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Technical analysis of stock trends using artificial neural networks
John, Pavel ; Petříčková, Zuzana (advisor) ; Pilát, Martin (referee)
Although the discipline has not received the same level of acceptance in the past, the technical analysis has been part of financial practice for centuries. One of the big issues was the absence of widely respected fully rational background that is necessary for the modern science. The presence of geometrical shapes recognized by a human eye in historical data charts remained as one of the most important tools till the last decades. Nowadays, it is possible to find commercial trading software which employs neural networks. However, a freely accessible tool is difficult to obtain. The aim of this work was to investigate the usability of applications of neural networks on the technical analysis and to develop a software tool that would implement the knowledge acquired. An application was created and a new promising trading strategy proposed along with experimental data. The advantages of the program presented include the ease of extensibility and a high variability in trading strategies setting.
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Spatial modeling of brain tissue
John, Pavel ; Neruda, Roman (advisor) ; Brom, Cyril (referee)
Neural connections in the human brain are known to be modified by experiences. Yet, little is known about the mechanism of the modification and its implications on the brain function. The aim of this thesis is to investigate what impact the spatial properties of brain tissue can have on learning and memory. In particular, we focus on the dendritic plasticity. We present a model where the tissue is represented by a two-dimensional grid and its structure is characterized by various connections between the grid cells. We provide a formal definition of the model and we prove it to be computational as strong as the Turing machine. An adaptation algorithm proposed enables the model to reflect the environmental feedback, while evolutionary algorithms are employed to search for a satisfactory architecture of the model. Implementation is provided and several experiments are driven to demonstrate the key properties of the model. Powered by TCPDF (www.tcpdf.org)
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Spatial modeling of brain tissue
John, Pavel ; Neruda, Roman (advisor) ; Brom, Cyril (referee)
Neural connections in the human brain are known to be modified by experiences. Yet, little is known about the mechanism of the modification and its implications on the brain function. The aim of this thesis is to investigate what impact the spatial properties of brain tissue can have on learning and memory. In particular, we focus on the dendritic plasticity. We present a model where the tissue is represented by a two-dimensional grid and its structure is characterized by various connections between the grid cells. We provide a formal definition of the model and we prove it to be computational as strong as the Turing machine. An adaptation algorithm proposed enables the model to reflect the environmental feedback, while evolutionary algorithms are employed to search for a satisfactory architecture of the model. Implementation is provided and several experiments are driven to demonstrate the key properties of the model. Powered by TCPDF (www.tcpdf.org)
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Technical analysis of stock trends using artificial neural networks
John, Pavel ; Petříčková, Zuzana (advisor) ; Pilát, Martin (referee)
Although the discipline has not received the same level of acceptance in the past, the technical analysis has been part of financial practice for centuries. One of the big issues was the absence of widely respected fully rational background that is necessary for the modern science. The presence of geometrical shapes recognized by a human eye in historical data charts remained as one of the most important tools till the last decades. Nowadays, it is possible to find commercial trading software which employs neural networks. However, a freely accessible tool is difficult to obtain. The aim of this work was to investigate the usability of applications of neural networks on the technical analysis and to develop a software tool that would implement the knowledge acquired. An application was created and a new promising trading strategy proposed along with experimental data. The advantages of the program presented include the ease of extensibility and a high variability in trading strategies setting.
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A ratio analysis and its application in system of allocation of overhead costs at job-order Manufacture Company
John, Pavel ; Wagner, Jaroslav (advisor) ; Novák, Vladimír (referee)
Principal and leading topics of this paper are overhead expenses in the process of their allocation and their assignment to the bearer of cost. In the theoretical part, the essential data for the practical part are summarized, definitely, these are the definition and basic classification of costs and expenses, then the characteristics and methods of the conventional costing process, considering methods of overhead expenses allocation. And further, in addition to the method TC (Total Cost), there is also the method ABC (Activity Based Costing) mentioned as a new and advanced view of the given problems. The aim of the practical part is to carry out an analysis of the state of overhead expenses control and administering in an allocation process, as well as assignment of overhead expenses to the Company "SIGMA GROUP a.s.". With the view to analyzed relations, namely pointing out to the assortment structure influence, a more detailed specification of the costs control should be realized aimed at solution of some problematic spheres within overhead distribution. Further to results of enquiry and examination there are some findings and recommendations specified.
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