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Automated internet trading based on optimized physics models of markets

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24information09v3ingber-mondescu.dvi Chapter 9 Automated Internet Trading Based on Optimized Physics Models of Markets L. Ingber and R.P. Mondescu We describe a real-time, internet-based S&P futures trading system, including a description of general aspects of internet-mediated inter- actions with electronic exchanges. Inner-shell stochastic nonlinear dynamic models are developed, and Canonical Momenta Indicators (CMI) are derived from a fitted Lagrangian used by outer-shell trad- ing models dependent on these indicators. Recursive and adaptive optimization using Adaptive Simulated Annealing (ASA) is used for fitting parameters shared across these shells of dynamic and trading models. 1 Introduction Launching and exploiting a successful automated trading system im- plies accomplishing two major tasks, of almost equal significance: � designing and developing a robust trading model of markets of interest, � connecting the system to markets, addressing two problems – the communications hardware infrastructure, – the software interface. To develop a robust and consistent model of markets, we should re- mark that real-world problems are rarely solved in closed algebraic form, yet methods must be devised to deal with this complexity to 305 306 L. Ingber and R.P. Mondescu extract practical informations in finite time. This is indeed true in the field of financial engineering, where time series of various financial instruments reflect non-equilibrium, highly non-linear, possibly even chaotic (Peters 1991) underlying processes. A further difficulty is the huge amount of data necessary to be processed. Under these circum- stances, to develop models and schemes for automated, profitable trading is a non-trivial task. Apparently, the connectivity task involves mostly a programming ef- fort, where a host of technical tools may considerably simplify the task. In practice an equal amount of work must be devoted to a proper design of various software components and solving multiple hard

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