PhD in Artificial Intelligence

42049 - Neural Networks in Finance (XNF) [UB]


Type: S3 Course
Semester: Spring
ECTS: 3 ECTS
Teaching Points: 7.5
Offer: Annual
Responsible Unit: UB
Responsible: Salvador Torra (UB), Enric Monte (UPC)
Language: English
Requirements:

GOALS

The Objective is to present of systematic form the possible applications of neural networks applications in Finance


CONTENTS

See detailed current content here.

  1. Neural Networks Overview
  2. Equity Applications (Modelling Stock Returns)
  3. Foreign Exchange applications (trading)
  4. Bond Applications (Rating)
  5. Macroeconomic Applications
  6. Corporate Performance (Business Failure Prediction)


CHARACTERISTICS OF THE COURSE

Main topics are Neural Networks and Finance


BIBLIOGRAPHY

  • Refenes, A.P. (1995). Neural Networks in the Capital Markets, Wiley.
  • Trippi R.R. y Turban. E. (1993). Neural Networks in Finance and Investing. Probus Publishing Company.
  • Zapranis A. y Refenes, A.P.(1999). Principles of Neural Model Identification, Selection and Adequacy, Springer.
  • Trippi, R.R. y Lee, J.K. (1992). Artificial Intelligence in Finance & Investing. State-of-the-Art Technologies for Securities Selection and Porfolio Management, IRWIN Professional Publishing.
  • Jimmy Shadbolt and John G. Taylor (2002). Neural Networks and the financial Markets, Springer.