Specialization and herding behavior of trading firms in a financial market

Abstract

The understanding of complex social or economic systems is an important scientific challenge.Here we present a comprehensive study of the Spanish Stock Exchange showing that most financial firms trading in that market are characterized by a resulting strategy and can be classified in groups of firms with different specialization. Few large firms overally act as trending firms whereas many heterogeneous firm act as reversing firms. The herding properties of these two groups are markedly different and consistently observed over a four-year period of trading.

How Markets Slowly Digest Changes in Supply and Demand

“…The presence of distinct classes of institutions and their mutual interaction has been investigated in a recent work by Lillo et al [2008b]. This study clearly identifies classes of institutions that are characterized by having a similar trading behavior.…”

“…Although this flow differs from longer horizon trades, which are supposed to be economically informed, these market-making strategies routinely use sophisticated short-term prediction tools and exploit any profitable high-frequency signals. The above simplified separation of market participants into two broad classes, speculators/liquidity hunters that trade at medium to low frequencies and market-makers/liquidity providers at high frequencies is both realistic and useful to understand the ecology of financial markets (Handa and Schwartz [1996], Farmer [2002], Wyart et al [2006], Lillo et al [2008b]). The competition between these two categories of traders allows one to make sense of a number of empirical facts, we believe much more usefully than noise trader models.…”

“…Nonetheless, several recent papers have demonstrated that it is possible to extract useful information about the identity of individual traders using such information, e.g. showing that there are consistent behaviors that are persistent in time associated with particular membership codes, that such behaviors can be organized into a taxonomic tree, and that it is possible to detect the presence of large institutional trades (Lillo et al [2008b], Zovko and Farmer [2007], Vaglica et al [2008]). …”

Identification of Clusters of Investors from Their Real Trading Activity in a Financial Market

“…Some papers [22,23,24,25,26,27] have investigated databases where it is possible to track the trading behavior of market members of the exchange. Members are credit entities and investment firms which are the only firms entitled to trade directly.…”

“…Therefore they trade on behalf of a large number of investors. Despite this fact, recent studies have shown that, probably due to a customer specialization, market member data allows to identify trading strategies, such as order splitting [23,24,25], liquidity provision [27], and contrarian or momentum trading [22]. In particular in this last study authors have performed an analysis of the linear correlation matrix of the trading activity of market members of the Spanish Stock Exchange in order to identify groups of investors (market members in this case).…”