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Editors' foreword

Published:2019-08-08 Issue:9 Volume:19 Page:1445-1448
ISSN:1469-7688
Container-title:Quantitative Finance
language:en
Short-container-title:Quantitative Finance

Author:

Creamer Germán G.¹²^ORCID,Kazantsev Gary³^ORCID,Aste Tomaso⁴^ORCID

Affiliation:

1. School of Business, Stevens Institute of Technology, Hoboken, NJ, USA

2. Visiting Scholar, Stern School of Business, New York University, New York, NY, USA

3. Bloomberg, New York, NY, USA

4. Department of Computer Science, University College London, London, UK

Publisher

Informa UK Limited

Subject

General Economics, Econometrics and Finance,Finance

Link

https://www.tandfonline.com/doi/pdf/10.1080/14697688.2019.1638160

Reference23 articles.

1. Using genetic algorithms to find technical trading rules1Helpful comments were made by Adam Dunsby, Lawrence Fisher, Steven Kimbrough, Paul Kleindorfer, Michele Kreisler, James Laing, Josef Lakonishok, George Mailath, and seminar participants at Institutional Investor, J.P. Morgan, the NBER Asset Pricing Program, Ohio State University, Purdue University, the Santa Fe Institute, Rutgers University, Stanford University, University of California, Berkeley, University of Michigan, University of Pennsylvania, University of Utah, Washington University (St. Louis), and the 1995 AFA Meetings in Washington, D.C. We are particularly grateful to Kenneth R. French (the referee), and G. William Schwert (the editor) for their suggestions. Financial support from the National Science Foundation is gratefully acknowledged by the first author and from the Academy of Finland by the second and from the Geewax-Terker Program in Financial Instruments by both. Correspondence should be addressed to Franklin Allen, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6367.1

2. A neural network versus Black-Scholes: a comparison of pricing and hedging performances

3. A neural network approach for credit risk evaluation

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