No. of Recommendations: 6
The first assumption we make in using the BMW method is that 'Average CAGR' is somewhat predictive of a stock's future CAGR. In other words, there is some expectation that future 'Average CAGR' will be similar to past 'Average CAGR', and that there will be some long-term fluctuation above and below the future Average CAGR line.

I prefer to use the longest data series available to determine Average CAGR.
The longer and tighter the data series, the more confidence I have that future Average CAGR will be close to past Average CAGR.
To baseline this idea, I assume that the future Average CAGR line will start from today's Average CAGR line (at the 0 RMS price).
However, I assume that the slope of the future Average CAGR line will be less than the Average CAGR line based on past price data. How much less slope depends on the length of the past data series (e.g. 40 years), and the amount of data scatter as measured by the spread between the RMS lines.

The way I have been doing this is to determine the slope of a line drawn from the 0 RMS point at the start of the data series - the left edge of the graph - to today's -2 RMS point.
I assume that slope and the future Average CAGR will be in the same ballpark, with the conservative assumption that the stock won't grow as fast in the long-term future as it has in its long-term past.

Sheridan's BMW charting tool had a feature to graphically determine this slope by connecting the oldest 0 RMS point and today's -2 RMS point. Unfortunately, the tool no longer works.

Here is how to determine the slope using math.

We need the following input variables:
A = Average CAGR expressed as a decimal (i.e. 12.0% --> A = 0.12)
Y = years of data used to calculate Average CAGR (40 years in this example)
R = the Return Factor associated with one unit of RMS. (This is the RF of a stock when the price is at the -1 RMS line. The value of R reflects the 'tightness' of the BMW chart; R close to 1 is tight. Larger R reflects more scatter in the price data around the Average CAGR line.)
R can be calculated as (1 RMS price) / (0 RMS price) from the Klein charts.

The output variable is F (future Average CAGR) expressed as a decimal, which can be converted to a percentage.

F = ( ( ((1+A)^Y) / (R^2) )^(1/Y) ) -1

Dividing by the expression (R^2) is what causes the line to shift the line downward by 2 units of RMS over the period Y years.
Using 2 units of RMS was an arbitrary choice on my part.
I could have used /R to shift downward just 1 unit of RMS, or /(R^3) by 3 units of RMS.

Another concept I am chewing on is to use /(R^R). That would penalize tight data just a little, and scattered data a lot more, which could be helpful for the BMW method to self-select suitable stocks. More on that later.
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