Originally Posted by photoguy
I will note that he used rolling windows on a monthly basis. I think monthly is poor choice as this greatly inflates the number of data points on the graph and makes his model seem much stronger than can be justified statistically (because of the heavy amount of overlap, the data points on the graph aren't anywhere near independent, etc. etc.).
I agree. I assumed there was a data point for monthly 10 year rolling periods as they were way too many data points for yearly 10 year rolling periods over the time frame the graph was supposed to be for. I'd like to see these graphs done annually (by calendar year) for 10 year rolling periods.
If you look at Bogle's graph for a bigger dataset (1915-2014) you can see that this relationship no longer holds and a Bogle prediction of 6% yields an actual return centered around 6%. The problem is that 1990-2014 is such a short time period that you can get a lot of noise and spurious results.
Why didn't he use this graph? Even though there is more scatter, I think it shows his prediction method is on average in line with returns. Of course Bogle couldn't have been doing predictions way back to 1915. Was this the data he used to create his prediction formula and back test it?
I should have specified in my prior post - I don't really predict a return of 11% over the next 10 years, but I think it is just as good a prediction as Bogles - meaning I don't put much stock in either prediction.
But over the truly long term (say 40-50 years) I think 11% is more likely than 6% - but I probably won't be around to see if I'm right.