Exponents of asset pricing

The Nobel Prize in Economic Sciences for 2013 was jointly awarded to Eugene F Fama, then at University of Chicago, Lars Peter Hansen, then at University of Chicago and Robert J Shiller, then at Yale University, New Haven, CT, USA "for their empirical analysis of asset prices".

Fama began his undergraduate studies in romance languages from Tufts University, but found the subject boring. He then took a course in economics and never looked back since then. Later, he did MBA in finance and PhD in economics in 1964 from the Booth School of Business at the University of Chicago. His Doctoral supervisor was Merton Miller, but he was also influenced by Benoit Mandelbrot. In particular, he learned about fat-tailed distributions (as opposed to normal distribution) and its relevance in many economic and finance issues. While doing his PhD, he started teaching at the Booth School in 1963 and has been teaching there since then.

Hansen did his undergraduate studies in mathematics and political science from Utah State University in 1974 and PhD in economics from the University of Minnesota in 1978. While at Minnesota, he was influenced by the young faculty members — Christopher Sims and Thomas Sargent (Nobel Prize winners in 2011). After his PhD, he joined the faculty at Carnegie Mellon University in 1978 and stayed there till 1981. In 1981, he joined the economics faculty and has been teaching there since then.

Robert Shiller did his undergraduate studies in economics from the University of Michigan at Ann Arbor in 1967 and Masters in economics from MIT in 1968. He did his PhD in economics in 1972, from MIT only. At MIT, he was taught by Paul Samuelson and his doctoral advisor was Franco Modigliani (the Nobel Prize winner in 1985). His doctoral dissertation focused on the econometrics of rational expectations, Bayesian statistics and distributed lag estimation. After his PhD, he joined as faculty at the University of Minnesota in 1972 and did teaching stints at University of Pennsylvania and MIT, before settling down at Yale University, where he has been teaching since 1982. Before joining Yale, Shiller joined the National Bureau of Economic Research in 1979 as a research associate and worked on recessions in the USA.

In this article, we will discuss the main works of Fama, Hansen and Shiller and review how they continue to be relevant in public policy areas.

Main works of Eugene Fama

Fama's interest in economics was triggered during his undergraduate days at Tufts when he shifted from studying literature. His professors at Tufts encouraged him to go to Chicago if he was interested in finance and economics. When he joined the Booth School at Chicago for his PhD, he significantly developed interest in finance and econometrics. Fama began attending the econometrics workshops, where he ran into Merton Miller, who became his doctoral advisor. Fama is best known for his work on the efficient market hypothesis. This hypothesis simply says that it is difficult to predict stock prices in the short run because markets factor in new information very quickly. More specifically, Fama looked at the time series data of stock prices and showed that stock returns have fat-tailed stable distributions, much like what Mandelbrot had hypothesised. In other words, the returns to stocks have too many outliers as compared to what a normal distribution would predict. Fama's thesis, 'The Behavior of Stock Market Prices' was published in the 'Journal of Business' in 1965. In a later paper of 1965, 'Random Walks in Stock Market Prices', Fama argued that stock prices followed a 'random walk' — a statistical term meaning that the time series has a mean and variance which changes over time and is therefore unpredictable.

Fama's work resulted in more research in economics and finance and had immediate applications in the stock brokerage firms. The finding that even the best investors could not beat the market, simply because they could not predict how stock prices move in the short term, led to different strategies of investing in the stock market. The advisory was now that one should diversify risk and invest in a portfolio of stocks.

Other publications by Fama include 'The Theory of Finance' (1972; co-authored with Merton H Miller), 'Foundations of Finance: Portfolio Decisions and Securities Prices' (1976), and many journal articles.

Main works of Lars Hansen

One of the conundrums in finance is how a rational investor reacts to risk and uncertainty in asset prices — what would be the best strategy to beat this uncertainty? It is generally accepted that the probability of high future returns is a reward for the risk taken and the uncertain times. Hansen made a distinction between risk and uncertainty: risk is when you know the probability of the outcome and uncertainty is when you have no idea about such a probability. Taking an example of an urn with six red and four green balls, one knows the probability of drawing a red or a green ball. However, if one just knows that there are ten balls, without knowing the colour of the balls and how many of each colour are there, we can't rely on probability. On top of this, if probabilities are not just unknown but also change over time, as they do in macroeconomic variables, things become more complicated.

Hansen quantified this aspect of uncertainty, modelled it and developed a statistical tool called GMM (Generalised Method of Moments) that allows one to test such theories of asset pricing under uncertainty. The GMM technique was used later in macroeconomics, labour economics, climate science and finance; it approximated the real world better since it made realistic assumptions about economic agents' beliefs and their learning abilities. Hansen developed his ideas further in collaboration with Thomas Sargent, which was captured in a book they co-authored — 'Robustness'. In this book, a new theory was proposed that sought to explain decision making when investor's beliefs changed over time.

Hansen also made a distinction between outside and inside uncertainty, which should be kept in mind while proposing models. Outside uncertainty is referred to as one which is faced by the econometrician who proposes the model, and inside uncertainty is the one faced by the actors inside the model. To quote from his Nobel lecture:

Using random processes in our models allows economists to capture the variability of time series data, but it also poses challenges to model builders. As model builders, we must understand the uncertainty from two different perspectives. Consider first that of the econometrician, standing outside an economic model, who must assess its congruence with reality, inclusive of its random perturbations. An econometrician's role is to choose among different parameters that together describe a family of possible models to best mimic measured real world time series and to test the implications of these models. I refer to this as outside uncertainty. Second, agents inside our model, be it consumers, entrepreneurs, or policy makers, must also confront uncertainty as they make decisions. I refer to this as inside uncertainty, as it pertains to the decision-makers within the model. What do these agents know? From what information can they learn? With how much confidence do they forecast the future? The modeller's choice regarding insiders' perspectives on an uncertain future can have significant consequences for each model's equilibrium outcomes.

Main works of Robert Shiller

While it is difficult to make predictions of stock prices over days and months, Shiller proposed that such predictions were possible over several years. He showed that prices of stocks and bonds followed a pattern, if seen from a long-term perspective. More specifically, he found that stock prices vary more than dividends, and that the ratio of prices to dividends tends to fall when it is high, and increases when it is low. This is true for all assets including stocks and bonds. Shiller also found that investors often overvalued prices and stocks (he referred to this as irrational exuberance), which led to asset 'bubbles' wherein asset prices rose to levels that were not sustainable. Shiller contended that such bubbles were bound to 'bust' sooner rather than later, which is what happened to the IT stocks in 2000 and the real estate stocks in 2008. Speaking of bubbles, Shiller further says that bubbles are more about how investors are insulated from some information, rather than about how 'crazy' they are. To quote from his Nobel lecture:

My definition puts the epidemic nature, the emotions of investors, and the nature of the news and information media at centre of the definition of the bubble. Bubbles are not, in my mind, about the craziness of investors. They are rather about how investors are buffeted en masse from one superficially plausible theory about conventional valuation to another. One thinks of how a good debater can take either side of many disputes, and, if the debater on the other side has weak skills, can substantially convince the audience of either side. College debate teams demonstrate this phenomenon regularly, and they do it by suppressing certain facts and amplifying and embellishing others. In the case of bubbles, the sides are changed from time to time by the feedback of price changes—at the proliferation caused by price increases or reminders of basic facts that a debater might use to defend the bubble—and the news media are even better at presenting cases than are typical college debaters.

Shiller was essentially saying that rational investors price a stock at the present value of expected future dividends. However, as we noted above, Shiller pointed out that stock prices fluctuate more than can be explained by fluctuations in dividends. Shiller attributed this variance to psychological and behavioural factors, arguing that investors might not be acting rationally and other factors were at play. He therefore surmised that the stock market was inefficient, which was opposite to the efficient market hypothesis of Eugene Fama, which we discussed above.

Shiller is also known for his application of behavioural economics to various areas such as finance and real estate. He created the S&P/Case-Shiller Home Price Index, along with Karl Case. This index tracks changes in the average price of residential real estate in several major US cities.

Shiller has written widely, but two of his recent books have been well received: 'Irrational Exuberance' (2009 edition), where he wrote that the increase in stock prices from 1994 to 2000 was not matched by similar growth in the real economy and that the stock price should be viewed as the present value of future dividends. In 'Finance and Good Society' (2013), he defended the returns from investment and clarified that 'derivatives' was not such a dirty word after all.

Conclusion

From the efficient markets hypothesis of Fama to the modelling of uncertainty by Hansen to the behavioural analysis of financial markets — including the prediction around the 2000 and 2008 bubbles — by Shiller, the three laureates have contributed significantly in advancing the study of finance and economics. While all of them studied the logic of asset pricing, each of them looked at different aspects of such pricing. On the one hand, Fama's hypothesis was that markets are informationally efficient since a stock price reflects all the information that is available. On the other hand, Shiller suggested that investors' behaviour is not totally rational and that psychology and behavioural economics needed to be invoked. This was because stock prices fluctuated more than dividends (which wouldn't happen in Fama's world where investors are rational and the stock price reflects all the information there was to reflect). Hansen confirmed the analysis of Shiller. Be that as it may, the different viewpoints have enriched our understanding of the way asset prices behave under uncertainty and in the real world.

The writer is an IAS officer, working as Principal Resident Commissioner, Government of West Bengal. Views expressed are personal.