Decision Technologies for Computational Finance

. Ed(s): Apostolos-Paul, N. (Refenes, London Business School, UK); Burgess, Andrew N. (London Business School, UK); Moody, John E.

ISBN 10: 0792383087 / ISBN 13: 9780792383086

Edité par Kluwer Academic Publishers, 1998

A propos de cet article

Proceedings of the Fifth International Conference Computational Finance Editor(s): Apostolos-Paul, N. (Refenes, London Business School, UK); Burgess, Andrew N. (London Business School, UK); Moody, John E. Series: Advances in Computational Management Science. Num Pages: 479 pages, biography. BIC Classification: KFF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 26. Weight in Grams: 868. . 1998. Hardback. . . . .

N° de réf. du vendeur V9780792383086

Détails bibliographiques

• Titre: Decision Technologies for Computational Finance
• Éditeur: Kluwer Academic Publishers
• Date de parution: 1998
• Langue: anglais
• ISBN à 10 chiffres: 0792383087
• ISBN à 13 chiffres: 9780792383086
• Reliure: Couverture rigide
• État de l'article: New

A propos de ce titre

Synopsis

This volume contains selected papers that were presented at the International Conference COMPUTATIONAL FINANCE 1997 held at London Business School on December 15-17 1997. Formerly known as Neural Networks in the Capital Markets (NNCM), this series of meetings has emerged as a truly multi-disciplinary international conference and provided an international focus for innovative research on the application of a multiplicity of advanced decision technologies to many areas of financial engineering. It has drawn upon theoretical advances in financial economics and robust methodological developments in the statistical, econometric and computer sciences. To reflect its multi-disciplinary nature, the NNCM conference has adopted the new title COMPUTATIONAL FINANCE. The papers in this volume are organised in six parts. Market Dynamics and Risk, Trading and Arbitrage strategies, Volatility and Options, Term-Structure and Factor models, Corporate Distress Models and Advances on Methodology. This years' acceptance rate (38%) reflects both the increasing interest in the conference and the Programme Committee's efforts to improve the quality of the meeting year-on-year. I would like to thank the members of the programme committee for their efforts in refereeing the papers. I also would like to thank the members of the computational finance group at London Business School and particularly Neil Burgess, Peter Bolland, Yves Bentz, and Nevil Towers for organising the meeting.