Predicting Bonds Using the Linear Relevance Vector Machine

  • Neep Hazarika
  • John G. Taylor
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

As described earlier in this book, a large part of the problem in modelling financial markets is to select the relevant inputs. Even if we restrict ourselves to only 40 input time series, and allowing for a choice of lags of up to 24, this still leads to a selection process involving up to 960 variables. This is difficult to achieve automatically in a single step, so various methods have been developed in an attempt to solve this combinatorial explosion.

Keywords

Shrinkage 

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Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Neep Hazarika
    • 1
  • John G. Taylor
    • 2
    • 1
  1. 1.Econostat New Quant LtdWargraveUK
  2. 2.Kings CollegeLondonUK

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