Google Search Trends May Predict Market Movements

Google Trend data may be predictive of something. Which is pretty exciting. It's just that figuring out exactly what the data is predicting is taking a lot of work.

Researchers have known for some time that such accumulated information about search trends may provide certain clues for important problems, like tracking the outbreak of diseases by determining why so many people in one geographical area are suddenly using search terms indicative of medical symptoms.

Given the financial orientation of our economy, interest in the application of such data to determine market movements is manifest. And there appears to be some optimism that the trends do possess some predictive value. There are two challenges, however. The first is that if too many people are using this data, then the data themselves begin to influence the markets, rather than simply predicting it. This has happened in the past where hedge funds and other 'sophisticated' investors have made large bets based on similar analyses only to discover that the bets did not pay off because so many other smart guys were employing the same statistical inputs and models that it negated the advantage they thought they had.

A second problem is that correlation is not necessarily causality. Some of the clues from Google Trends are indirect or not sufficiently focused to be of much use. What the researchers do believe is that the trend data may provide insights into how traders make decisions at specific times about specific investments. Insights into what motivates securities traders may be scary or depressing, but it could be useful. JL 

Phillip Ball reports in Nature:

Traders reveal their mood — but no easy path to riches — in the search terms they use.

Suppose you had a direct line into the minds of stock-market traders. Would you be able to predict which investment decisions they will take, and thus anticipate the markets?
A team of researchers in the United Kingdom and the United States now suggests that such a crystal ball might exist, in the form of the search terms recorded and made publicly available by Google Trends. Tobias Preis, a computational social scientist at the University of Warwick, UK, and his colleagues say that their analyses of Google Trends data show “early warning signs” of how the markets will shift — including the financial crash of 2008. Their results appear in Scientific Reports¹.

Trading up

The predictive value of Google Trends has been demonstrated in other areas of social science. Most famously, outbreaks of influenza have been seen emerging in real time by monitoring the numbers of Google searches for terms related to flu prevention and cure².
The potential of using such information to study economic behaviour has been spotted before. Preis and his co-author, the physicist Eugene Stanley of Boston University in Massachusetts, have themselves shown that certain search terms reflect the volume of stock-market transactions³. Mathematical physicist Didier Sornette of the Swiss Federal Institute of Technology in Zurich, in collaboration with Japanese economists, has found that the volatility (fluctuations) of financial markets can be correlated with the prevalence of particular topics in the business news⁴.
But what traders and investors really want, of course, is a method that not only assesses the current state of the markets but also anticipates their future course. In particular, episodes of instability, such as the financial crisis of 2008, are often preceded by periods of concern during which investors avidly seek information to decide whether to buy or sell.
Preis and his colleagues reasoned that such anxieties and moods might be signalled by Google search terms. It might be expected, for instance, that just before the onset of the latest financial crisis, 'debt' would have featured prominently. And that is just what the researchers found.
To test whether such correlations could be made predictive, they devised trading strategies in which a decision to buy or sell was linked to the recent prevalence of particular search terms. They simulated how these strategies would have performed between 2004 and 2011 on the basis of real data from the financial markets.
Of the 98 ‘Google Trends’ strategies the researchers explored, that based on 'debt' performed best. By 2011, it would have increased the value of a financial portfolio by more than 300%, compared with just 16% for a common conventional investment strategy.
But although the results sound impressive, the relevance of a predictive Google search term is not always clear. The second-best strategy, for example, was linked to 'colour', and the fourth best to 'restaurant'. Even the use of 'debt' is not obvious, because its role in the financial crash was apparent only as it happened. “How would they know in advance that they should use ‘debt’?” asks Sornette.

Psychological insight

“In retrospect, it is always possible to derive what appear to be highly successful trading strategies,” says economist Paul Ormerod of the London-based consultancy Volterra Partners. “But what we want is to be able to do that before the event, not after.”
Furthermore, economists acknowledge that any transparently profitable strategy for playing the markets will quickly lead to a change in trader behaviour that cancels it out — a principle called Goodhart’s law, after the British economist Charles Goodhart. “Social systems have the complication that the system may directly react to predictions being made about its behaviour,” agrees Susannah Moat, a computational social scientist at University College London and a co-author on the study.
The researchers suggest, however, that a key outcome of their approach might be to elucidate the psychological mechanisms that guide traders to their decisions, which could be encoded in their information gathering. “Stock-market data themselves tell us little about how traders make decisions,” says Preis.
“We think that the overall pattern we observe may reflect loss aversion,” he adds — the fact that people are more concerned about losing money than they are about missing an opportunity to gain the same amount.