Predictive Models Response

[Shannon]

Since I can't find the original prediction thread, I'll post my latest prediction with the models here.

This experiment is to see how accurate the models are when only one run is done. Usually I do a large number of runs and follow the average value.

This prediction is made on June 21st, 2020. The question was:

What will the average value of the American stock market for each month be in the next 6 months, relative to what it is today?

Results:

June: slight increase from here to the end of the month.
July: appears to be some instabilty which challenges the market, but it seems to maintain a relatively steady position for this month.
August: A significant, but unstable, increase.
September: A very large increase.
October: A serious crash, but far from the worst possible.
November: Market is "starting over", probably has small gains, but appears to remain at about where the crash left it.

Remember the following when considering what actually happens:
1. This is an experiment to see what happens when I don't repeatedly verify the data the models give. Can they accurately predict something as unpredictable as the stock market, when it is even less predictable during these crazy times, while only being run once - which should result in the least possible accuracy? I don't know. That's why we are doing this experiment.
2. These are for the average value of the American stock market as a whole during that month (or in the case of June, what's left of it).
3. This is NOT me showing off the models by making bold predictions to prove it works. I know it works. This is me trying to see how well it works when used in the worst possible ways against the most challenging possible targets.

I'm not giving investment advice here. This is an experiment. You should not consider this data valid until after this period of time has passed, and we can consider what actually happened to compare it to.