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Finacial Models Don't Correlate With Consumer Demand

By: Charles Mussallem, Lauren Foss, Anil Nair, and Eduardo Pantin

Financial analysts forecast expected returns using linear financial models. This becomes problematic because consumer demand is non linear. Consumers often change the products and services they use, replacing them when a superior one is introduced. These forecasts becomes even harder because the value of a product or a service increases exponentially as more people use it. This is explained by the ‘network effect’. The fax machine or the success of companies like Facebook is examples of the network effect. Initially, fax machines were not worth very much at all because few people and businesses had them. However, as more and more people and businesses used fax machines, the value of this market grew from 80,000 units sold in 1984 to over one million units sold in 1987. In its conception, Facebook was very hard to value, but as their user base grew to over a billion people across the globe, the company grew to a market capitalization of over $500 billion.

In the adoption phase of a new product, financial analysts use linear models to predict the future cash flows. This is the wrong method because the value of the product or service is usually a slow initial growth trajectory, followed by a period of exponential growth. This ends up with the stocks being mispriced because of the disconnection between consumer behavior and stock valuations. Many analysts do not look beyond their financial models when valuing a stock. By monitoring consumer demand closely and following trends, you could exploit this arbitrage of mispricing like the hedge fund Tremblant did. Tremblant’s strategy was to visit and call retailers and do their own consumer research. By knowing the consumer demand, they would know which companies should be booming and which should be dying off. You could exploit this arbitrage for many companies such as Kodak. 11 out of 13 analysts had a buy rating for Kodak even though people were not using film anymore and digital cameras were apparently the sure future. Kodak’s stock continued to trade around $30 a share until suddenly losing nearly all its value dropping to $2 per share.

Another possible reason for the delay in forecast updates is due to the fact that when you change your position, you tend to decide against the crowd. Many times there is a personal relationship between the investment bank(s) and the companies they cover. If the bank does not want to lose their relationships with some of these big companies because most of these companies are also the banks customers. Companies use investment banks for capital funding, consulting, and to guide them in all sorts of deals. They make a lot of money from these companies and they do not want the company using another bank.

Institutional investors avoid taking greater risks associated with investments in small firms such as greater return volatility and lower liquidity. These constraints that affect investment decisions of institutions may lead to market segmentation, herding behavior, and continuous neglect of certain securities (Arbel et al. (1983), Nofsinger and Sias (1999)). Gompers and Metrick (1999, pp. 1‐2) find that institutions demand stock characteristics that differ from the rest of the market: “institutions invest in stocks that are large, more liquid, and have had relatively low returns during the previous 10 year” (Oppenheimer and Precourt (2013)).

Analysts’ decisions to follow firms and institutional investors’ decisions to hold shares of the same firms in their portfolios are interrelated: institutions pay close attention to the recommendations, and analysts base their decision to provide coverage on the size of the institutional holdings, among other things” (O’Brien and Bhushan (1990), Gompers and Metrick (1999), Hotchkiss and Strickland (2003), Malmendier and Shanthikumar (2007)). The relationship between institutions and analysts is a supplier‐consumer type of relationship; while analysts strive to increase institutional ownership in the firms they follow, institutional demand for information about particular firms affects analysts decisions about which firms to follow (O’Brien and Bhushan (1990)). This shows that investing with the strategy of basing your trades off of analyst ratings and institutional investors yield you a lower average return while taking enormous amounts of risk. I believe in order to be a successful trader, one must invest in companies that continue to grow their top and bottom line and continue to monitor how consumers view their products or services. By paying attention to what consumers are purchasing or using, you can have a competitive advantage.

Clearly there is a large risk associated with trying to exploit these arbitrages, although I believe they still can be done. Many companies such as Netflix and Facebook had negative analyst ratings in the beginning, although as the companies grew, their market value grew exponentially over the past couple years. Other companies like GE, Macy’s, and others had good analyst ratings up until this year. We have since seen both GE and Macy’s stock decline by over 40%. By keeping a close eye on consumer demand and market trends, you could profit from this arbitrage.


Arbel A., S. Carvell, P. Strebel. 1983. Giraffes, Institutions and Neglected Firms. Financial Analysts Journal, Volume 39, No. 3: 57‐63.

Gompers P., A. Metrick. 1999. Institutional Investors and Equity Prices. Working paper.

Hotchkiss E., D. Strickland. 2003. Does Shareholder Composition Matter? Evidence from the Market Reaction to Corporate Earnings Announcements. The Journal of Finance, Volume LVIII, No. 4: 1469‐ 1498.

Malmendier U., D. Shanthikumar. 2007. Are small investors naive about incentives? Journal of Financial Economics, Volume 85, No. 2: 457‐489.

O’Brien P., R. Bhushan. 1990. Analyst Following and Institutional Ownership. Journal of Accounting Research, Volume 28: 55‐76.

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