Fr. 115.20

Decision Technologies for Financial Engineering - Proceedings of the Fourth International Conference on Neural Networks in the Capital Markets (Nncm '96)

English · Paperback / Softback

Shipping usually takes at least 4 weeks (title will be specially ordered)

Description

Read more










This volume selects the best contributions from the Fourth International Conference on Neural Networks in the Capital Markets (NNCM). The conference brought together academics from several disciplines with strategists and decision makers from the financial industries.The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering.Applications -- risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets -- equity; foreign exchange; bond; commodity; derivatives; Approaches -- data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic.The chapters emphasizes in-depth and comparative evaluation with established approaches.

Product details

Assisted by Yaser Abu-Mostafa (Editor), Apostolos-Paul Refenes (Editor), Andreas S Weigend (Editor), Andreas S. Weigend (Editor)
Publisher World Scientific Publishing Company
 
Languages English
Product format Paperback / Softback
Released 11.12.1997
 
EAN 9789810231248
ISBN 978-981-02-3124-8
No. of pages 436
Series Progress in Neural Processing
Progress In Neural Processing
Subject Social sciences, law, business > Business > General, dictionaries

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.