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Testing of Indicators for Technical Analysis in Stock Market Trading
Kaděra, Miroslav ; Hrubý, Martin (referee) ; Rozman, Jaroslav (advisor)
The topic of this thesis is testing of indicators for technical analysis, done from the point of view of their suitability for automatic stock market trading systems. The thesis tests behaviour of simple moving average, exponential moving average and the RSI indicator. A simple automatic trading system was made for each indicator. Profitability of the system was tested for various parameters of the used indicator. The testing was realized using real historical data of more than ten years historical period. The results show that profitability of the system can be increased by tens of percent. Even though for stable profitable trading the trader should work out a lot of other rules than just indicator parameters.
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Pattern Recognition in Temporal Data
Hovanec, Stanislav ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
This diploma work initially conduct research in the area of descriptions and analysis of time series. The thesis then proceed to introduce the problems of technical analysis of price charts as well as indicators, price patterns and method of Pure Price Action. The method Pure Price Action is demonstrated in this work in two practical examples of its application to real businesses with a view to discovering and analyzing price patterns, as well as analysis and prediction of future price and financial evolution. This analysis is an introduction to the processes of successful business, following on from this we discuss the theme of Pattern Recognition and the Instance Based Learning method. The practical aspect of this work is carried out with the aid of a MATLAB applied algorithm for the analysis of the price pattern Correction for sale and purchase in dynamic time segments, specifically in trading price graphs, like those used for commodities or stock trading. For the analysis of time series we use the Pure Price Action method. The Instance Based Learning method is used by the algorithm to recognize price patterns. The created algorithm is verified on real data of a 5 minute time series of the US Dow Jones price charts for the years 2006, 2007, 2008. The achieved accuracy is evaluated with the aid of Equity Curves.
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Testing of Indicators for Technical Analysis in Stock Market Trading
Kaděra, Miroslav ; Hrubý, Martin (referee) ; Rozman, Jaroslav (advisor)
The topic of this thesis is testing of indicators for technical analysis, done from the point of view of their suitability for automatic stock market trading systems. The thesis tests behaviour of simple moving average, exponential moving average and the RSI indicator. A simple automatic trading system was made for each indicator. Profitability of the system was tested for various parameters of the used indicator. The testing was realized using real historical data of more than ten years historical period. The results show that profitability of the system can be increased by tens of percent. Even though for stable profitable trading the trader should work out a lot of other rules than just indicator parameters.
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Pattern Recognition in Temporal Data
Hovanec, Stanislav ; Hynčica, Ondřej (referee) ; Honzík, Petr (advisor)
This diploma work initially conduct research in the area of descriptions and analysis of time series. The thesis then proceed to introduce the problems of technical analysis of price charts as well as indicators, price patterns and method of Pure Price Action. The method Pure Price Action is demonstrated in this work in two practical examples of its application to real businesses with a view to discovering and analyzing price patterns, as well as analysis and prediction of future price and financial evolution. This analysis is an introduction to the processes of successful business, following on from this we discuss the theme of Pattern Recognition and the Instance Based Learning method. The practical aspect of this work is carried out with the aid of a MATLAB applied algorithm for the analysis of the price pattern Correction for sale and purchase in dynamic time segments, specifically in trading price graphs, like those used for commodities or stock trading. For the analysis of time series we use the Pure Price Action method. The Instance Based Learning method is used by the algorithm to recognize price patterns. The created algorithm is verified on real data of a 5 minute time series of the US Dow Jones price charts for the years 2006, 2007, 2008. The achieved accuracy is evaluated with the aid of Equity Curves.
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Vyhodnocení technické analýzy a investiční strategie buy and hold na burze NYSE
Šíma, Karel
This thesis deals with the results comparison of investment strategies which are based on indicators of technical analysis and buy-and-hold investment strategy. Testing of these strategies was performed in the period from 30th September 2002 to 31st October 2012 on shares of companies that are being traded on the New York Stock Exchange. The results are finally compared with those published in other thesis or articles.
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