Monitoring for Disruptions in Financial Markets

Machine learning algorithms for time series in financial markets

This research is related to the usefulness of different machine learning methods in forecasting time series on financial markets. The main issue in this field is that economic managers and scientific society are still longing for more accurate forecasting algorithms. Fulfilling this request leads to an increase in forecasting quality and, therefore, more profitability and efficiency. In this pa...

Markets for Financial Information

Chaos in Financial Markets

This paper reviews the literature on chaos in financial time series, and concludes that there is little evidence of low-dimensional chaos in financial markets.

Hamiltonian in Financial Markets

A statistical physics model for the time evolutions of stock portfolios is proposed. In this model the time series of price changes are coded into the sequences of up and down spins. The Hamiltonian of the system is introduced and is expressed by spin-spin interactions as in spin glass models of disordered magnetic systems. The interaction coefficients between two stocks are determined by empir...

Experimentation in Financial Markets

I this paper, we use a unique data set on the Italian interdealer bond market to empirically estimate the process of strategic experimentation. The results show how the information generated in the process of interdealer trading affects the incentive to experiment. Upon receipt of an order, dealers deliberately engage in trade with other dealers either to exploit the information contained in th...