The master thesis is focused on detailed description of technical analysis and familiarization with fundamental analysis options. Theoretical part of the thesis is focused on describing the market behaviours, the most used technical indicators and tools which are used during market trading. Following part describes the most used trading platform and its weaknesses. Practical part designs and implements tools for elimination of the platform weaknesses.

This diploma thesis deals with the Triple Screen trading system in the theoretical and practical level. As part of the work semiautomatic trading system, which focuses on trading with corn is designed. Previously, there are discussed theoretical assumptions necessary for the successful implementation of the trading system. There is explained and described deal with corn and principles and possibilities nowadays. The practical part includes the creation of custom application in Matlab development environment and scripting language. Using this application is simulated trading corn with selected trend indicators and oscillators. Using historical data there is found the best combination of indicators and it is subsequently applied on the following dates.

This bachelor thesis aims to investigate household electricity supply and demand during a crisis. Both quantitative and qualitative aspects of crisis preparedness and household electricity demand are considered. In this thesis, the subject is studied by conducting simulations of electricity consumption as well as retrieving theoretical framework and concepts from literature and interviews. Emphasis will be on how the cost of a lithium-ion battery storage, that supplies households with electricity during power outages, is affected by households’ behavioural patterns regarding electricity use. To estimate household electricity demand, data are utilized from a stochastic model which simulates household members electricity usage patterns. Three different scenarios are modelled, representing varying household electricity reliance, across different lengths of power outages. The first scenario illustrates households’ normal electricity demand. The second scenario represents a changed behaviour pattern leading to a reduced electricity demand. The third and last scenario concerns a case where households with adequate crisis preparedness are taken into account, resulting in a linearly scaled down electricity demand. Gaps in the distribution of responsibility between municipalities and households concerning crisis preparedness are brought up and discussed. The thesis highlights households with unique needs that risk not getting the support needed from the municipality in case of a crisis. The result shows that meeting the electricity demand for Knivsta urban area during a power outage by utilizing a battery storage would be very costly for the municipality. Despite the cost reduction from decreased electricity consumption, large investments are still required. A battery storage system on that scale might not be the only nor most optimal solution for crisis preparedness. Instead, opportunities are found by challenging prevailing norms of constant electricity supply and increased resilience among households. Lastly, possible solutions less costly for the municipality are presented.

在這篇文章裡我們採用了White所提出的真實檢驗法(Reality Check)來解決探勘資料偏誤(Data-snooping bias)的問題，結果顯示從1980年到2008年間，技術分析法則的確可以幫助投資人在日圓兌美元及英鎊兌美元這兩個外匯市場獲利；我們也發現在外匯市場最普遍的技術分析方式─移動平均法(moving average)表現不如其他的技術分析法則，而通道突破法(channel break-out)的表現則明顯優於其他技術分析法則。 除了檢驗技術分析方法的獲利性之外，我們也嘗試著探討技術分析方法的獲利性與央行干預之間的關係，追隨Szacmary與Mathur在1997年所發表的論文，我們把技術分析法則擴充為在真實檢驗法中所使用到的所有法則，並且盡可能加長分析的期間。結果顯示技術分析法則的獲利與央行干預並不存在任何特定的關係。 / In this paper we construct a huge universe of simple trading rules and apply White’s Reality Check to mitigate data-snooping bias then detect the profitability of technical trading rules. We find that technical analysis is useful no matter in the full sample time or each subsample period. The channel break-out method outperforms the other methods in our finding while the profitability of the most commonly used moving average method is worse than the others. Furthermore, we inspect the relationships between the returns of technical trading rules and central bank intervention. The results suggest that there’s no evident relationship between the return series of trading rules and central bank intervention and are not consistent with the view of our following previous study.

This diploma thesis deals with the technical analysis with the emphasis on creating, testing and using of trading systems. Its objective is to find out whether it is possible for a trader to design and trade his own profitable trading system with widely accessible tools and methods. First part of the thesis concentrates among other things on the explanation of stock valuation principles, description of tested shares and time period. The second and third chapters fully describe the process of trading system development and the analysis of results of both trading systems. Last chapter is devoted to the interconnection of European stock markets, which is explored by the means of correlation analysis among different stock indexes. The correlation coefficients show a strong link of the markets and the rising level of integration of European markets.

First chapter describes International Financial Markets. Second chapter describes market fundamental analysis. Third chapter describes market technical analysis and efficient market hypothesis testing. Fourth chapter discusses market psychological analysis. Fifth chapter encompasses other theoretical background to be used in application. Sixth chapter deals with application of fundamental and technical analysis on a tennis betting market having found parallels between the sports betting markets and financial markets.

Submitted by Verena Pereira (verenagoncalves@uefs.br) on 2018-07-20T23:30:41Z No. of bitstreams: 1 Disserta??oMestradoVers?oFinalCD.pdf: 2552948 bytes, checksum: 021c9ef4954fba969e5860759364257e (MD5) / Made available in DSpace on 2018-07-20T23:30:41Z (GMT). No. of bitstreams: 1 Disserta??oMestradoVers?oFinalCD.pdf: 2552948 bytes, checksum: 021c9ef4954fba969e5860759364257e (MD5) Previous issue date: 2018-03-06 / The biggest challenge for stock market traders is to identify the timing to enter and exit in a trade. This research uses a trading system based on bullish and bearish candlesticks patterns to identify buy and sell signals in the brazilian?s stock market with exit through the chandelier method. The trading system was tested during the period 2005 and 2010 for application in two strategies between 2011 and 2016. The statistical significance and robustness of the strategies were evaluated through skewness, kurtosis, Monte Carlo, z-score, t-test and walk-forward. They revealed some prediction in bullish candlesticks standards / O maior desafio para os investidores no mercado de a??es ? identificar o momento para entrar e sair de uma negocia??o. Esta pesquisa utilizou um sistema de negocia??o baseado em padr?es candlesticks de alta e de baixa para gerar sinal de compra/venda no mercado brasileiro de a??es e vender/comprar por meio do m?todo chandelier exit. O sistema de negocia??o foi testado para simular negocia??es no per?odo entre 2005 e 2010 e para aplica??o em duas estrat?gias no per?odo entre 2011 e 2016. A signific?ncia estat?stica e robustez das estrat?gias foram avaliadas por meio daskewness, kurtosis, Monte Carlo, z-score, t-test e walk-forward. Eles revelaram algum grau de predi??o nos padr?es de candlesticks de alta

Partindo dos conceitos estabelecidos pela Hipótese dos Mercados Eficientes (HME), a qual questiona a validade da Análise Gráfica, e considerando as críticas feitas à HME pelos defensores das assim chamadas Finanças Comportamentais, e outros, este estudo procurou detectar a existência de uma relação entre os sinais gráficos observados no dia-a-dia do mercado de ações brasileiro e as tendências que lhes sucedem, durante um período de 8 anos, para um número de papéis. Os resultados obtidos neste trabalho evidenciam a existência de tal relação, sugerindo a validade da utilização da Análise Gráfica como instrumento para a previsão de preços no mercado de ações brasileiro, no período considerado. / Based on the principles established by the Efficient Market Hypothesis (EMH), which argues that the Technical Analysis is of no value in order to predict future prices of securities, and considering the criticism to the EMH by the advocates of the so called Behavioral Finance, and others, this work tried to detect the existence of a relationship between the graphic signals observed day by day in the Brazilian stock market and the trends which happen after these signals, within a period of 8 years, for a number of securities. The results obtained from this study offer evidence of the existence of such relationship, suggesting the validity of the Technical Analysis as an instrument to predict security prices in the Brazilian stock market within that period.

Este trabalho apresenta um método de predição não linear de séries temporais econômicas. O método baseia-se na análise técnica e fundamentalista de cotação de ações, filtragem wavelet, seleção de padrões e redes neurais artificiais. No modelo técnico emprega-se a transformada wavelet para filtrar a série temporal econômica de comportamentos aleatórios ou não econômicos. Após a filtragem dos dados o algoritmo de projeções sucessivas é utilizado para a seleção de padrões de treinamento para a rede neural artificial, com o objetivo de selecionar os padrões de comportamento mais importantes na série. No modelo fundamentalista utiliza-se variáveis econômicas que podem estar correlacionadas com a série, com o objetivo de aprimorar a predição da série na rede neural artificial. Para avaliação do método são utilizados dados de séries temporais econômicas referentes à cotação de preços de ações negociadas na bolsa de valores de São Paulo, onde os resultados da predição do comportamento futuro são comparados com modelos matemáticos clássicos e com o modelo convencional, que se baseia somente na análise técnica. Apresenta-se uma comparação dos resultados entre modelos técnicos, modelos matemáticos e o método proposto. O modelo matemático utilizado (ARIMA) apresentou seu melhor desempenho em séries com pouca variância, porém com desempenho inferior quando comparado com o modelo técnico e com o método proposto. A avaliação do erro de predição em termos de RMSEP evidenciou que o método proposto apresenta os melhores resultados em relação aos demais métodos. / This work presents a method for predicting nonlinear economic time series. The method is based on fundamental and technical analysis of script quotation, a multiscale wavelet filtering, pattern selection and artificial neural networks. In the technical model is used the wavelet transform in order to filter the economic time series from random or not economic behaviors. After the data filtering, the successive projections algorithm was used for the training pattern selection to the artificial neural network. In the fundamentalist model is used financial and macroeconomics variables that is correlated with the time serie in order to improve the network forecasting. For the evaluation of the proposed method are used temporal series data related to scrips prices quotation of São Paulo stock market. It presents a comparison of the results between technical model, mathematical model and proposed method. The mathematical model (ARIMA) presented better results in series with few variance, however have low performance when compared with the technical model and with the proposed method. The prediction error evaluation shows that the proposed method has better results than the other methods.

This thesis presents Genetic Programming methodologies to find successful and understandable technical trading rules for financial markets. The methods when applied to the S&P500 consistently beat the buy-and-hold strategy over a 12-year period, even when considering transaction costs. Some of the methods described discover rules that beat the S&P500 with 99% significance. The work describes the use of a complexity-penalizing factor to avoid overfitting and improve comprehensibility of the rules produced by GPs. The effect of this factor on the returns for this domain area is studied and the results indicated that it increased the predictive ability of the rules. A restricted set of operators and domain knowledge were used to improve comprehensibility. In particular, arithmetic operators were eliminated and a number of technical indicators in addition to the widely used moving averages, such as trend lines and local maxima and minima were added. A new evaluation function that tests for consistency of returns in addition to total returns is introduced. Different cooperative coevolutionary genetic programming strategies for improving returns are studied and the results analyzed. We find that paired collaborator coevolution has the best results.