Calculating Beta for Compuware Co. Essay Example
Calculating Beta for Compuware Co. Essay Example

Calculating Beta for Compuware Co. Essay Example

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When calculating beta for publicly traded companies on financial websites, the methods used can vary. Beta is a measure of an asset's risk compared to the market, but different websites have different assumptions and therefore calculate beta with different values. This can result in a variance in beta as high as 0.

50. In order to determine the assumptions made by websites to calculate their betas, we conducted several regression analyses using Compuware's stock return compared to the S&P 500 and Ken French's Fama-French Model. The assumptions are based on the assumption that both the S;P 500 and Compuware's stock return values are calculated on the same days as the data from Ken French's Fama-French Model.

It should be noted that beta's value can be significantly influenced by subtracting or selecting a different day to start the week or month. Thus, further investigation of thi


s factor is essential before making any assumptions. Moreover, discrepancies between Ken French's data and Yahoo finance's data were discovered, necessitating the removal of certain duplicated or mismatched days or weeks. The frequency at which stock returns are measured (daily, weekly, or monthly) has the most significant impact on beta. Our calculations indicated beta values ranging from 0.8310 to 2.

The difference in value at 0848 was 1.2538, primarily caused by the daily frequency. Daily frequencies had noticeably lower betas, likely because of the large volume of data points approaching the market efficient value. Excluding the daily frequency, the variance of the betas decreases to 0.6462. Changing the time periods used in calculating beta had significant effects on its actual value, possibly due to varying economic conditions in different years.

Sometimes our performance is good,

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while other times it might not be as good, and the value of beta will depend on the timeframe we consider. The impact of the risk-free rate on beta is relatively small, as demonstrated in Exhibit 1. When we include or exclude the risk-free rate from our calculations, we observe little change in the overall beta. This can be attributed to the stability of the risk-free rate during the analyzed time periods. If the risk-free rates were more volatile, we would expect to see a greater fluctuation when taking beta into account. Comparison between S&P 500 and...

CAPM - When comparing excess returns on the S&P 500 to the CAPM model using Ken French's data, we observe minimal differences in beta calculations. However, as we analyze shorter time frames, specifically monthly frequencies, we start to notice an impact. Notably, the monthly one-year betas exhibit greater variability compared to the monthly three or five-year betas. Given that Yahoo Finance and Reuters provide transparent explanations of their beta calculations, we can easily align our values with theirs.

When performing a regression analysis on the excess returns of the S;P 500 against a company's stock return, both the choice of time frame and the frequency of data recording greatly affect the beta. Therefore, it is important for analysts to be skeptical of betas without knowledge of how they were calculated. The ability to manipulate the parameters in calculating a beta should be acknowledged and justified. In essence, when calculating beta, it should be viewed as an estimation.

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