Accession Number : ADA276408


Title :   A Radial Basis Function Approach to Financial Time Series Analysis


Descriptive Note : Doctoral thesis,


Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB


Personal Author(s) : Hutchinson, James M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a276408.pdf


Report Date : Dec 1993


Pagination or Media Count : 158


Abstract : 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. Radial basis functions, Option pricing, Parameter estimation, Time series prediction, Confidence, Stock market.


Descriptors :   *FINANCIAL MANAGEMENT , *MULTIVARIATE ANALYSIS , *TIME SERIES ANALYSIS , MATHEMATICAL MODELS , ERRORS , NONLINEAR ANALYSIS , SPECIAL FUNCTIONS(MATHEMATICS) , COMPUTER APPLICATIONS , THESES , PREDICTIONS , PARAMETERS


Subject Categories : Economics and Cost Analysis
      Statistics and Probability


Distribution Statement : APPROVED FOR PUBLIC RELEASE