Control systems identification in finance and economics

摘要

The research program that views economies as complex dynamic systems has received significant development over the past several decades and has become known as "Complexity Economics". The amount of information that economies create has grown exponentially. Most markets on formal exchanges have become electronic and they are consolidating into new organizational structures. The data from worldwide economic activity are widely available. However, the methods of analysis and interpretation of these data have not kept pace. Everyday hundreds of parameters are reported by corporations, governmental and nongovernmental agencies. Corporations make their earnings reports, financial events, and other information available. This flood of information is continuously analyzed in the various media. However, the effect of this influence is subject to varied interpretation. The research reported here seeks to define a method by which to quantify this influence using several globally-traded financial instruments. The methodology applies data analysis techniques analogous to those used for control of dynamical systems and links the response of trading activity to reports of economic activity. The important issues are (1) identification of the reports that have significant effect on trading activities in specific markets, and (2) determination of the extent, magnitude, and duration of the influence. We design a computational dynamical systems model from the derivatives of the market prices and use the external economic data as driving functions on the dynamical system. We explore a financial market system model consisting of the derivatives markets in crude oil, stock indices, and currencies.