In this model, we use the midline of our exponential regression rainbow (green line) to give us
insight into the "fair value" of HEX.
To supplement this model, we take an "n-day moving average" of the extension from our exponential fit.
For example: on day 200, the value of this "n-day MA" is a 200-day MA. By definition, this moving average will reduce in volatility over the long-term as every day it averages over longer lengths of time.
We then multiply this n-day moving average by our monotonically increasing exponential fit. After doing some statistics on price action relative to this dynamic average, we obtain a standard deviation (defined by ratios: actual/expected versus the traditional differences: actual-expected) with which we can define a "Gaussian channel".
We know that Gaussian distributions should contain:
~99.7% of data within 3 standard deviations from the mean,
~95.5% of data within 2 standard deviations from the mean,
~68.3% of data within 1 standard deviation from the mean,
and therefore might expect price action to be bounded by these curves in a similar fashion.
The chart below plots HEX's price and its Gaussian Channel.
How To Use
Long term HEX investors can monitor the daily price relative to this channel. Historically, we've seen that the price of HEX stays within the bounds of this channel nearly 100% of the time.
Gerardo - @gerawrdog