Investment in shares versus investment in other assets -- which gives the greater gain?

How one university collected the data to try and answer this question

A. It all began in 1958 with a phone call from Louis Engel, a banker at Merrill Lynch, a US-based financial management company, who wanted to know how investors in shares had performed relative to investors in other assets such as low risk investments with guaranteed returns. ‘I don’t know, but if you gave me $50,000 I could find out,’ replied Jim Lorie, a dean at the University of Chicago’s business school. Louis Engel soon agreed to provide the funding, and more. The result, in 1960, was the launch of the University’s Center for Research in Security Prices. Half a century later CRSP (pronounced ‘crisp’) data are everywhere. They provided the foundation of at least one-third of all empirical research in finance over the past 40 years, according to a presentation at a symposium held this month. They probably influenced much of the rest.

B. Getting the CRSP data together was a tough process in what were then the early days of computers. Up to three million pieces of information on all the shares traded on the New York Stock Exchange between 1926 and 1960 were transferred from paper in the exchange’s archive to magnetic tape. A lot of time was spent adjusting prices to take account of complexities in the market. Lorie and his co-researcher, Lawrence Fisher, chose January 1926 as the start date because they wanted the data to span at least one complete business cycle from boom to bust, or vice versa.

C. When these two economists published the first study based on the CRSP data in 1964, they reported that the annual compound return on the shares over the entire 35-year period was, depending on the tax status of the investor, between 6.8% and 9%. Acknowledging that good data on the performance of other assets were not available, the study claimed that the rate of return on shares was ‘substantially higher than for alternative investment media,’ providing the first empirical support for the still popular idea that shares outperform other investments over the long run. Fisher and Lorie also observed that many people chose to invest in assets with lower returns because they were cautious by nature, and were concerned about the risk of loss inherent in investing in the stock market. Economists today call the amount of extra return that investors need to compensate them for this additional risk the ‘equity risk premium’, although they differ greatly on how big investors should expect it to be.

D. After Fisher and Lorie’s 1964 report there was no stopping the love affair between financial economists and the data that studying these numbers produced. Myron Scholes, now a Nobel laureate, became director of CRSP in 1974, and ensured the database was both kept up to date and made readily available to academic economists everywhere. In turn, this resource became ever more useful as computing power became more affordable. The CRSP database has since been expanded to include a full range of different types of investments. It has been replicated across the world.

E. One of the earliest uses of CRSP data was by Eugene Fama, an economist at the University of Chicago, to support his ‘efficient-market hypothesis’. He found that over a lengthy period share prices tended to rise and fall randomly, without showing much of a pattern. Markets are efficient, he said, because all relevant information is reflected in share prices at any given moment, meaning there are no predictable movements in prices for smart investors to exploit. Fama did concede that there was some evidence of temporary short-term predictability in share prices, however. That stipulation has resulted in a vast number of papers based on discovering such ‘variations’ through data mining. In theory, such anomalies are potentially lucrative for investors, but as believers in efficient markets observe with satisfaction, it seems that no sooner are such anomalies discovered and reported in journals than they typically disappear.

F. However, the sheer volume of material means that financial economists are becoming increasingly specialised, which may have costs as well as benefits. Some economists worry that much of this statistical analysis is creating some interference that drowns out serious thinking about the big questions, such as why the financial system nearly collapsed in 2008 and how a repeat can be avoided. Robert Shiller, an economist at Yale University and a long-time sceptic about the efficient-market hypothesis, feels that with the creation of the CRSP database economists suddenly believed that finance had become scientific. According to Shiller, conventional ideas about investing and financial markets -- and about their vulnerabilities -- seemed out-of-date to the new empiricists. He worries that academic departments are full of economists who are so specialised in data analysis that they fail to see and understand the whole. They get a sense of authority from work that contains lots of data. To have seen the 2008 global financial crisis coming, he argues, it would have been better to ‘go back to old-fashioned readings of history, studying institutions and laws. We should have talked to grandpa.'

G. Scholes responds to this criticism with the contention that the usefulness of this empirical analysis is proven by the fact that demand for it continues to grow. At CRSP’s 50th anniversary symposium, plans were unveiled to publish indicators on an expanding range of investments, as well as for growth and value stocks. These indicators, CRSP claims, will be more academically rigorous and cheaper than existing ones. For believers in the efficiency of markets, that should be enough to ensure CRSP’s continuing success.

First words

Pinpointing the origin of language might seem like idle speculation, because sound does not fossilise. However, music, chit-chat and even humour may have been driving forces in the evolution of language, and gossip possibly freed our ancestors from sitting around wondering what to say next.

There are over 6,000 different languages today, and the main language families are thought to have arisen as modern humans wandered about the globe in four great migrations beginning 100,000 years ago. But how did language evolve in the first place? Potential indicators of early language are written in our genetic code, behaviour and culture. The densest evidence is a gene called FOXP2, in which mutations appear to be responsible for speech defects. FOXP2 in humans differs only slightly from the gene in chimpanzees, and may be about 200,000 years old, slightly older than the earliest modern humans. Such a recent origin for language seems at first rather silly. How could our speechless Homo sapiens ancestors colonise the ancient world, spreading from Africa to Asia, and perhaps making a short sea-crossing to Indonesia, without language? Well, "language" can have two meanings: the infinite variety of sentences that we string together, and the pointing and grunting communication that we share with other animals.

Marc Hauser and colleagues argue that the study of animal behaviour and communication can teach us how the faculty of language in the narrow human sense evolved. Other animals don’t come close to understanding our sophisticated thought processes. Nevertheless, the complexity of human expression may have started off as simple stages in animal "thinking" or problem-solving: number processing, such as "how many lions are we up against?", navigation, or social relations. In other words, we can potentially track language by looking at the behaviour of other animals.

William Noble and Iain Davidson look for the origin of language in early symbolic behaviour and evolutionary selection in fine motor control: throwing and making stone tools could have developed into simple gestures like pointing that eventually entailed self-awareness. They argue that language is a form of symbolic communication rooted in behavioural evolution. Even if archaic humans were physically capable of speech, a hyoid bone has been found in a Neanderthal skeleton, we cannot assume symbolic communication. They conclude that language is a feature of anatomically modern humans, and an essential precursor of the earliest symbolic pictures in rock art, ritual burial, major sea-crossings, structured shelters and hearths -- all dating, they argue, to the last 100,000 years.

But the archaeological debate of when does not really help us with what was occurring in those first chats. Robin Dunbar believes they were probably talking about each other -- in other words, gossiping. He discovered a relationship between an animal’s group size and its neocortex, and reconstructed grooming times and group sizes for early humans. Dunbar argues that gossip provides the social glue permitting humans to live in cohesive groups up to the size of about 150. Apes are reliant on grooming to stick together, constraining their social complexity to groups of about 50. Gelada baboons stroke and groom each other for several hours per day. Dunbar concludes that, if humans had no speech faculty, we would need to devote 40% of the day to physical grooming just to meet social needs. Humans manage large networks by "verbal grooming" -- chatting with friends, so the audience can be much bigger than for one-to-one grooming. Dunbar also notes that, just as grooming releases opiates that create a feeling of wellbeing in monkeys and apes, the smiles and laughter associated with human banter may have a similar effect.

Giselle Bastion argues that gossip has acquired a bad name -- associated with women and opposed by men who claim objectivity -- although men gossip too; we all track other people and maintain alliances. Dean Falk suggests that before the first smattering of language there was "motherese", musical gurgling between mother and baby with eye contact and touching. Early human babies could not cling on to their mother while she walked on two feet, so motherese evolved to soothe and control infants. Dunbar also suggests nomadic expansion out of Africa, maybe 500,000 years ago, demanded larger group sizes and language sophistication to form alliances necessary for survival. Davidson and Noble, who reject Dunbar’s gossip theory, point to significant brain-size increase from about 400,000 years ago, possibly correlating with increasing infant dependence. Once words were out -- and eventually written -- they acquired an existence of their own far from the roots of language.