Financial and statistical tools are quite significant in any analyst’s study as it offers the best values to the analyst to make better decision (Bandy, 2013). Here, in the report, various statistical tools such as regression analysis, correlation etc has been studied to identify the performance of Telstra Company’s stock price in last 10 years.
Beta is a measurement tool to identify the volatility in the stock in context with the overall market. It is also known as systematic risk of the company.
In Part 1, Asset beta has been found. Asset beta is used to calculate the volatility in the stock prices. This beta takes the consideration of company’s leverage from the capital structure of the company (Borio, 2015). This beta has been used in Part 1 to identify the changes which have occurred in Telstra in last 10 years.
Financial ratios are used to determine the relationship among the financial items of the company. In part 1, four financial ratios have been calculated to identify the performance of the company in last 10 years for comparison purpose and identify the trend in the company. Firstly, P/E ratio has been calculated. PE ratio measures the market price of the company against the total earnings of the company. This ratio is mainly calculated by the financial analysts to identify the relative worth of the company.
Further, Debt to equity ratio is calculated to identify the long term obligation management of the company. This ratio measures the degree of an organization to fund its debt through the available equity funds. Moreover, Times Interest Earned measures the ability of the organization to pay its debt obligation by using the current income of the company. Lastly, market value to book value ratio is used to identify the business’s net assets against the sale price of shares of the company (Gitman and Zutter, 2012). It is used by the financial analyst to identify the market position of the company. Hence, the above mentioned ratios are quite useful for the analyst to make decision about the company.
R Square Meaning
R Square is a statistical tool which denotes the proportion of variances for a dependent variable. In other words, it shows how data are close on the regression analysis. As given in the example file, the R square of regression is 0.344. It denotes that the data are to so close on the fitted line (Borio, 2015).
R square and P value
Based on Part 1, R square and P value of Beta and all the financial ratios of the company have been calculated and it has been found that Beta vs. DE and Beta vs. MV/BV are not significant due to the fact that α < p. In these cases, the models are explaining the variation of data and thus it is not considered as significant. Rest all the ratios are denoting the significant values. Lastly, the Beta Vs all the ratios have been measured and found that the model is significant because significant X variable is included.
Correlation denotes whether two variables are linked to each other and how strongly they are linked. In case of Beta to PE, Beta to TIE, Beta to MV/BV and P/E to MV/BV, it has been found that correlation is positive which denotes that increment in one variable will lead the other variable towards increment and vice versa (Brigham and Ehrhardt, 2013). In case of other variables, it has been found that they have negative correlation with each other that means if one variable is leading towards positivity, the other will lead towards negativity.
Beta analysis in context with ratios
Based on the analysis in time series analysis, it has been found that Beta was constant with each of the ratios. However, while studying the regression analysis, it has been found that beta has changed with each of the variable, along with the R square and p values because of the fact that the variables are not getting fitted into the same regression analysis (Grinblatt and Titman, 2016).
To conclude, each statistical tool is different to each other and offer different relevant information. In case of Telstra, it has been found that the performance of the company has been changed a lot in last 10 years and it is important for the analyst to identify all the factors before making any decisions.