PhD in Artificial Intelligence

Neural Networks in Finance and Investing [UB]


Type:
Semester:
ECTS: This course is a 20-hour-long seminar.
Teaching Points:
Offer:
Responsible Unit: LSI
Responsible: Salvador Torra Porras, Enric Monte
Language: English
Requirements:

GOALS

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


CONTENTS

  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 SEMINAR

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.