|some kinda Wave Theory|
Fig.1 Price vs Time
The change in Slope is:
where ω2 is some (as yet unknown) positive constant of proportionality.
Rearranging terms, we get:
How to choose ω2 ?
If we rewrite equation (1) as a differential equation,
How to choose P0 ?
As a first effort, we choose for P0 the
Average Price Paid for the stock over the past
Here's an example of what we'd get, using equation (3) and substituting, each day, the two previous stock prices P(n) and P(n-1), with T=10 days and taking the VMA over the previous 20 days:
Fig.2 Predicting the Price P(n+1)
In this example, the direction of the changes in the Predicted price (UP or DOWN) agree with those of the actual price changes 77% of the time. (I'll call this the UP/DOWN Correlation ... why not?)
Also, the NEXT predicted price for May 8/98 is $16.40 whereas the actual price on May 8 was $16.09 (an error of 1.9%).
How to choose P(n) ?
Should P(n) be the Open? High? Low? Close? Average?
Aaah, that's the question ...
How about extrapolating ?
If we stop using the actual prices P(n) and P(n-1)
(at some point in time) and start using the previously
predicted prices, we get something like:
Fig.3 Extrapolating the Price
where, in the extrapolated portion of the graph, the chosen value of T = 6 is clearly evident (in that the predicted prices oscillate with a period of about 6 days). Further, the choice of a constant P0 = $16.75 results in our "predicted WAVE" oscillating about this value.
Fig.4 Predicting CBR
Fig.5 Extrapolating CBR
See: more Waves