Sat, 19 Jul 2008 05:17:13 BST CiteULike: pdlug's neuralnetwork http://www.citeulike.org/user/pdlug/tag/neuralnetwork 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/778023 <i>Science, Vol. 313, No. 5786. (28 July 2006), pp. 504-507.</i><br /><br />High-dimensional data can be converted to low-dimensional codes by training a multilayer neural network with a small central layer to reconstruct high-dimensional input vectors. Gradient descent can be used for fine-tuning the weights in such "autoencoder" networks, but this works well only if the initial weights are close to a good solution. We describe an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much better than principal components analysis as a tool to reduce the dimensionality of data. 10.1126/science.1127647 Reducing the Dimensionality of Data with Neural Networks GE Hinton RR Salakhutdinov doi:10.1126/science.1127647 Science, Vol. 313, No. 5786. (28 July 2006), pp. 504-507. 2006-07-28T15:16:42-00:00 2006 Science 313 5786 504 507 data network neural neuralnetwork