Quote from Thunderdog:
I'm not sure I unerstand what this means. They are either random or they are not. "Worse than random" is similar to "better than random" in that neither is random. At least that's how I see it.
Thanks for you comments thunderdog, as I find you one of the few posters I have come to respect on the boards.
I should be more specific. When I refer to random, I am implicitly referring to random in the gaussian sense.
Markets are very close to gaussian random and can be modeled as such if you remove the fat tail (black swan/10 sigma etc.. ) events. This is why when people run random generators on excel, they look so similar to market price action. It is also why most academics model them as such.
It is the frequent price shocks that make markets non(gaussian) random.
Note that while this implies they are not strictly (gaussian)random, the difference does not make the non-(g)random nature any more beneficial to modellers, rather it makes it worse (i.e. random, yet worse).
Often people jump in and argue about randomness and modeling without making the distinction. When I say worse than random, what I mean is that you could come up with a pretty reliable methodology based on random modeling, it's the fat tail shocks that killed many well thought out systems like LTCM. These 10 sigma type events are what make it worse than random IMO. On a smaller scale, you can think about gap up and gap downs, certainly those are are advatages (order flow) available to the specialist that can wipe out the uninformed trader who expects well defined random behavior to be on his side. Hope that defines it a little better. In this sense, I don't really see how unforeseen gaps (which are the fat-tail "non-gaussian random" events on a smaller scale) are in the retail trader's favor.
Statistics is a useful discipline. However, I think it has far more descriptive value than it has predictive value. Further, given that you cannot even assume a normal distribution for market price activity, but must rely on an even wider form of distribution, I would think that the use of statistical theory has fairly limited value in a short-term trading environment concerned with strict loss containment. Just my opinion, of course.
Regarding statistics, I am implying that structuring bets ( I.e. some form of risk management) hold more weight than betting based on reading charts.
The structured bets are useful against systems that have a random bias (like roulette machines for example).
I read a recent book on how norman leigh broke monte carlo's roulette machines based on a betting algorithm he devised. I think the key to success lies along these lines of thinking vs. reading charts and ascertaining future outcomes via expectations.
