Mon, 07 Jul 2008 16:39:33 BST CiteULike: pdlug neuralnet http://www.citeulike.org/user/pdlug/tag/neuralnet CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/pdlug/article/2751744 <i>Social Science Research Network Working Paper Series</i><br /><br />This paper proposes an intelligent combination of neural network theory and financial statistics for the detection of statistical arbitrage opportunities in specific pairs of stocks. The proposed intelligent methodology is based on a class of neural network-GARCH autoregressive models for the effective handling of the dynamics related to the statistical mispricing between relative stock prices. The performance of the proposed intelligent trading system is properly measured with the aid of profit & loss diagrams, for a number of different experimental settings (i.e. sampling frequencies). First results seem encouraging; nevertheless, further experimentation on the optimal sampling frequency, the forecasting horizon and the points of entry and exit is necessary, in order to achieve highest economic value when transaction costs are taken into account. An Intelligent Statistical Arbitrage Trading System NICK Kondakis Nikos Thomaidis Social Science Research Network Working Paper Series 2008-05-04T00:03:09-00:00 Social Science Research Network Working Paper Series arbitrage garch neuralnet neuralnetwork statarb statistics trading http://www.citeulike.org/user/pdlug/article/878138 <i>PNAS, Vol. 79, No. 8. (15 April 1982), pp. 2554-2558.</i><br /><br />Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices. 10.1073/pnas.79.8.2554 Neural Networks and Physical Systems with Emergent Collective Computational Abilities JJ Hopfield PNAS, Vol. 79, No. 8. (15 April 1982), pp. 2554-2558. 2006-09-29T17:13:47-00:00 1982 PNAS 79 8 2554 2558 ai computation intelligence neural neuralnet neuralnetworks