PL EN


2015 | 16 | 1 | 116-125
Article title

ARTIFICIAL NEURAL NETWORK SUPPORTING THE PROCESS OF INVESTING ON THE FOREIGN STOCK EXCHANGES

Content
Title variants
Languages of publication
EN
Abstracts
EN
The publication presents the use of artificial neural networks as a tool expert that supports the process of decision-making for the quarterly period to invest in selected stock exchanges. It proposes a set of 10 features of exchanges, which is of enough universal character that the approach presented in the publication may be useful for any chosen stock exchange. The conducted study was based on actual data.
Year
Volume
16
Issue
1
Pages
116-125
Physical description
Dates
published
2015
Contributors
  • Department of Regional Policy and Food Economy, University of Rzeszow , mhalicki@ur.edu.pl
References
  • Azoff, E. M. (1994) Neural Network Time Series Forecasting of Financial Markets,1st ed., Chichester, Wiley.
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  • Francis J.C. (2000), Inwestycje. Analiza i zarządzanie, Wig-Press, Warszawa, pp. 287-290.
  • Kalemli-Ozcan S., Papaioannou E., Peydr’o J.-E. (2013) Financial Regulation, Financial Globalization, and the Synchronization of Economic Activity, The Journal of Finance, Vol. 68, No. 3, pp. 1179-1228.
  • Lui Y.-H., Mole D. (1998) The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence, Journal of International Money and Finance No. 17, pp. 535-545.
  • Lynch A.-W. (2001) Portfolio choice and equity characteristics: characterizing the hedging demands induced by return predictability, Journal of Financial Economics, No. 62, pp. 67–130.
  • Markowitz H. (1952) Portfolio Selection, The Journal of Finance, Vol. 7, No. 1, pp. 77-91.
  • Menkhoff L. (2010) The use of technical analysis by fund managers: International evidence, Journal of Banking & Finance, No. 34, pp. 2573–2586.
  • Menkhoff L., Sarno L., Schmeling M., Schrimpf A. (2012) Carry Trades and Global Foreign Exchange Volatility, The Journal of Finance, Vol. 67, No. 2, pp. 681-718.
  • Morajda J., Domaradzki R. (2005) Application of Cluster Analysis Performed by SOM Neural Network to the Creation of Financial Transaction Strategies, Journal of Applied Computer Science, Vol. 13. No 1, pp. 87-98.
  • Pokharel G., Deardon R. (2014) Supervised learning and prediction of spatial epidemics, Spatial and Spatio-temporal Epidemiology, No. 11, pp. 59–77.
  • WFE, (http://www.world-exchanges.org/) [Accessed 28 August 2015].
Document Type
Publication order reference
Identifiers
YADDA identifier
bwmeta1.element.desklight-20406e31-97a3-4479-a2b2-168557b26f41
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