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Introduction
Most companies and large businesses have continuously used spreadsheet software to keep records and analyze their financial performance. Specifically, the use of excel and other relative software has dominantly been used by financial analysts to analyze the firm’s performances since they allow for procedures and methodologies in computing and calculating eth changes in each firm’s performances. In the stock exchange market, the spreadsheet software has been used to analyze the trends in stock performances and determine the most performing stocks based on the variances and beta of each stock.
This software assists the analysts in making sound decisions based on the results computed and the financial output generated from each firm. In the current technological generation, where most business transactions are conducted online and by use of complex methods, spreadsheets have been continuously used to assist financial experts in analyzing the trends in various transactions and conducting procedural analysis by improving on the unique features that this software provider provides. Though the software is critical in measuring the risk and analyses the financial data of the stock performance, they are also limited in other areas as they do not allow for sound comparison of various company stocks and cannot explain the origin of the key changes in these stock performances.
Uses of Spreadsheet Software
The spreadsheet software allows the users to compute the financial data using the key features displayed in this spreadsheet. For example, Excel has various functions, including the average, standard deviation, variance, coefficient of variance, and the geometric mean, which an accountant can use to analyze the stock performance of various company stocks (Fisher, 2019). The spreadsheets also enable the users to critically assess the performance of stocks based on their risks and returns and the volatility of their performance to advise the potential investors on the best decision regarding the stock investment.
The software assists various departments in computing and analyzing the financial transactions originating from regular business activities. The key departments which use this software in the company include the finance, audit, marketing, human resource, and operations management departments (Eisner & Nadiri, 2020). The finance department uses spreadsheets to compute the overall performance of both financial and vital data, which affect the business operations. In addition, the finance department uses these spreadsheets to make sound decisions about the firm’s performance and reports the business status for easy interpretation and analysis.
The marketing department of various firms uses this software to analyze the trends in performances of various stocks and advice their clients on the best-performing stocks in the global market. In addition, the marketing department is interested in this software to enable them to analyze various financial data and evaluate the stock changes to assess their risks and returns to potential investors (Eklund, Palmberg, & Wilberg, 2018, para. 1).
The human resource and operations management teams are interested in this software to critically assess the need for recruitment and retention based on their company’s performance from the records and results presented by the financial department. The operations management also depends on the results presented to advise the company on the future business activities they can involve depending on the feasibility and viability of these projects (George, Howard-Grenville, Joshi, & Tihanyi, 2020).
Conclusion
In conclusion, the software has a wide range of uses in a complex environment. They enable the users to critically assess the various financial data presented in the global market through analyses of the key functionality available in this software. The use of spreadsheets has continuously been used in the recent business generation to assist the management and other stakeholders in making sound decisions on the best-performing company stocks for their investment plans (Eklund, Palmberg, & Wilberg, 2018, para. 3). Most businesses and large companies continue to gain from spreadsheets as they can analyze their reports prudently and report accordingly for the key users to make their decisions depending on the data presented to them.
Calculation of company Stocks
Compute the arithmetic and geometric mean return for large-company stocks and the corresponding standard deviation.
From the calculation, the arithmetic means, geometric mean and standard deviation of the large company stocks are 2.38, 1.03, and 0.93, respectively, indicating that these stocks are relatively strong in the market and show slight deviation in their means. The difference between the arithmetic mean and geometric mean is approximately 1.30 showing that there is high performance in the stocks of large companies.
Determine the coefficient of variation for large-company stocks and interpret your results.
The coefficient of variation of 39.24% means the poor performance of large-company stocks between 1994 and 2013.
Use the return data provided in the box and repeat steps 1 and 2 above for the small company stocks and the S&P 500 index and compare the risk/return relationships based on the coefficient of variation (CV).
Calculate the beta of large and small company stocks relative to the S&P 500 index and interpret your result.
In both the two stocks, there was a beta of 9.365 and 2.485, respectively, indicating that these stocks were more volatile than S&P stocks indices. The deviation between the large and small company stocks was higher than the average market indices in the stock exchange market.
Form an equally weighted portfolio of large and small stocks and compute the Reward-to-Risk Ratio (the slope of the Security Market Line).
Lower the weight of the equally weighted stock portfolio to 80 percent and add 20 percent US Treasury bills. Compute the resulting Reward-to-Risk Ratio. Increase the weight of US Treasury bills to 40 percent and 60 percent, repeat your computation, and interpret your results.
When the weighted stock portfolio of both the two company stocks is reduced to 80% and 20% treasury bills are added, the reward to risk ratio is reduced to 0.43 and 16.78, respectively, indicating that treasury bills, when added, decrease the general reward to risk ratio of stocks. Alternatively, when the weighted averages of the two company stocks are increased to 40% and 60% bills added further, there would be an increase in the reward to risk ratio of the two stocks from 2.03 and 18.38, respectively, showing that the addition of bills of more than 50% and increasing the weights further increases the general reward to risk ratio of company stocks.
References
Eisner, R., & Nadiri, M. (2020). Investment behavior and neoclassical theory. Review of Economics and Statistics, 50 (3), 369-382.
Eklund, J., Palmberg, J., & Wilberg, D. (2018). Inherited corporate control and returns on investment in small and large companies. An Entrepreneurship Journal.
Fisher. (2019). The theory of interest: Analysis of the impact of investment decisions in real-life situations. Macmillan, New York.
George, Howard-Grenville, Joshi, & Tihanyi. (2020). The investor communication strategies of newspaper corporations: A computerized content analysis. International Journal.
Prasanna, C. (2018 ). Investment analysis and portfolio management: Risks associated with investment decisions. MacMillan Books, 55-60.
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