Even though the researcher designed and conducted the thesis in the most possibly proper way, there are still some existing constraints that affecting the research result.
Concerning companies choice, there should have been much more sample companies to be studied in order to obtain better outcomes. Because the thesis aims at addressing the intrinsic value of US technology companies and the financial growth of companies in technology sector since the technology crisis 2000s, such objectives are large at an industrial and national scale, it requires a large number of companies to be analyzed so that the result would be more convincing and exact. However, this thesis will be an enormous work consuming lots of time and effort if analyzing a large amount of companies. Therefore, the researcher chose thirty biggest companies by market capitalization in the technology sector that qualifies for certain requirements of the research methodology to conduct the research. It doesn’t mean that the company choice is not relevant and just a temporary plan, it just cannot illustrate the analysis as well as a bigger company population can.
Regarding performance growth of sample companies, although price-to-earnings ratio is the most commonly used ratio to measure financial health of companies, the
application of only this metric cannot efficiently capture all the inherent risk as well as the potential growth of the sample companies. This ratio only is helpful to bear the relationship between the stock price with monetary benefit of the stock-earnings, hence, it just builds up a small part of the big picture of the companies’ performance.
Instead, the combination of more metrics should have been applied so as to gain better insights in companies’ financial position over the time frame.
In conducting discounted free cash flow model to determine the companies’ present value, there are various inherent limitations. First, historical data used to estimate future free cash flow is not really optimal as old performance is not always able to bear good prediction for future development of companies. In some cases, the present value of the company has negative value since in previous years, the company’s structure of earnings and spending was not balanced when the company made huge reinvestment in new technology, innovation or corporate management. That is, even though in the past, the company’s indicators bore negative value, but they are probably not a sign of unhealthy development but a preparation for future development. Therefore, using entirely such negative historical value that led to negative present value of some companies cannot result in most appropriate outcomes.
Instead, some of the outliners in negative historical value should have been eliminated when forecasting future free cash flow to reduce bias and better the result. Second, the time period of eleven years used to forecasting future free cash flow is relatively short to actually capture the real present value of the sample companies. Because the chosen companies are largest by market capitalization in technology sector in the US, they are also considered healthy going-concerns, which means their operations are supposed to last for a very long period of time. A much longer period of time should have been applied so as to better measure the future free cash flows of companies then to relevantly discount them back to the present value. The chosen period was limited by the required data used for DCF model accessible by the researcher. The researcher is not able to find or access many sample companies’ financial statements before 2001.
Nevertheless, the way the researcher conducted the DCF model with 11-year period future free cash flow was relatively relevant to obtain certain helpful results regarding the research question as indicated in the previous sections.
In conclusion, this thesis was not conducted in the most optimal way to achieve the most exact outcomes but it was conducted with the most possibly available resources within the researcher’s reach. However, this dissertation can still reveal certain valuable insights regarding the research’s scope. The researcher believes that this thesis is a useful work that can be beneficial for further researches regarding valuation methods, intrinsic value of companies, financial ratios, financial management,
investing strategies and so on.
References
Alberro, J. 2015. Estimating damages using DCF: from free cash flow to the firm to free cash flow to equity (and back). Oxford University Press, 3, 689-698.
Bagust, P. 2017. The technological revolution and the future of residential property. Accessed on 10 February 2018. Retrieved from
http://www.rics.org/fi/knowledge/research/insights/the-technological-revolution-and-the-future-of-residential-property-/
Boskovska, D. 2013. Some problems in determining the free risk rate of return.
Institute of economics Skopje, 70-73.
Brealey, R., Myers, S. & Allen, F. 2008. Principles of corporate finance.
Massachusetts Institute of Technology, 10, 355-358.
Brigham, E. & Ehrhardt, M. 2005. Financial management (theory and practice).
Thomson South-Western, 12, 507-508.
Corporate tax rate 2013-2017. 2017. Page on Deloitte’s website. Accessed on 4 January 2019. Retrieved from
https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Tax/dttl-tax-corporate-tax-rates-2013-2017.pdf
Creswell, J. & Clark, V. 2011. Designing and conducting mixed methods research.
Sage knowledge, 2.
Damodaran, A. 1996. Investment valuation: tools and techniques for valuing any assets. 2nd. ed.
Elbannan, M. 2014. The capital asset pricing model: an overview of the theory.
International Journal of Economics and Finance, 1, 216-222.
Fama, E. 1970. Effiecient Capital Markets: A review of Theory and Empirical Work. The Journal of Finance, 2.
Fenendez, P. 2015. Company valuation methods. University of Navarra.
Fenendez, P. 2017a. Valuing companies by cash flow discounting: 10 methods and 9 theories. University of Navarra.
Fenendez, P. 2017b. Valuation using multiples: How do analysts reach their conclusions?. University of Navarra.
Geier, B. 2015. What did we learn from the dotcom stock bubble of 2000s?.
Accessed on March 18 2018. Retrieved from http://time.com/3741681/2000-dotcom-stock-bust/
Greener, S. 2008. Business research methods. London: Ventus Publishing, 36.
Heaton, J. & Lucas, D. 1999. Stock prices and fundamentals. Northewestern University Kellogg Graduate School of Management.
History Of The Development Of Capm Finance Essay. 2013. Page on Essay’s website. Accessed on 10 November 2017. Retrieved from
https://www.uniassignment.com/essay-samples/finance/history-of-the-development-of-capm-finance-essay.php?cref=1
Hollstein, F & Prokopczuk, M. 2016. Estimating Beta. University of Washington, 1437-1466.
Holthausen, R & Zmijewsk, M. 2012. Valuation with marketing multiples: how to avoid pitfalls when identifying and using comparable companies. Journal of applied corporate finance, 3, 26-38.
Hox, J. & Boeije, H. 2005. Data collection, primary vs secondary. Utrkh University.
Johnson, B. & Christensen, L. 2014. Educational research: quantitative, qualitative and mixed approaches. Sage publications, 5.
Kelly, M. 2017. Capital asset pricing model (CAPM). Accessed on 10 November 2017. Retrieved from https://www.business.com/articles/capital-asset-pricing-model-capm/
Ketz, E. 2016. Free cash flow and business combinations. Accessed on 15 December 2017. Retrieved from https://www.cpajournal.com/2016/11/23/free-cash-flow-business-combinations/
Koller, T., Goedhart, M. & Wessels, D. 2010. Measuring and managing the value of companies, 103-104.
Kothari, C. 2004. Research methodology: methods and techniques. University of Rajasthan, Jaipur (India), 2.
Lim, P. 2017. 5 signs tech stocks are about to bring down the market again.
Accessed on 14 February 2018. Retrieved from
http://time.com/money/5001194/stock-market-signs-tech-bubble-crash/
Madura, J & Fox, R. 2014. International financial management. Florida Atlantic University, 13, 84-85.
Martin, V. 1990. Reviewing discounted cash flow analyses. The appraisal journal January 1990, 83-87.
McClure, B. 2007. Discounted cash flow analysis. Accessed on 15 February 2018.
Retrieved from https://i.investopedia.com/inv/pdf/tutorials/dcf.pdf
Molla, R. 2017. 57 start-ups became unicorns this year and seven lost their horns.
Accessed on 16 February 2018. Retrieved from
https://www.recode.net/2017/12/20/16761708/2017-startups-funding-billion-valuation-company
Mullins, D. 1982. Does the capital asset pricing model work?. Accessed on 10 November 2017. Retrieved from https://hbr.org/1982/01/does-the-capital-asset-pricing-model-work
Rachlin, H. 2003. Rational thought and rational behavior: a review of bounded rationality: the adaptive toolbox. Journal of the experimental analysis of behavior, 79, 409-412.
Ross, S., Westerfield, R. & Jaffe, J. 2005. Corporate finance. The McGraw Hill Companies, 6, 60-68.
Ross, S., Westerfield, R. & Jordan, B. 2010. Fundamentals of corporate finance.
Massachusetts Institute of Technology, 443.
Ruback, R. 2002. Capital cash flows: a simple approach to valuing risky cash flows. Graduate School of Business Administration Harvard University, 85-103.
Russo, T. 2017. Twelve stocks to buy to keep the gain going in 2018. Accessed on 17 February 2018. Retrieved from
https://www.forbes.com/sites/investor/2017/12/10/12-stocks-to-buy-to-keep-the-gains-going-in-2018/#40900b0f2adf
Saksonova, S. 2009. Company’s operating assets and free cash flow as a source of profit. University of Latvia.
Schwab, K. 2015. Are you ready for the technological revolution?. Accessed on 12 February 2018. Retrieved from https://www.weforum.org/agenda/2015/02/are-you-ready-for-the-technological-revolution/
Sehgal, S. & Pandey, S. 2010. Equity valuation using price multiples: evidence from India. Asian academy of management journal of accounting and finance, 89-108.
Serra, R. & Fávero, L. 2018. Multiples’ Valuation: The Selection of Cross-Border Comparable Firms. Emerging Markets Finance and Trade, 54, 1973-1992.
Sharma, R. 2017. When will the tech bubble burst?. Accessed on 14 February 2018. Retrieved from https://www.nytimes.com/2017/08/05/opinion/sunday/when-will-the-tech-bubble-burst.html
Shiller, R. 2000. Irrational exuberance. Princeton University Press, 60-63.
Singh, K. 2007. Quantitative social research methods. Sage Publications India, 62-67.
Surbhi, S. 2016. Difference between qualitative and quantitative research.
Accessed on 15 March 2018. Retrieved from
https://keydifferences.com/difference-between-qualitative-and-quantitative-research.html
Welsh, J. & White, J. 1975. Cash flow forecasting: one solution to inadequate financing, 19-27.
What’s the relationship between r squared and beta?. 2015. Page on Investopedia’s website. Accessed on 11 November 2017. Retrieved from
https://www.investopedia.com/ask/answers/012915/whats-relationship-between-r-squared-and-beta.asp
Appendices
Order Company’s name Company’s symbol
1 Adobe System incorporated ADBE
2 Autodesk Inc. ADSK
3 American Software Inc. AMSWA
4 Amazon.com Inc. AMZN
5 Ansys Inc. ANSS
6 Apple Inc. AAPL
7 Activision Blizzard Inc. ATVI
8 Cadence Design Systems Inc. CDNS
9 Cerner Corporation CERN
10 Cisco System Inc. CSCO
11 Cognizant Technology Solutions Corporation CTSH
12 Citrix Systems Inc. CTXS
13 Electronic Arts EA
14 International Business Machine Corporation IBM
15 Intel Corporation INTC
16 Intuit Inc. INTU
17 Lam Research LRCX
18 Microsoft Corporation MSFT
19 Micron Technology Inc. MU
20 NCR Corporation NCR
21 Nuance Communications Inc. NUAN
22 Nvidia Corporation NVDA
23 Oracle Corporation ORCL
24 Qualcomm Inc. QCOM
25 Ret Hat Inc. RHT
26 Synopsys Inc. SNPS
27 Symantec Corporation SYMC
28 Western Digital Corporation WDC
29 Xilinx Inc. XLNX
30 Xerox Corporation XRX