The economics Nobel matters for India

Eugene Fama’s lesson is clear: sentiments matter far less for markets than information captured by prices

In his early work, Fama provided substantial empirical evidence from US stock markets, showing that they did not seem far from the theoretically efficient ideal. Photo: Scott Olson/Getty Images/AFP
In his early work, Fama provided substantial empirical evidence from US stock markets, showing that they did not seem far from the theoretically efficient ideal. Photo: Scott Olson/Getty Images/AFP

The recent announcement of the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel has gone to three extremely deserving recipients. The combination of deep economic insight and clever methodological contributions that Eugene Fama, Lars Hansen and Robert Shiller have brought to this field has revolutionized our understanding of the determinants of asset prices.

Understanding asset price variation is not only a means to engage in profitable speculation. Asset price predictions are key inputs to important calculations, including the size of the pensions that people can expect to receive on retirement; capital budgeting and capital allocation by companies; investment advice and portfolio allocation; and ascertaining whether governments are solvent or insolvent. So the work of the laureates has substantial real-world impact.

To better understand their contributions, it’s instructive to begin with a perception voiced frequently in many of our drawing rooms, namely that equity markets in India are driven mainly by “sentiment”, and that fundamental factors simply don’t drive fluctuations in the Sensex. This characterization is virtually the complete opposite of Eugene Fama’s 1970 definition of an “efficient market”, namely, one in which prices fully reflect all available and relevant information. In such a market, Fama argued, there would be rapid, profitable trading in the event of dislocations between prices and relevant fundamental information, which in turn would discipline prices back to fundamentals. In his early work, Fama provided substantial empirical evidence from US stock markets, showing that they did not seem far from the theoretically efficient ideal—this more or less represented the academic consensus in the late 1960s, and through the 1970s. A critical input into this work by Fama and other researchers was the groundbreaking creation in the 1960s of the Center for Research in Security Prices at the University of Chicago—housing vast quantities of high-quality data, which allowed researchers to work on these important questions. The creation and effective utilization of such high-quality data represents perhaps the first lesson for us in India—the more investment that is made in opening data to free inquiry, the more elevated the public debate that is engendered.

Enter Robert Shiller in the early 1980s, with a devastating critique of the prevailing efficiency consensus. He began with a simple point: the index of all stocks, in an efficient market, simply represents a claim to all future cash flows paid out by these stocks. This accounting relationship tells us that if stock prices are high today, future cash flows are expected to be high as well. Conversely, falls in stock prices should be justified by future falls in cash flows. Of course, the key here is the discount rate applied to these cash flows, and Shiller began with the most basic assumption, namely that the discount rate is constant over time.

Using data on two well-known stock indices, the S&P Composite and the Dow Jones Industrial Average, Shiller showed that a simple calculation using data over a long historical period revealed an astonishing difference between current variation in stock prices (extremely high) and future variation in cash flows discounted at a constant rate (an order of magnitude lower). Armed with this evidence, Shiller concluded that the efficient markets hypothesis appeared indefensible. Lars Hansen arrived at a similar conclusion about the difficulty of explaining stock prices using fundamental information using a newly developed methodology, different data, and a different modelling approach. However, in a series of subsequent papers, Shiller also showed that while equity markets are volatile in the short run, the volatility damps down as a consequence of predictable patterns in stock returns, over the longer run. This insight suggests a different approach to viewing stock prices, with consequences for the many questions raised earlier. Here lies the second lesson—simply dismissing the market as an irrelevant sideshow isn’t the right response—once we spend time understanding the deep drivers of market variation, we can adjust our computations appropriately. Moreover, there may be an important role for appropriate financial market regulation once we better understand the underlying economics.

Enter Fama once again in the 1990s. A series of papers written with his frequent co-author Kenneth French showed that moving one’s investments towards smaller firms and “old economy” firms paid rich dividends in the long run. This important insight has shown up repeatedly across countries, time periods, and even different assets—and the methodologies that have been developed have revolutionized the practice of asset management. Here is the third and perhaps most important lesson—wherever there is a problem (for example, unexplained stock market volatility), there is likely a (very profitable) solution (such as the right asset allocation strategy) which can benefit many. The key is dedicated research and a desire to pierce through the fog of ignorance.

Together, the laureates have greatly improved our understanding of modern asset markets. Their blend of rigorous statistical methodology, deep connections with economic theory, and healthy respect for “market wisdom” has provided a huge impetus to one of the most important and active areas of current research in economics. The lessons for India are clear.

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Tarun Ramadorai is professor of financial economics at the Saïd Business School, University of Oxford, and a member of the Oxford-Man Institute of Quantitative Finance.

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