Quote from MAESTRO:
I would like to point out a little gem that, in my point of view, is relevant to this discussion. The advantage of using something similar (but not quite) to ârange barsâ is to present the price-time series in the format that is a lot more Gaussian than one can imagine. Example: If you take an S&P 500 chart for the last 40 years or so and try to run the frequency distribution analysis you would soon find out that it looks like Log-normal or Power Low distribution. If you then plot a chart that presents the daily close price divided by an Average daily ATR (average true range) you will easily find that the chart looks totally different and it is 100% Gaussian! This leads to so many implications! The golden nugget here, of course, is presenting the price movements in the units of its volatility! This influenced dramatically the way I look at the markets and led to the development of the whole slew of successful trading strategies.
I find this particularly fascinating given that I am currently working with markets relative to random number distributions.
If you don't mind clarifying (I don't expect a free lunch here, I just don't quite understand one part) -- relative to what are you taking the 'frequency' for the S&P 500 chart? Overall price levels? Price levels on there own, being continuous, don't seem to lend themselves to frequency distribution tables without some form of normalization. Currently, I have been examining distance from the 200DMA -- but I don't think this is what you mean.
Am I misunderstanding?
Thanks for the insight.
Just think; it will come to you... I promise