Similarity based financial networks: tracking investor's trading behavior
- Day - Time: 12 April 2011, h.15:00
- Place: Area della Ricerca CNR di Pisa - Room: C-29
- Fabrizio Lillo (Scuola Normale Superiore di Pisa, Dipartimento di Fisica, Università di Palermo & Santa Fe Institute, U.S.A.)
Networks are a powerful tool to explore the interaction structure of many complex systems. In the vast majority of studied networks a link between two nodes identifies a direct interaction (e.g. trading activity, credit relation, etc) between the two nodes. Similarity based networks are a different class of networks where the presence of a link identifies a similarity between the two nodes. Here I consider two important applications of similarity based networks to financial markets. In the first one the nodes are stocks traded in a financial market and a link identifies a similarity in price dynamics. This network allows to identify clusters of stocks with similar price comovement and it is therefore useful in monitoring the whole market dynamics and in portfolio optimization. In the second case I consider similarity based networks of investors in the Finnish stock market. A suitably designed methodology allows to identify in an unsupervised way classes of investors with a common investment behavior. We study the investment behavior of these identified classes and we consider their interaction. In both cases a special emphasis is given to the behavior of similarity based financial networks in the presence of extreme market movements.