This article won the Prize of the French Finance Association 2014.
We took a close look at the personality of traders to try and understand better how speculative bubbles work and we noticed that some traders do not act rationally. However they are not the only ones who affect financial markets.
For each transaction, traders have to take into account many parameters: market trends, competitors’ strategies and the latest news. But sometimes the situation gets out of hand, and other less rational aspects influence their decisions.
Studying why people make decisions can explain certain events
In spite of their experience, individuals sometimes act in a biased way. We may thus observe disproportionate reactions, such as buying shares at a price that is much too high in relation to their intrinsic value. These are illogical decisions which trigger speculative bubbles and stock markets then crash when everyone wants to sell assets simultaneously and their value collapses.
While it is now acknowledged that some traders do not act rationally at a given time, we still find it difficult to imagine that this might also be true for market-makers. These market-makers are organizations (mostly investment banks), or people, who set the buy and sell prices of assets: they are said to ‘quote’ the buying and selling prices and thus set the value of the assets. However, it is possible to demonstrate that some of these market-makers also make the wrong decisions. The market-makers are considered to be more experienced and “battle-hardened”. They are paid to stay one step ahead and traders are trained to analyze their latest strategies. As they are key players, it was difficult to admit that these market-makers might act irrationally, by increasing prices until red lights started flashing, or, inversely, lowering the price of shares in a context of increasing demand.
In order to study the effect of this phenomenon, we separated the two main biases. The first bias, related to the degree of optimism, causes the broker to misread the market trend. Thus when clues are showing that a share is about to lose value, he may think that it will soon go up again. The second bias, related to the level of self-confidence, leads him to over-estimate his own skill. He may then cause the price of the share to vary a lot, thus making the market more volatile. Now, the higher the volatility, the bigger the gains and losses.
The effects of these biases on markets
We first observed that the biases of market-makers affect the depth and liquidity of the market. A deep market is one in which the price remains relatively stable A liquid market is a market in which prices are not set aggressively (there is then a lot of buying and re-selling).
For instance, an optimistic market maker may think that the information he received is more reliable than it actually is and consider that his judgment is less crucial for his decision. He will then tend to overestimate the price of the asset, and traders (who buy and re-sell) will decrease the number of their transactions. When this market maker is too confident of his assessment, he will quote the share less aggressively and thus increase the liquidity of the market.
The tulip bulb crisis was the first speculative bubble and remains an outstanding example of a frenzied financial market. In 1636-1637, some bulbs were sold at more than 15 times the annual salary of the horticulturist and the volumes exchanged on the markets were completely unrelated to the actual number of available bulbs.
The first conclusion we can draw from this study is that market-makers who are too confident or not confident enough can make either profits or losses. When the market maker is pessimistic, but still trusts his own judgment, then price variations are seen to be weaker.
Prices increase mechanically, and the volume exchanged by rational traders is then low. Nevertheless, one conclusion of the study is that market-makers are able to take advantage of this market: the rise in prices does not affect the overall demand.
The results of this research also show that while traders with biased behavior trigger situations of disequilibrium, market-makers who are over-confident increase the likelihood that this will happen. For instance, an optimistic market maker amplifies excessive trading, which means that there are too many transactions. We can compare this to the Internet bubble, when both traders and market-makers thought they were witnessing the birth of a new economy and hence the likelihood of extreme growth.
The prices of shares in technology start-ups then went sky-high, uncorrelated with the actual profits of the companies and nevertheless, the number of transactions continued to increase. The March 2000 crash led to a recession in the sector but also in the economy in general with losses exceeding the profits made.
Moreover, we proved that there was an unexpected result: the fact that market-makers may behave in a biased way sometimes favors traders who are not very confident. In this case, a trader who lacks confidence may get better results than a trader who acts correctly. Consider for example a share whose value will not change. The optimistic market maker believes that it will increase and therefore sets a high price. A pessimistic trader believes that it will drop and therefore sells his shares, whereas a ‘standard’ trader will wait. In this case the pessimistic trader will make profits but not the ‘standard’ trader.
We may conclude from our research that the volatility observed may not only be due to traders, but may also be amplified by the attitude of market-makers. In fact, the last conclusion of the study is that in the extreme cases of levels of confidence, we observe excessive volatility and an excessive number of transactions. In a situation in which some traders lack confidence, market-makers who also lack confidence will cause rational traders to make too many transactions.
We are now working on a new more complex model which assumes that some market-makers act according to the way others do: in other words they no longer act as independent ‘black boxes’ but take into account the strategies of their counterparts.