to be non-random - eg. the recent subprime crash
    :rolleyes:
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    (Original post by President_Ben)
    Tip: Don't take trading advice from HR.

    (ooooh)
    Why, did you find out the hard way? :p:
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    (Original post by Jan)
    :rolleyes:
    I think that what Jan means to point out is that you're confusing "random" with "Gaussian". Of course markets are random. The question is whether their randomness is Gaussian (i.e. easy to deal with) or whether it follows some other, unknown, distribution (i.e. hard to deal with). The problem is an epistemological one - we can only get information about a distribution by sampling, but without knowing what the distribution is we don't know how many samples we need to determine the distribution. Truly a vicious circle!

    Actually, **** it. Jan summed it up better than I did.
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    Heh...

    That's the epistemological problem with the idea of probability as a whole is it not? To what extent is a probability distribution a useful mathematical device for approximating deterministic behaviour in a system (e.g. coinflip) as compared to something which is fundamentally random (i.e. Quantum Mechanics).
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    (Original post by Cexy)
    I think that what Jan means to point out is that you're confusing "random" with "Gaussian". Of course markets are random. The question is whether their randomness is Gaussian (i.e. easy to deal with) or whether it follows some other, unknown, distribution (i.e. hard to deal with). The problem is an epistemological one - we can only get information about a distribution by sampling, but without knowing what the distribution is we don't know how many samples we need to determine the distribution. Truly a vicious circle!

    Actually, **** it. Jan summed it up better than I did.
    Hope that you're planning on giving another lecture with Piers next year.
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    Yes, there's the whole 'determinism vs probability' debate, which I think is what you're referring to. I find it fairly uninteresting myself - I find it much more gratifying to extend probability to cover situations where our knowledge is fundamentally or practically incomplete and go from there. Drop all considerations of whether a system is 'really' deterministic or probabilistic, and use the theory of probability in the way that it should be used - to help us make good decisions when we lack information.

    That's subtly different to the problem that I was alluding to, though. IF you expect that some process is modeled by a distribution, and you want to find out what that distribution is, then how do you work it out? The answer is that you can't if you want complete accuracy, although there are tools to help you if the data is basically well-behaved (i.e. if it's Gaussian or something nearby). There's a whole literature on time series and monte carlo inference that you can bone up on if you're sufficiently interested in that kind of thing.
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    (Original post by Jan)
    Hope that you're planning on giving another lecture with Piers next year.
    I will if he invites me back! I have a whole load of new ideas which I hope to test out on some unsuspecting audiences over the summer. Most of which have dubious historical or mathematical content, admittedly, but I think I should be able to weasel them in nonetheless...
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    Something very important that no one has mentioned is the factor of human intuition; it's enough to bring trading away from randomness and into profitability.

    The fact is that markets are controlled by people, and hence have a degree of predictability. The trader with the better intuition - who picks up on the same vibes as everyone else in the markets - will do better on average.
 
 
 
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