EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 91 (2021) SHS Web Conf., 91 (2021) 01041 References
Open Access
Issue
SHS Web Conf.
Volume 91, 2021
Innovative Economic Symposium 2020 – Stable Development in Unstable World (IES2020)
Article Number 01041
Number of page(s) 11
Section Stable Development in Unstable World
DOI https://doi.org/10.1051/shsconf/20219101041
Published online 14 January 2021
  1. M. Vochozka, J. Horak, T. Krulicky, Innovations in management forecast: Time development of stock prices with neural networks. Marketing and Management of Innovations, 2020(2), 324-339 (2020). [CrossRef] [Google Scholar]
  2. P. Suler, J. Horak, T. Krulicky, Validation of the prediction of ČEZ stock prices. Littera Scripta, 13(1), 194-210 (2020). [CrossRef] [Google Scholar]
  3. J. Vrbka, Z. Rowland, Stock price development forecasting using neural networks. SHS Web of Conferences - Innovative Economic Symposium 2017: Strategic Partnership in International Trade (2017). [Google Scholar]
  4. B. Groda, J. Vrbka, Prediction of stock price developments using the Box-Jenkins method. SHS Web of Conferences - Innovative Economic Symposium 2017: Strategic Partnership in International Trade (2017). [Google Scholar]
  5. H. Zhou, Y. He, Y.X. Jin, Modelling for forecasting of pattern recognition - based on comparison and analysis be-tween U.S. stock market and Chinese stock markets. Proceedings of the 2016 International Conference on Applied Mathematics, Simulation and Modelling, 41, pp. 1-5 (2016). [Google Scholar]
  6. D. Stramirovic, D. Sarvan, V. Miljkovic, S. Blesic, Analysis of cyclical behavior in time series of stock market returns. Communications in Nonlinear Science and Numerical Simulation, 54, 21-33 (2018). [CrossRef] [Google Scholar]
  7. L.J. Chmielewski, M. Janowicz, A. Orłowski, Advances in intelligent systems and computing. Springer Verlag, 403, pp. 641-647 (2016). [CrossRef] [Google Scholar]
  8. A. Kolkova, Indicators of technical analysis on the basis of moving averages as prognostic methods in the food industry. Journal of Competitiveness, 10, 102-119 (2018). [CrossRef] [Google Scholar]
  9. M. Frömmel, K. Lampaert, Does frequency matter for intraday technical trading? Finance Research Letters, 18, 177-183 (2016). [CrossRef] [Google Scholar]
  10. T. Shalini, S. Pranav, S. Utkarsh, Picking buy-sell signals: A practitioner’s perspective on key technical indicators for selected Indian firms. Studies in Business and Economics, 14, 205-219 (2019). [CrossRef] [Google Scholar]
  11. V.A. Sobreiro, T.R.C.C. da Costa, R.T.F. Nazario, J.L.E. Silva, E.A. Moreira, M.C. Lima, H. Kimura, J.C.A. Zambrano, The profitability of moving average trading rules in BRICS and emerging stock markets. North American Journal of Economics and Finance, 38, 86-101 (2016). [CrossRef] [Google Scholar]
  12. P. Marek a B. Sediva, Optimization and testing of RSI. In: Financial management of firms and financial institutions. Ostrava: VŠB-Technical University of Ostrava, Czech Republic, pp. 530-537 (2017). [Google Scholar]
  13. F. García, F. Guijarro, J. Oliver, R. Tamošiūnienė, Hybrid fuzzy neural network to predict price direction in the German DAX-30 index. Technological and Economic Development of Economy, 24, 2161-2178 (2018). [CrossRef] [Google Scholar]
  14. B.W. Crowell, Y. Bock, Z. Liu, Single-station automated detection of transient deformation in GPS time series with the relative strength index: A case study of Cascadian slow slip. Journal of Geophysical Research: Solid Earth, 121, 9077-9094 (2016). [CrossRef] [Google Scholar]
  15. P. Rihova, M. Svoboda, Profitability of selected technical analysis indicators. European Financial Systems 2018: Proceedings of the 15th International Scientific Conference, pp. 591-598 (2018). [Google Scholar]
  16. I. Podhorska, K. Valaskova, V. Stehel, T. Kliestik, Possibility of company goodwill valuation: Verification in Slovak and Czech Republic. Management & Marketing-Challenges for the Knowledge Society, 14(3), 338-356 (2019). [CrossRef] [Google Scholar]
  17. K. Valaskova, T. Kliestik, L. Svabova, P. Adamko, Financial risk measurement and prediction modelling for sustainable development of business entities using regression analysis. Sustainability, 10(7) (2018). [CrossRef] [Google Scholar]
  18. A. Moreira, T. Muir, Volatility-managed portfolios. Journal of Finance, 72, 1611-1644 (2017). [CrossRef] [Google Scholar]
  19. S. Basak, A. Pavlova, A model of financialization of commodities. Journal of Finance, 71, 1511-1556 (2016). [CrossRef] [Google Scholar]
  20. S.R. Baker, N. Bloom, S.J. Davis, Measuring economic policy uncertainty. Quarterly Journal of Economics, 131, 1593-1636 (2016). [CrossRef] [Google Scholar]
  21. A.R. Arévalo Murillo, Short-term forecasting of financial time series with deep neural networks. Thesis: Ingeniería de Sistemas (2016). [Google Scholar]
  22. E. Chong, C. Han, F.C. Park, Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies. Expert Systems with Applications, 83, 187-205 (2017). [CrossRef] [Google Scholar]
  23. The Coca-Cola Company (KO). Yahoo Finance [online]. Available at: https://finance.yahoo.com/quote/KO/history?p=KO (2020). [Google Scholar]
  24. A. Hayes. Investopedia [online]. New York. Available at: https://www.investopedia.com/terms/d/dowtheory.asp (2019). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.