National Repository of Grey Literature 10 records found  Search took 0.01 seconds. 
The Use of Artificial Intelligence on Stock Market
Lajczyk, Pavel ; Budík, Jan (referee) ; Dostál, Petr (advisor)
This master's thesis deals with artificial neural networks and possibilities of their use on stock market. In next chapters of this thesis there are provided design and implementation of stock prices prediction tool. The implementation is done with use of the MATLAB software. The created prediction tool is then tested in a simple trading simulation and achieved results are discussed in the end
Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
The Use of Artificial Intelligence on Stock Market
Skočík, Michal ; Pekárek, Jan (referee) ; Budík, Jan (advisor)
Diploma thesis is focused on problematics of artificial neural networks and their usage on capital markets. There is a software created as a part of this diploma thesis which can load input data and create neural network that serves for share price forecast. This program is created in numerical computing environment MATLAB. Created neural network is tested under simulation of business model. Results are discussed upon examination of results of simulation.
The Use of Artificial Intelligence on Stock Market
Brnka, Radim ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The thesis deals with the design and optimization of artificial neural networks (specifically nonlinear autoregressive networks) and their subsequent usage in predictive application of stock market time series.
The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market
Ševčík, Martin ; Bobková, Irena (referee) ; Dostál, Petr (advisor)
This diploma thesis describes issues of use of means of artificial intelligence for the decision making support on stock market. It includes theoretical knowledge of technical, fundamental and psychological analysis and artificial intelligence. Based on these facts have been created specific suggestions for the use of artificial neural networks to forecast the future value of the index S&P 500 by using development environment of the MATLAB software.
The Use of Artificial Intelligence on Stock Market
Skočík, Michal ; Pekárek, Jan (referee) ; Budík, Jan (advisor)
Diploma thesis is focused on problematics of artificial neural networks and their usage on capital markets. There is a software created as a part of this diploma thesis which can load input data and create neural network that serves for share price forecast. This program is created in numerical computing environment MATLAB. Created neural network is tested under simulation of business model. Results are discussed upon examination of results of simulation.
Analysis and Prediction of Foreign Exchange Markets by Chaotic Attractors and Neural Networks
Pekárek, Jan ; Dostál, Petr (referee) ; Budík, Jan (advisor)
This thesis deals with a complex analysis and prediction of foreign exchange markets. It uses advanced artificial intelligence methods, namely neural networks and chaos theory. It introduces unconventional approaches and methods of each of these areas, compares them and uses on a real problem. The core of this thesis is a comparison of several prediction models based on completely different principles and underlying theories. The outcome is then a selection of the most appropriate prediction model called NAR + H. The model is evaluated according to several criteria, the pros and cons are discussed and approximate expected profitability and risk are calculated. All analytical, prediction and partial algorithms are implemented in Matlab development environment and form a unified library of all used functions and scripts. It also may be considered as a secondary main outcome of the thesis.
The Use of Artificial Intelligence on Stock Market
Lajczyk, Pavel ; Budík, Jan (referee) ; Dostál, Petr (advisor)
This master's thesis deals with artificial neural networks and possibilities of their use on stock market. In next chapters of this thesis there are provided design and implementation of stock prices prediction tool. The implementation is done with use of the MATLAB software. The created prediction tool is then tested in a simple trading simulation and achieved results are discussed in the end
The Use of Means of Artificial Intelligence for the Decision Making Support on Stock Market
Ševčík, Martin ; Bobková, Irena (referee) ; Dostál, Petr (advisor)
This diploma thesis describes issues of use of means of artificial intelligence for the decision making support on stock market. It includes theoretical knowledge of technical, fundamental and psychological analysis and artificial intelligence. Based on these facts have been created specific suggestions for the use of artificial neural networks to forecast the future value of the index S&P 500 by using development environment of the MATLAB software.
The Use of Artificial Intelligence on Stock Market
Brnka, Radim ; Budík, Jan (referee) ; Dostál, Petr (advisor)
The thesis deals with the design and optimization of artificial neural networks (specifically nonlinear autoregressive networks) and their subsequent usage in predictive application of stock market time series.

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