Informed Trading Behavior

FOLLOWING, CONTRARIAN OR HYBRID: QUANTITATIVE TRADING STRATEGIES ARE EXPLAINED IN A STUDY PUBLISHED IN THE JOURNAL OF ECONOMIC THEORY

by Stefano Rossi, full professor at Department of finance

Quantitative trading - the trading of securities based on the quantitative analysis of observable variables such as price, volume, and other characteristics of financial assets and markets - is now predominant in financial markets. Quantitative strategies can be classified as trend following (e.g. buying after the price has risen); contrarian (e.g. buying after the price has dropped); o hybrid strategies in which the direction of trading varies depending on time horizon, market structure, order of magnitude of price movements or order flows. Empirical evidence shows a huge differential in quantitative trading performance between institutional and retail investors. In fact, retail and individual investors who pursue trend following and contrarian strategies lose money on average. Therefore, a behavioral finance literature has developed that explains the use of such strategies with imperfect cognitive processes, bounded rationality, or other deviations from the paradigms of perfect rationality and efficient markets. As a result of these imperfections, quantitative traders should necessarily lose money.

On the contrary, the evidence shows that institutional investors gain a lot from trend following and contrarian strategies. Therefore, the explosion of quantitative trading profits of hedge funds and other sophisticated agents presents a challenge to a purely behavioral view of quantitative trading.
In an article about to appear in the Journal of Economic Theory, Katrin Tinn (McGill) and I propose a theoretical model of rational quantitative trading, with the aim of understanding the mechanisms behind the high returns of quantitative trading for sophisticated investors such as hedge funds. In the model, based on Kyle (1985), a risky stock is traded on two dates, and there are two types of traders, strategists acting on information about fundamentals or market structure, and noise traders. The market maker sets the price of the security equal to its expected value.

Crucially, we let go the restrictive assumption that the market maker has complete information on the number of fundamentally informed investors. We therefore show that sophisticated investors, who do not know the fundamentals but know how many fundamentally informed investors are in the market, stand to gain from adopting trend following and contrarian strategies. The reason is that sophisticated investors infer better than the market maker whether the volumes traded in the past are due to fundamental information or noise. We therefore show that the higher performance of hedge funds in quantitative trading derives from their superior ability to acquire information on the extent of informed trading present in the market at a given time, rather than information on fundamentals.

In particular, we show that with few investors informed on fundamentals, trend following (compared to contrarian) prevails after small (compared to large) order flows. The reason is that the market maker interprets the observation of small order flows too cautiously, suspecting that they reflect the absence of information on fundamentals. On the contrary, the strategic trader understands that the information is there, but confirms what is expected a priori; with few informed investors this results in a small aggregate order flow. Therefore, the strategic trader issues a trend following order. With many investors informed on fundamentals, the opposite happens: trend following (compared to contrarian) after large (compared to small) order flows.
In conclusion, our model provides a theoretical justification for the third type of quantitative trading: hybrid strategies in which the direction of trading depends on the magnitude of order flows and price movements. Furthermore, the model presents a unifying framework that clarifies the conditions under which the prevailing form of quantitative trading is trend following or contrarian, and clarifies how its direction can change non-monotonously depending on the magnitude of order flows.