This is an interesting rebuttal to Uber's valuation that was posted here awhile back. What do you think? (link inside the post)
How to Miss By a Mile: An Alternative Look at Uber's Potential Market Size
July 11, 2014: On June 18, Aswath Damodaran, a finance professor at NYU's Stern School of Business, published an article on FiveThirtyEight titled "Uber Isn't Worth $17 Billion." This post was a shortened version of a more detailed post he had written for his own blog titled "A Disruptive Cab Ride to Riches: The Uber Payoff." Using a combination of market data, math, and financial analysis, Professor Damodaran concluded that his best estimate of the value of Uber is $5.9 billion, far short of the value recently determined by the market. This estimate of value was tied to certain "assumptions" with respect to TAM (total available market) as well as Uber's market share within that TAM. And as you would expect, his answer is critically dependent on these two assumptions.
As the Series A investor and board member at Uber, I was quite intrigued when I heard that there was a FiveThirtyEight article specifically focused on the company. I have always loved the deep, structured analysis that Bill Simmons and Grantland bring to sports, and when Nate Silver also joined ESPN, I was looking forward to the same thoughtful analysis applied to a much broader range of subjects. Deep research and quantitative frameworks are sorely lacking in today's short attention span news approach. I could hardly wait to dive in and see the approach.
The funny thing about "hard numbers" is that they can give a false sense of security. Young math students are warned about the critical difference between precision and accuracy. Financial models, especially valuation models, are interesting in that they can be particularly precise. A discounted cash flow model can lead to a result with two numbers right of the decimal for price-per-share. But what is the true accuracy of most of these financial models? While it may seem like a tough question to answer, I would argue that most practitioners of valuation analysis would state "not very high." It is simply not an accurate science (the way physics is), and seemingly innocuous assumptions can have a major impact on the output. As a result, most models are used as a rough guide to see if you are "in the ball park," or to see if a particular stock is either wildly under-valued or over-valued.