Quote from nfactorial:
This paper might be of interest:
"On the distribution of stock market data"
http://lit.jinr.ru/Reports/annual-report05/ShortLITReports2004_StockMarket-163.pdf
Quote:
"[...] for most stocks the distribution of the closing prices normalized by traded volumes fits well the log-normal function.
Do you see any practical implication?
Quote from braincell:
In mathematical theory, is it possible to create an automated strategy that will be profitable on a random walk chart?
Quote from braincell:
I've read ALL of the posts within this thread from the start. There have been some great interesting debates, minus the pissing match somewhere down the middle. Anyway, I have a question which pretty much makes the original question obsolete and should answer the most important thing
Here it is, especially for all you PhD guys.
Question:
In mathematical theory, is it possible to create an automated strategy that will be profitable on a random walk chart?
Assumptions:
We can assume we are running the random walk into infinity, and that the randomness of it cannot be predicted and doesn't follow any known model of random number generation (for example we use some unknown noise patterns for the value generation - like background space microwave radiation). By profitable I mean that if we run the random walk into infinity, the profits just keep increasing.
I think answering this questions answers a lot of others that have been raised during the discussions within this interesting thread.
Quote from MAESTRO:
Yes and no. There are no games that could be constructed on the 50/50 coin toss type of a process that have positive (or negative) expectations in the long (indefinite) run. The expectation for any strategy based on a 50/50 coin toss game is always zero (providing of course that we are not dealing with a bounded walk or have limited budget etc.) However, there are unlimited number of games that one could construct on BIASed (non 50/50) games as well on any random walk type of a process that have other than normal distribution. Thankfully, markets are not normally distributed; they are log-normal at best. It creates the opportunities to create strategies that exploit the market's âabnormalityâ in a very stable fashion.