A meeting of opposites - the nobel prize in economics

My column for the Nov edition of Wealth Insight - here. The unedited version is below:


This month, the Nobel prize for economics was jointly awarded to Eugene Fama, Lars Hansen and Robert Shiller. In itself, the award to three economists is not comment worthy. What makes it interesting is the combination of individuals and the ideas they represent.  Fama and Shiller represent opposite views on how prices of financial assets are formed.

The Chicago Tradition

Between 1940-43, Friedrich Von Hayek, an economist at the London School of Economics, wrote a book – “The Road to serfdom”. Having watched the takeover of Vienna by Nazi Germany, this book outlined his opposition to “Big government”. In the book, Hayek says “when economic power is centralized as an instrument of political power it creates a degree of dependence scarcely distinguishable from slavery.”

The book was published by the Chicago University in 1944, and became the basis of “libertarianism” which found its chief proponent in Milton Friedman. Along with a group of friends, Friedman went on to form the “Chicago School”. Friedman believed that markets worked better than governments. Over time, the Chicago school started to believe that markets were “perfect”.

Fama and Efficient Markets

Fama arrived in Chicago as a MBA student in 1960 – and started work on stock price movements. His initial work was statistical – exploring the statistical distribution of stock price movements. Fama soon proposed that stock price movements were random – and that any non-random movement would be arbitraged away by traders so that any non-random patterns were essentially fleeting. He argued that “the actions of the many competing participants should cause the actual price of a security to wander randomly about its intrinsic value.” He called this the “Efficient Market“.

In 1964, Lawrence Fisher and James Lorie published a study covering data over 34 years – anyone who bought all stocks in the New York Stock Exchange and reinvested dividends would have earned 9% post costs over those 34 years. Subsequently, they demonstrated that a randomly selected assorted portfolio also performed as well. Monkeys with darts were as good as mutual fund managers. The markets were indeed efficient – and all available information seemed to be in the price.

Fama went on to teach portfolio theory and came across the work of Markowitz and Sharpe. He quickly realised that the Capital Asset Pricing Model (CAPM) was the model that proposed the economic theory of how stock prices moved – leading to efficient markets.

The analysis that mutual funds and fund managers rarely beat markets – especially after costs, led John Bogle to form the Vanguard Index fund. Indexed investing had come to the markets.

Behavioural Finance and inefficient markets

Later research into economic behaviour of individuals revealed that choices made by individuals were not all rational or “efficient”. People avoided certain loss while being willing to bet on uncertain gain. Somehow, efficient markets demanded that despite each individual decision being irrational, the collective was always rational. This was difficult to explain. Shiller, a PhD from MIT, started to test assertions of efficient markets. He found for example, that stock prices that were supposedly determined by future dividends, were way more volatile than the dividend paid. They were also more volatile than earnings, demand, replacement cost – or any other fundamental parameter. The “rationality” hypothesis of the market had no explanation for this volatility.

Shiller asserted that the leap from observing that stock prices were difficult to predict to that they were right, was “one of the most remarkable errors in the history of economic thought”.  Lawrence Summers a Harward economist, constructed an alternate finance universe where investors weren’t rational and prices did not reflect economic fundamentals. He was able to show that over a simulated 50 year period, no test could determine statistically the difference between the two market constructs – real market vs simulated market. Summers at a speech to finance professors said “Financial economists like Ketchup economists work only with hard data and are concerned with the interrelationships between the prices of different financial assets. They ignore what seems to many to be the more important question of what determines the overall level of asset prices.”

Slowly, the realization that markets could remain inefficient for long periods was being accepted by academicians. Fischer Black in a lecture titled “Noise” said that noise made financial markets possible but also imperfect. Without noise, prices would stay at their fundamental value and there would be no trading. Unfortunately, noise also made the detection of fundamental value impossible. 

As computers became more powerful, more instances of statistically significant “inefficiencies” started to be discovered. Some indicated that trends tended to persist – stocks prices continued to trend in one direction more often than random moves would imply. When corporate earnings differed from expectations, it took a while for the price to reflect the new expectations fully. The January effect and the “small stock” effect were also persistent.

Confronted with this data, Fama modified the CAPM to bring in factors other than just market moves to explain price behaviour. These were the 3 factor and 4 factor models. However, these turned out to be cases of data mining. Perhaps there was something to beating the market after all.

The Nobel committee in its press release summarises it thus “There is no way to predict the price of stocks and bonds over the next few days or weeks. But it is quite possible to foresee the broad course of these prices over longer periods, such as the next three to five years. These findings, which might seem both surprising and contradictory, were made and analyzed by this year’s Laureates, Eugene Fama, Lars Peter Hansen and Robert Shiller....The Laureates have laid the foundation for the current understanding of asset prices. It relies in part on fluctuations in risk and risk attitudes, and in part on behavioral biases and market frictions”. The search for a perfect market model continues.