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Manufacturing and Allied

  10 Download     📄   2 Pages / 329 Words

Assignment 


Group

Sector

Group 1

MANUFACTURING & ALLIED

Group 2

INSURANCE

Group 3

COMMERCIAL AND SERVICES

Group 4

CONSTRUCTION & ALLIED

Group 5

AGRICULTURAL

Group 6

BANKING TIER 1

Group 7

BANKING TIER 2

Group 8

ENERGY & PETROLEUM

Group 9

AUTOMOBILES & ACCESSORIES

Instructions

  1. Using Excel or R software refer to the Assignment data (NSE VWAP HISTORICAL PRICES 1Oct-12 to 25-Sep-15) to prepare a report on the stock prices as per the sector allocated to your group.
  2. For the final report - Submit your final report (strictly in pdf) and the supporting working file (Soft) in Excel or R before the Due date.
  3. The due date is – Monday, 30th November 2020. You are highly encouraged to consult me as you prepare the data for the analysis.
  4. The submission package should be properly referenced using APA style. No Plagiarism Allowed.
  5. The report should be based on measure of location, measure of dispersion, distribution of data and correlation analysis. Be sure to answer the following questions in your report.
  • Measure of Location
    1. Create a scatter plot. Around what values of price do the data tend to cluster?
    2. What is the mean sales price?
    3. What is the median sales price?
    4. Is one measure more representative of the typical stock prices than the others?
  • Measure of Dispersion
    1. What is the range of sales prices?
    2. What is the standard deviation?
    3. Is the standard deviation a useful statistic for describing the dispersion of data?
    4. Determine the coefficient of variations in each of the listed company hence determine which company had better results
  • Measure of distribution
    1. Compute the minimum, maximum, median, and the first and the third quartiles of price.
    2. Create a box plot. Comment on the distribution of stock prices.
    3. Create a histogram. Comment on the distribution of data using skewness and kurtosis.
    4. Hence suggest how this distribution may inform future decisions on performance of stock prices
  • Correlation analysis
    1. Using a scatter plot, describe the relationship between different companies in your respective sectors.
    2. Compute correlation coefficient and compare the results with part (a).
    3. Compute R squared and interpret.

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