Individual Article Review 3
Executive summary
Cornell and Damodaran use discount cash flow model and other analytical tools to study the effect of investor sentiment in the run-up in Tesla’s stock price between March 22, 2013 and February 26, 2014. Although the authors do not include the premium for a synergy from a merger or acquisition and the premium for a real option to enter a new market in the valuation of the stock, they find that the stock is overvalued by nearly 150% during the run-up period. They also conclude that the increase in market price is attributed in part to investor sentiment instead of fundamentals.
Data and Methods
Data includes revenue, earnings, profit margins, calculated growth rate, and Tesla’s invested capital, can be drawn from financial statements of the firm, which is publicly available returns data. Although the data are of a couple months, I think they are well enough to justify the role played by investor sentiment. The authors are able to conclude their findings with these data using standard analytical tools and valuation analysis.
The authors develop a detailed discount cash flow models to estimate the value of Tesla. Discount cash flow model is an existing and well established methodology to price a stock. This model is applied by Damodaran for the evaluation of Tesla in 2013 with four key inputs: expected cash flow from existing assets, expected growth in operating income, cost of equity and capital, and estimated terminal value. All these estimates are calculated based on the most aggressively optimistic assumption which gives value creation the benefit of the doubt. Hypothesis testing with t-statistics is also used to examine whether the run up in Tesla’s stock price is the result of arrival of new fundamental information.
Results
The discount cash flow models show that the stock is overvalued by approximately 150% in September 2013 and March 2014. However, there are insufficient news arrived during the one year run-up period and no news can justify the increase in market price. Furthermore, statistics and figure support that noise trades who