Estimating Qualcomm stock prices. As an example of the polynomial regression, consider data on the weekly stock

Question:

Estimating Qualcomm stock prices. As an example of the polynomial regression, consider data on the weekly stock prices of Qualcomm, Inc., a digital wireless telecommunications designer and manufacturer over the time period of 1995 to 2000. The full data can be found on the textbook€™s website in the following table.

Yd Wealth Year Interest Rate 1977 2992.1 3360.7 13786.3 -1.190 1978 3124.7 3527.5 14450.5 0.113 3203.2 3193.0 1.704 1979

During the late 1990, technological stocks were particularly profitable, but what type of regression model will best fit these data? Following figure shows a basic plot of the data for those years.

Price 500 450 400 200 150 Date 66/67/II 66/t/01 66/6/8 66/D1/9 66/61/ 2/22/99 86/87/71 86/7/1I 86/8/6 86/8 7/13/98 3/23/

This plot does seem to resemble an elongated S curve; there seems to be a slight increase in the average stock price, but then the rate increases dramatically toward the far right side of the graph. As the demand for more specialized phones dramatically increased and the technology boom got under way, the stock price followed suit and increased at a much faster rate.
a. Estimate a linear model to predict the closing stock price based on time. Does this model seem to fit the data well?
b. Now estimate a squared model by using both time and time-squared. Is this a better fit than in (a)?

c. Finally, fit the following cubic or third-degree polynomial:

Y_i = Î²₀ + Î²₁X_i + Î²₂X²_i + Î²₃X³_i+ u_i

where Y = stock price and X = time. Which model seems to be the best estimator for the stock prices?

Stocks
Stocks or shares are generally equity instruments that provide the largest source of raising funds in any public or private listed company's. The instruments are issued on a stock exchange from where a large number of general public who are willing...