Quote from nLepwa:
Actually you change the relative magnitude because your normailzation factor isn't constant.
That way you can remove the fat tails.
Imagine you're at a coca-cola factory and you see all bottles coming out. You know that the content of each bottle is normally distributed with a mean 33 cl and std 1cl. In other words for 67% of the bottles the content is 32-34 cl and for 95% it is 31-35cl.
Now imagine that someone lets you bet on whether the next bottle you see will have less or more content than the previous one with a r:r 1:1. If the previous bottle had 36cl or 29cl it would be an easy bet right?
In trading I'm trying to set up the same kind of betting proposition.
Ninna
Quote from intradaybill:
This is a good example. Are we talking here Bayes prior statistics?
Actually, it is not an esay bet. It is a high probability bet. Maybe playing with words here but it makes a difference.
You have an unfair coin, heads is 0.05%. You see heads after a toss. Is it an easy bet? Actually, you can see heads a few more times and that can ruin you for good.

Quote from intradaybill:
I was not replying to you
Then, if you are using any technique available in any book, you are certainly not having an edge.
I know people that constantly fade the signals of that formula and make money at the expense of fools who read some technical analysis.
They have even devise projections to know when the fools will be placing tardes based on that and similar indicators.
Quote from RCG Trader:
Still looking for that edge rather than learning how to read price huh![]()
And you think the RSI will help you with this![]()
Good luck with that.
Quote from Kevin Schmit:
Seiously Ninna, I think you are giving away too much here.

Quote from dwpeters:
By normalizing market prices, do you mean something like detrending the price? For example creating a series that is difference of the price and a moving average? I have heard of the trend adjusted stochastic which I think incorporates this into the indicator.
I never covered these topics when I took statistics, or perhaps I forgot, but in looking up the definition of a gaussian process, it appears that it essentially describes something with a normal distribution. Since stock market returns do not have a normal distribution I don't know how you would convert them into something that does. I don't think simply detrending would do this.
Perhaps that is one of your trade secrets, in which case I understand if you don't want to elaborate for those of us that are statistically challenged.