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2016 | 5 | 4 | 508-519

Article title

USING NEURAL NETWORKS TO PREDICTION ON WARSAWS STOCK EXCHANGE

Authors

Content

Title variants

Languages of publication

EN

Abstracts

EN
The paper describes an experiment consisting of the application of artificial intelligence algorithms in the processes of predicting the stock market. A special tool was developed to evaluate whether artificial neural networks can predict stock market behavior. The aim of this paper was also to test how neural networks tapping trivial and easily attainable input data perform in an environment which is both complex and difficult to predict.

Year

Volume

5

Issue

4

Pages

508-519

Physical description

Dates

published
2016

Contributors

  • Institute of Information Technology, Lodz University of Technology

References

  • Bronw C. (2012) Technical Analysis for the Trading Professional, Mc Graw Hill
  • Elder A. (2012) Zawód inwestor giełdowy - Psychologia rynków. Taktyka inwestycyjna. Zarządzanie portfelem, Wolters Kluwer
  • Fast Artificial Neural Network Library (FANN) http://leenissen.dk
  • Łędzewicz M (2014). Mechanizmy sztucznej inteligencji w predykcji zachowań giełdowych, Politechnika Łódzka
  • Wanjawa B. A (2014) Neural Network Model for Predicting Stock Market Prices, LAP LAMBERT Academic Publishing
  • Witkowska D. (2002) Sztuczne sieci neuronowe i metody statystyczne: wybrane zagadnienia finansowe, C.H. Beck Łódź
  • Witkowska D. (1990) Sztuczne sieci neuronowe w analizach ekonomicznych, C.H. Beck Łódź
  • Zirilli J.S.(1996) Financial Prediction Using Neural Networks, Wiley
  • Azoff M.E. (1994) Neural Network Time Series: Forecasting of Financial Markets Wiley
  • http://aitech.pl/sphinx/pakiet-sphinx/ Aitech artificial intelligence laboratory
  • Gately E. (1995) Neural Networks for Financial Forecasting, Wiley
  • Trippi R.R.(1992) Neural Networks in Finance and Investing: Using Artificial Intelli-gence to Improve Real-World Performance, Probus Pub Co
  • Pring M.J. (2015) Martin Pring’s Introduction to Technical Analysis, Mc Graw Hill Education

Document Type

Publication order reference

Identifiers

ISSN
2084-5537

YADDA identifier

bwmeta1.element.desklight-e0473a04-70d4-469b-8ea6-7ce08400aba6
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