A Radial Basis Function Approach to Financial Time Series Analysis

Title: en_US A Radial Basis Function Approach to Financial Time Series Analysis
Creator: en_US Hutchinson, James M.
Date: 2004-10-20T14:45:36Z
Date Available: 2004-10-20T14:45:36Z
Date Issued: en_US 1993-12-01
Identifier: en_US AITR-1457
uri: http://hdl.handle.net/1721.1/6783
Abstract: en_US Nonlinear multivariate statistical techniques on fast computers offer the potential to capture more of the dynamics of the high dimensional, noisy systems underlying financial markets than traditional models, while making fewer restrictive assumptions. This thesis presents a collection of practical techniques to address important estimation and confidence issues for Radial Basis Function networks arising from such a data driven approach, including efficient methods for parameter estimation and pruning, a pointwise prediction error estimator, and a methodology for controlling the "data mining'' problem. Novel applications in the finance area are described, including customized, adaptive option pricing and stock price prediction.
Extent: en_US 160 p.; 681549 bytes; 2849290 bytes
Format: application/octet-stream; application/pdf
Language: en_US
Relation: en_US AITR-1457
Subject: en_US radial basis functions; en_US option pricing; en_US parametersestimation; en_US time series prediction; en_US confidence; en_US stock market