AJIBM  Vol.10 No.1 , January 2020
Uber Future Value Prediction Using Discounted Cash Flow Model
Abstract: It is important to make a reasonable valuation of a company. A good valuation can make a difference in lots of aspects. In this research, the purpose of predicting valuation of Uber is to gain the future free cash flow and stock value of it, so that we can provide information for its future development strategy and put forward feasible business decisions, and then improve the future value of it. What’s more, we hope to use the information of Uber’s valuation to make investment analysis, understand its advantages and disadvantages, and help investors make better decisions. The reason why we choose Uber as a research object because it is a growing company that needs the right strategy and a lot of investments. Making valuation of Uber can help it attract investment and make stratagem. We use the discounted cash flow model to value Uber. We estimate the company’s income, expenditure, free cash flow and equity beta in the future by investigating and studying its data in recent three years and the data of a peer group. Finally, we get Uber’s optimistic price, pessimistic price and target price. All of the prices are higher than the present price which means it has a good development prospect and be good for investing.
Cite this paper: Li, M. (2020) Uber Future Value Prediction Using Discounted Cash Flow Model. American Journal of Industrial and Business Management, 10, 30-44. doi: 10.4236/ajibm.2020.101003.

[1]   Uber’s S-1 Filing as of April 11, 2019.

[2]   Uber’s Stock Price Data.

[3]   Amazon’s Historical Stock Price Data.

[4]   Amazon’s Financials.

[5]   Tesla’s Financials.

[6]   Tesla’s Historical Stock Price Data.

[7]   Expedia’s Financials.

[8]   Expedia’s Historical Stock Price Data.

[9]   GrubHub’s Financials.

[10]   GrubHub’s Historical Stock Price Data.

[11]   NetFlix’s Financials.

[12]   NetFlix’s Historical Stock Price Data.

[13]   Booking Holding’s Financials.

[14]   Booking Holdings’s Historical Stock Price Data.