Re: rpietila Wall Observer - the Quality TA Thread ;)
Eureka! It is this simple:
- Every predictor gives two prices in log scale eg. "In 2014-5-16 the price is between 2.7 and 2.85 (roughly 500 and 700)"
- When the actual price is known, you take min [ abs ( actual - upper_limit); abs ( actual - lower_limit) ]
- Whoever has the lowest average error after a reasonable number of predictions (predictions can be renewed as often as you wish regardless of their maturity) is the best!
- Proof omitted
- Every predictor gives two prices in log scale eg. "In 2014-5-16 the price is between 2.7 and 2.85 (roughly 500 and 700)"
- When the actual price is known, you take min [ abs ( actual - upper_limit); abs ( actual - lower_limit) ]
- Whoever has the lowest average error after a reasonable number of predictions (predictions can be renewed as often as you wish regardless of their maturity) is the best!
- Proof omitted
I would be very grateful if you could explain this to a simpleton like myself.
Whoever was the closest to the actual price with the narrowest range was the best. I think he's being a little facetious here, because this is, of course, obvious.