First off let me begin by saying that I'm brand new to statistics and I would appreciate it if you could dumb down any answers for my problem.
I am trying to create a general prediction of how much a stock will go up in value in the following 7 days. What I have done is get a list of all percentages that the stock went up for each 7 day period, I got a list of the inputs and performed a multiple regression formula and received the coefficients for each input (3 inputs). I tested the coefficients for each stock and they are between 0.9 and 1 which I understand is very good.
Predicted Return = ((Rating1 * Rating1Coef) + (Rating2 * Rating2Coef) + (Rating3 * Rating3Coef)) * rsquared
I then went back over the list of all percentages that the stock made for each 7 day period and compared it to my predicted value using the inputs and the coefficients and below is a list of stocks and the percentage of how often my prediction was correct (i.e. my prediction was lower than how much the stock actually made)
Symbol | Probability of Predicted < Actual | Avg Pct Difference of Predicted vs Actual JNUG | 72.26% | -44.80% TLL | 6.22% | -58.44% TKMR | 14.45% | -44.64% ENRJ | 14.64% | -48.18% GENE | 21.90% | -17.39% ZIOP | 14.06% | -25.15% DWTI | 52.46% | 22.78% DGAZ | 93.41% | -107.66% SQQQ | 5.71% | -63.30% ASPS | 17.18% | -81.11%
- Is there any information that you need to know that I'm leaving out?
- What general steps can I take to increase the probability of choosing an amount that is close to the actual amount?
- Since my rsquared values are all fairly high, this just means that the predicted value will come close to the average amount that the stock made with similar inputs right?