PL EN


2013 | 154 | 32-44
Article title

Implementacja i ocena systemu eksperckiego sieci neuronowych w analizie rynku akcji

Content
Title variants
EN
Implementati on and Evaluation of the Neural Network System for Stock Market Data Analysis
Languages of publication
PL
Abstracts
EN
The application of neural network system for multi-dimensional stock market data analysis is presented in the paper. Developed system predicts stock price movements based on daily quotation data like: volume, minimum and maximum session price, opening and closing price. Several studies were carried out, to compare systems investment decisions, with decisions that were made on the basis of some commonly used methods of stock market analysis. These methods are: MACD, Bootstrap, Markowitz Portfolio. For valuation purpose, the real stock market data of the four largest Polish companies were used. All companies are quoted on the Warsaw Stock Exchange and belong to the WIG 20 index. For the benchmarking, only stock data from the year 2009 were used. In order to enrich the benchmarking tests, three investment scenarios were added. First known as the skeptical assume that only incorrect investment decisions were made. Second known as the optimistic assume that only correct investment decisions were made. Last one known as passive assume that no investment decision were made - it is so called "buy and hold" conception. The benchmarking results confirmed, that the neural network system is able to make investment decisions, that significantly increase the profitability of the investment portfolio. Neural network system provide investment suggestions, that can be considered as an alternative to other commonly used methods of stock market analysis. However statistical tests proved a high correlation between quality of systems investment decisions and market trend and lack of correlation to the "optimistic" scenario. Neural network systems may help in investment process, but cannot be considered as fully reliable way of investment process automation.
Year
Volume
154
Pages
32-44
Physical description
Contributors
References
  • Appel G., Dobson E., Understanding MACD, Traders Press 2008.
  • Boyle P., Seng Tan K., Quasi-Monte Carlo Methods in Numerical Finance, "Management Science" 1996.
  • Brock W., Lakonishok J., Lebaron B., Simple Technical Trading Rules and the Stochastic Properties of Stock Returns, "The Journal of Finance" 1992.
  • Chrzan P., Timofiejczuk G., Porównanie zastosowania sieci neuronowych i modeli klasy GARCH w prognozowaniu stóp zwrotu. Część 1, s. 147-156, w: Rynek Kapitałowy. Skuteczne inwestowanie, red. W. Tarczyński, Uniwersytet Szczeciński, Szczecin 2002.
  • Czekała M., Analiza fundamentalna i techniczna, Akademia Ekonomiczna, Wrocław 2007.
  • Davison, A., Hinkley V., Bootstrap Methods and their application, Cambridge University Press 1997.
  • Edwards R., Magee J.,. Bassetti W.H.C,. Technical Analysis of Stock Trends, Ninth ed. Boca Raton: CRC Press 2007.
  • Karczyński T., Techniki sztucznej inteligencji w zarządzaniu - sieci neuronowe w analizie cen akcji, Politechnika Wrocławska, Wrocław 2010.
  • Mamaysky H., Wang J., Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation, "The Journal of Finance" 2000.
  • Markowska-Kaczmar U., Sieci neuronowe w zastosowaniach, Oficyna EXIT, Warszawa 2003.
  • Maryański W., Podstawy analizy technicznej, wypracowanie: 2005.04.05.
  • Mielczarek B., Metody próbkowania w symulacji Monte Carlo, Wydział Informatyki i Zarządzania PWR, Wrocław 2007.
  • Park C., Irwin S., The Profitability of Technical Analysis: A Review, AgMAS Project Research Report 2004-04, University of Illinois at Urbana-Champaign.
  • Pliński M., Rudkowska D., Rutkowski L., Sieci neuronowe, algorytmy genetyczne i systemy rozmyte, PWN, Łódź-Warszawa 1997.
  • Radosiński E., Systemy informatyczne w dynamicznej analizie decyzyjnej, PWN, Warszawa 2005.
  • Rutkowski L., Metody i techniki sztucznej inteligencji. Inteligencja obliczeniowa, PWN, Warszawa 2005.
  • Tarczyński W., Analiza portfelowa na giełdzie papierów wartościowych, PTE, Szczecin 1996.
  • Cesari R., Cremonini D., Benchmarking, Portfolio Insurance and Technical Analysis: A Monte Carlo Comparison of Dynamic Strategies of Asset Allocation. "Journal of Economic Dynamics and Control" 2003.
Document Type
Publication order reference
Identifiers
ISSN
2083-8611
YADDA identifier
bwmeta1.element.desklight-032c4c1d-0c18-4817-b100-aac9ef038dd3
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.