Machine Learning In Computational Finance

Machine Learning In Computational Finance

Practical algorithms for building artificial intelligence applications

LAP Lambert Academic Publishing ( 2012-05-12 )

€ 49,00

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In the first part of the book practical algorithms for building optimal trading strategies are constructed. Both non-restricted and risk-adjusted (Sterling ratio and Sharp ratio) trading strategies are considered. Constructed optimal trading strategies can be used as training dataset for the AI application. In the next part of the book one particular type of Machine Learning - finding optimal linear separators - is considered, and combinatorial deterministic algorithm for computing minimum linear separator set in 2 dimensions is given. In the last part of the book presented efficient algorithms for preventing overfitting. Shape constrained regression is an accepted methodology to deal with overfitting. Algorithms for nonparametric shape constrained regression in the form of isotonic and unimodal regressions are given.

Book Details:

ISBN-13:

978-3-659-11889-0

ISBN-10:

3659118893

EAN:

9783659118890

Book language:

English

By (author) :

Victor Boyarshinov

Number of pages:

88

Published on:

2012-05-12

Category:

Money, Bank, Stock exchange