AP/ECON 3210C Assignment

AP/ECON 3210C Assignment

Note: You are free to use any programming languages listed in the course outline, but I will focus the program of R for Assignment.

DUE DATE: Monday December 4th, 2023 11:59 pm, eclass Assignment Submission Site A penalty of 20 marks per day will be applied for late submissions.

STEP 1:  DATA COLLECTION

Choose 3 lists of 36 stocks on the TSX or NYSE fromhttp://eoddata.com/stocklist/TSX.htm

Your job is to pick 36 stocks based on your name.

If your name is David Lee, then DA-VI-LE can be your combination.

So

•   36 stocks whose symbols begin with D or A (call this the 1st basket)

•   36 stocks whose symbols begin with V or I (call this the 2nd basket)

•   36 stocks whose symbols begin with L or E (call this the 3rd basket)

•   So you have a total of 108 stocks

•   and get the daily high price for ALL of them on the same date (please record this date).

RULE:

•   CHOOSE STOCKS that have prices for multiple years (at least 3 years or more)

•   Select a particular date of any year.

•   Then get the daily high price. For example, if you collect the stock price of 108 stocks

from May 1, 2016, then collect the prices from May 1, 2017, and from May 1 of 2018 (± 1- 10 days).

•   Do not use stocks that have a negative price or a zero price (so you may need to initially select more than 108 stocks because some might need to be rejected if they have zero or negative prices - you need to end up with 108 stocks with non-zero and non-negative prices).

Data collection:

Go to this record in OMNI:https://ocul-

yor.primo.exlibrisgroup.com/permalink/01OCUL_YOR/1jocqcq/alma991022036369705164

Under view online, click on the link for Canadian Financial Markets Research Centre TSX

Summary Information Database:

STEP 2:  ANALYSIS

Your job is to answer the following questions.  For each question, you have to provide the computer output (copy-paste), then discuss if necessary.

Part 1: 5 Questions (50 marks)

1.   Data presentation (10 marks)

•   Use R or other programming languages (such as STATA, SAS, SPSS, etc) to show your  data collected.  Your data should be 108 observations with 3 or more columns (3 or more variables with appropriate variable names).

2.   Descriptive statistics (10 marks)

•   Use R or other programming languages (such as STATA, SAS, SPSS, etc) to show some descriptive statistics such as means, variances, standard deviations, outliers, data plots (boxplots) etc.

•   We require simple statistics and some graphical representation of each of the three or more variables that have been gathered.

3.   One-sample t test: (10 marks)

•   Test if there is a significant difference in the mean value of the price of the sets of stocks in the first year from the mean value of the price of the second year, at the α = 0.05 level of significance.

•   You have collected the data with three or more variables.  Choose one variable (one column) as a sample and choose the mean value of another variable.

•   Then carry on one sample t-test with the mean of the second year as the null hypothesis.

•   You must state the proper hypotheses, test statistics,p-value and conclusions.

4.   Two-sample t test (10 marks)

•   Test if there is a significant difference in the mean value of the sets of stocks between the two-year period, at the α = 0.05 level of significance (Carry on two-sample t-test).

•   You can choose any two years.

•   You must state the proper hypotheses, test statistics,p-value and conclusions.

5.   Compare the means for multiple years (10 marks).

•   Test the equality of the means for all the variables in your data.

•   You must provide the ANOVA table and state the proper hypotheses, test statistics, p- value and conclusions.

Part 2: 3 Questions (50 marks)

6.   Estimate a multiple regression model (20 marks)

•   Model:̂(y) =  β(̂)0  +  β(̂)1x1  + β(̂)2x2  + ⋯ … ..

•   Among the three or more variables (three or more columns), set one variable as Y and set the remaining variables as X1, X2, etc, and perform regression analysis.

•   Justify the scientific significance of the variable(s) and the estimated model with t test, F test, R-squared, adjusted R squared, etc.

•   For each test, you must clearly identify the null and alternative hypotheses, the statistic value, and the p-value and conclusion.