Sure, the 2 main ways to represent time series data is using either a linear price scale, or a log price scale. Both have very distinct advantages, however it is worthwhile noting the entire history of the DJIA only makes sense using a log scale. It is consistent with the principle of the 'time value of money'.
Straight lines on a log chart are constant rates of change (% returns). On a linear chart, this same data is parabolic in an uptrend. Points of support and resistance appear in log charts that don't line up on linear charts, and vice versa.
The 'law of diminished utility' is a linear data set that relates to any portfolio of prices of any size. The best recent example is $goog, and explains perfectly why rising wedges work as high percentage bearish patterns. More importantly, diminishing utility relates to the capitalisation of the entire market, and portfolio size is irrelevant.
It is a mathematically certainty that linear price movements create diminished returns, using $goog as an example only. Consider $100 price moves from $500, $600, ... all the way to $1200. Initially, $100 is 20% of $500. But in the last stage of the trend $100 is 10% of $1000, and less as it goes higher from there. In order to maintain a constant rate of return on capital, $GOOG price *has to* go parabolic on a linear chart. If it goes linear, then the growth of capital being invested into $GOOG is diminishing, the equity risk premium reduces the r/r ratio. This is axiomatic, and the cause of cycles IMO.
National real (infl adj) GDP is another perfect example of linearity of growth that causes diminished rates of change. Because it *has to*. UK and US GDP trends are prime examples of diminished return.
Creating and maintaining non-linear price changes is the archilles tendon of capitalism - it is why the single largest return on capital is venture capital. IPO stage is into a secondary market often banking massive returns for venture stakeholders. When the reality of price valuations (of anything) becomes unsustainable, real money pulls out = drop in demand. Having monitored the 30 largest listed global funds for the last 2 years, real money funds (globally) is anything north of $10Bn that moves market prices.
Can do some charts on it to demonstrate it, the $goog 4hr is a cracker - but applies equally to any time series price chart.
(20min delay)