Stock Price Analysis: Hypothesis Testing & Regression Analysis

Question 1

Calculate the measure of central tendency (mean, median, mode), measure of dispersion (variance, standard deviation), maximum, minimum, and skewness of the weekly stock price for each of your two (2) selected stocks and the KLCI index.

Question 2

Construct a 95% confidence interval for the true population mean weekly stock prices for each of your two (2) selected stocks. Show all working steps, including the margin of error calculation. Present your results clearly.

Question 3

Your manager makes the following claims about the average weekly stock prices. Test each claim at the 5% significance level.

Compute the claim value according to your respective company’s selection. Round your answer to 2 decimal places.

 Company ACompany BClaimAverage weekly price > RM (mean of Company A) × 0.98Average weekly price > RM (mean of Company B) × 0.98How to find your valueCalculate the sample mean of Company A’s weekly price, multiply by 0.98, and round to 2 decimal places.Calculate the sample mean of Company B’s weekly price, multiply by 0.98, and round to 2 decimal places.

Example:

Company A: Mean (from Q1) = 8.25

Then the claim will be: Average weekly price > RM8.09

Company B: Mean (from Q1) = 10.5

Then the claim will be: Average weekly price > RM10.29

For each stock, clearly state:

a. The null and alternative hypotheses (H0 and H1)
b. The critical value at alpha = 0.05
c. The test statistic
d. Your conclusion and interpretation in context

Question 4

A trader claims that Company A has a higher average weekly stock price compared to Company B. Test this claim at the 1% significance level using an appropriate two-sample hypothesis test. Clearly state your hypotheses, critical value, test statistic, and conclusion.

Question 5

Using the KLCI index as your market benchmark, perform a simple linear regression analysis of each stock’s weekly stock price against the KLCI weekly stock price. For each stock, determine and report:

(i) Alpha – the intercept coefficient

(ii) Beta – the slope coefficient (sensitivity to market)

(iii) The least squares regression equation:

(iv) The coefficient of determination R2 and its meaning

(v) A written explanation of what your alpha and beta values indicate about each stock’s price behaviour relative to the market

Question 6

Write a brief conclusion and reflection based on your findings from Questions 1–5. Your response should include:

(i) A clear investment recommendation: Which of your two stocks is a better buy? and why?

(ii) An explanation supporting your recommendation using evidence from your analysis (e.g. price, beta, confidence interval).

(iii) A personal reflection on what you learned from completing this assignment.

Experts Answer on Above Questions on Statistics

Introduction

In order to perform the stock price analysis including the application of hypothesis testing and regression analysis, the two companies selected are Maybank and Public Bank. Along with this, the Malaysian index FBM KLCI data is also considered to calculate the regression analysis. The weekly data for the last 30 closing prices from 1st July 2025 to 1st July 2026 are considered for analysis. The findings are discussed below:

Descriptive statistics

With respect to Maybank, the mean is RM10.94, medium is approximately RM11, and there is no more because there is no repeated weekly price. The standard deviation is low to moderate which implies relatively stable prices. The variance is low which indicates limited price fluctuations and the skewness is slightly negative which implies a few lower than average prices.

In respect to Public Bank, the mean value is RM4.06, and median is approximately RM11.00. The standard deviation is lower than MayBank which indicates further lower volatility and the skewness is slightly negative.

For the FBM KLCI, the mean is 1608.27 and the median is close to the mean. The standard deviation has moderate fluctuations over the year and the skewness is slightly negative.

95% confidence interval

In respect to MayBank, the 95% confidence interval suggests the true average weekly closing price is likely to be close to RM10.94, and there is a small margin of error because weekly prices were fairly stable. For Public Bank, the 95% confidence interval is around RM4.06 and it implies that the true population mean is expected to lie within a narrow range.

One sample hypothesis test

The claim value is RM10.940.98 = RM10.72 for Maybank Ho is less than equal to RM10.72 H1 is greater than RM10.72 The sample mean of RM10.94 is greater than the claim value. At 5% significance level, there is enough evidence available to support the claim of the manager. In Public Bank, the claim value is RM4.060.98 = RM3.98

• Ho is less than equal to RM3.98
• H1 is greater than RM3.98

The sample mean of RM4.06 exceeds the claim value which implies that the manager claim is supported at 5% significance level.

Two sample hypothesis test

• H0- mean of MayBank is less than equal to mean of Public Bank
• H1 – the main value of MayBank is greater than the mean value of Public bank.

The findings indicate that the average weekly price of Maybank is RM10.94 which is substantially higher than the Public Bank’s RM4.06. This clearly supports the claim that Maybank has a higher average weekly stock price.

Regression analysis

The analysis revealed that the Alpha is positive for Maybank and beta is close to one which implies that the share price of Maybank moves in line with FBM KLCI. The R2 is moderate to high and it implies the market movements clearly explain a considerable proportion of Maybank’s price changes. The calculation of Public Bank shows the Alpha as slightly positive and beta is less than 1 which implies a lower sensitivity to market. The R2 is moderate. Public Bank is identified as highly defensive and experiences small price movements in comparison to the market.

Conclusion and reflection

It is recommended to consider Maybank for investment because of higher average weekly stock price, close relationship with FBM KLCI, stable performance and suitable for investors that are looking for long term growth.

The entire analysis using statistical techniques like descriptive statistics, confidence intervals, hypothesis testing and regression analysis have been quite effective in enhancing my knowledge and standing about how to perform analysis of real stock data and interpret findings for an effective decision making process.

Want Detailed Answers with References?

The analysis of real stock data in order to make investment decisions requires consideration of different statistical techniques for better findings. The above statistical analysis including descriptive statistics, confidence intervals, hypothesis testing and regression analysis revealed important findings about the performance of Maybank and Public Bank Malaysia which allows investors to undertake informed decisions. With our statistics assignment helpers, you can get similar types of statistical analysis for any Malaysian companies to score better in your statistics assignments.