The aim of the thesis was to optimize selected trading strategy in the currency market FOREX. For the optimization was chosen strategy Donchian 5 and 20 and was applied on currency pair EUR/USD. At first was performed backtesting, exit optimization, time optimization and found the importance of position sizing. Then the system was tested in paper trading at broker Admiral Markets, daytrading five minutes chart. Business strategy was optimized and is achieving positive results.

This thesis is about basics of forex the currency market. The main objective of the thesis is to create a forex business strategy, which should be functional, complex and profitable in long term. Testing of this strategy based on historical data and using a real investment account will follow. Thesis is divided into three main chapters. Starting with theoretical part, where we define basic terms, which will be used later, mainly in analytical chapter. Another important part of this chapter will be about three basic approaches how to analyze market, called technical, funamental and relational analysis. The second major chapter is analytical part, in which we are going to build trading strategy Strategie Tomáše Havlíka. This specific trading strategy will compared to the most comonly used trading strategies, tested using historical data and on live account. There will be couple of hand picked trades, which will be analyzed as another part of this chapter. Chapter evaluation of results is focusd not only on evaluating each currency pair and it s various timeframes, but other statistics too, which where acquired during the testing period. Average 50% year over year rentability reached on hourly timeframe and 30% rentability reached on four hour timeframe proves the overall profitability and usefulness of the strategy. Finally, the Conclussion, chapter where we focus on future development of the trading strategy and its integration into a komplex trading approach, which consists of several trading strategies, which are ultimately creating cooperative entity. Information, which will create a backbone of this thesis, will be accquired from respected books aswell as well known internet sources, written mainly by group of authors called FXstreet.cz and British trader Anna Coulling.

This Thesis is dedicated to the variance decompositions from the VAR model un- der the Diebold, Yilmaz (2012) methodology combined with the Baruník, Křehlík (2017) method of frequencies that was used to create traditional and directional spillover tables to be compared under different frequencies. Diverse markets vari- ables were used for the analysis during the period 1/6/1999 to 29/6/2018. The S&P 500 Index represented the financial markets, EUR/USD and YEN/USD rep- resented the Forex markets, and eight types of commodities: Crude Oil, Natural Gas, Gasoline, and Propane represented energy commodities and Corn, Coffee, Wheat, and Soybeans represented food commodities. This analysis contribute to understanding of the dynamic frequency connectedness in case of a differentiated system of markets. The main finding was the strongest short-frequency reaction to shocks in case of all variables, which is opposite behavior than usually observed in banking sector frequency dynamics analyses. JEL Classication: F12, F21, F23, H25, H71, H87 Keywords: connectedness, financial market, forex market, commodity market, systemic risk, spillovers, frequency analysis Author's e-mail: 93414233@fsv.cuni.cz Supervisor's e-mail: barunik@fsv.cuni.cz

This thesis focuses on description of methods of technical analysis, characteristics of foreign exchange markets and it also mentions the efficient market theory. The aim is to use the knowledge of technical analysis to select one simple trading strategy and through its optimalization to discover a functional and efficient trading system. In order to enable followers to continue in optimalization, it is also described the optimalization process in detail with probable obstacles. There are also mentioned other different and possible ways for further testing of this strategy.

The forex market is a complex, evolving, and a non-linear dynamical system, and its forecast is difficult due to high data intensity, noise/outliers, unstructured data and high degree of uncertainty. However, the exchange rate of a currency is often found surprisingly similar to the history or the variation of an alternative currency, which implies that correlation knowledge is valuable for forex market trend analysis. In this research, we propose a computational correlation analysis for the intelligent correlation extraction from all available economic data. The proposed correlation is a synthesis of channel and weighted Pearson's correlation, where the channel correlation traces the trend similarity of time series, and the weighted Pearson's correlation filters noise in correlation extraction. In the forex market analysis, we consider 3 particular aspects of correlation knowledge: (1) historical correlation, correlation to previous market data; (2) cross-currency correlation, correlation to relevant currencies, and (3) macro correlation, correlation to macroeconomic variables. While evaluating the validity of extracted correlation knowledge, we conduct a comparison of Support Vector Regression (SVR) against the correlation aided SVR (cSVR) for forex time series prediction, where correlation in addition to the observed forex time series data is used for the training of SVR. The experiments are carried out on 5 futures contracts (NZD/AUD, NZD/EUD, NZD/GBP, NZD/JPY and NZD/USD) within the period from January 2007 to December 2008. The comparison results show that the proposed correlation is computationally significant for forex market analysis in that the cSVR is performing consistently better than purely SVR on all 5 contracts exchange rate prediction, in terms of error functions MSE, RMSE, NMSE, MAE and MAPE. However, the cSVR prediction is found occasionally differing significantly from the actual price, which suggests that despite the significance of the proposed correlation, how to use correlation knowledge for market trend analysis remains a very challenging difficulty that prevents in practice further understanding of the forex market. In addition, the selection of macroeconomic factors and the determination of time period for analysis are two computationally essential points worth addressing further for future forex market correlation analysis.

The forex market is a complex, evolving, and a non-linear dynamical system, and its forecast is difficult due to high data intensity, noise/outliers, unstructured data and high degree of uncertainty. However, the exchange rate of a currency is often found surprisingly similar to the history or the variation of an alternative currency, which implies that correlation knowledge is valuable for forex market trend analysis. In this research, we propose a computational correlation analysis for the intelligent correlation extraction from all available economic data. The proposed correlation is a synthesis of channel and weighted Pearson's correlation, where the channel correlation traces the trend similarity of time series, and the weighted Pearson's correlation filters noise in correlation extraction. In the forex market analysis, we consider 3 particular aspects of correlation knowledge: (1) historical correlation, correlation to previous market data; (2) cross-currency correlation, correlation to relevant currencies, and (3) macro correlation, correlation to macroeconomic variables. While evaluating the validity of extracted correlation knowledge, we conduct a comparison of Support Vector Regression (SVR) against the correlation aided SVR (cSVR) for forex time series prediction, where correlation in addition to the observed forex time series data is used for the training of SVR. The experiments are carried out on 5 futures contracts (NZD/AUD, NZD/EUD, NZD/GBP, NZD/JPY and NZD/USD) within the period from January 2007 to December 2008. The comparison results show that the proposed correlation is computationally significant for forex market analysis in that the cSVR is performing consistently better than purely SVR on all 5 contracts exchange rate prediction, in terms of error functions MSE, RMSE, NMSE, MAE and MAPE. However, the cSVR prediction is found occasionally differing significantly from the actual price, which suggests that despite the significance of the proposed correlation, how to use correlation knowledge for market trend analysis remains a very challenging difficulty that prevents in practice further understanding of the forex market. In addition, the selection of macroeconomic factors and the determination of time period for analysis are two computationally essential points worth addressing further for future forex market correlation analysis.

FOREX technical analysis indicators, their characteristics and capabilities are researched in this final master thesis. The main goal of this thesis is to determine if technical analysis indicators can recognise patterns in price movements and if they can predict future price movement. The first part of the thesis presents with FOREX theoretical aspects, its characteristics and participants. In the second part of the thesis FOREX analysis tools are overviewed, focusing on technical analysis. Most popular technical analysis indicators are analyzed. The third part of the thesis provides with the essentials of FOREX trading strategy creation using technical analysis. In the fourth part the FOREX trading strategy using technical analysis is created and tested. The results of the trading strategy are presented and analyzed. Last part of the thesis contains the summary of the thesis, conclusions and suggestions. Thesis has 6 parts: introduction, theoretical and practical sections, conclusions and suggestions, references. Structure: introduction, theoretical and practical sections, conclusions and suggestions, references. Thesis consist of: 66 p. text without appendixes, 23 pictures, 5 tables, 62 bibliographical entries. Appendixes included. / Šiame baigiamajame magistro darbe nagrinėjami FOREX rinkos analizei naudojami techniniai indikatoriai, jų savybės bei galimybės. Pagrindinis baigiamojo darbo tikslas yra nustatyti, ar techninės analizės indikatoriai gali nustatyti vaiutų kainų kitimo pasikartojančius modelius ir ar jie gali numatyti kainų judėjimą ateityje. Pirmojoje baigiamojo darbo dalyje pristatomi teoriniai FOREX rinkos aspektai, jos dalyviai bei charakteristika. Antrojoje baigiamojo darbo dalyje apžvelgiami FOREX analizės įrankiai, išskiriant techninę analizę. Aprašomi populiariausi techninės analizės indikatoriai. Trečiojoje baigiamojo darbo dalyje nagrinėjami pagrindiniai prekybos FOREX rinkoje strategijos kūrimo naudojant techninę analizę elementai. Ketvirtojoje baigiamojo darbo dalyje kuriama ir testuojama prekybos FOREX rinkoje strategija naudojant techninę analizę. Pateikiami prekybos strategijos rezultatai bei jų analizė. Paskutinėje baigiamojo darbo dalyje, remiantis gautais rezultatais, pateikiamos išvados ir pasiūlymai. Darbą sudaro 6 dalys: įvadas, teorinė, praktinė dalys, išvados ir siūlymai, literatūros sąrašas. Darbo apimtis – 66 p. teksto be priedų, 23 iliustr., 5 lent., 62 bibliografiniai šaltiniai. Atskirai pridedami darbo priedai.

Magistro darbe yra analizuojama: techninės analizės praktinis pritaikymas Forex rinkoje, rizikos įvertinimas ir portfelio sudarymas. Pagrindinis darbo tikslas ištirti investicijas Forex rinkoje ir jas pagrįsti naudojant investicijų ekonominę analizę. Darbe išnagrinėti pagrindiniai indikatoriai: slankiųjų vidurkių divergencija konvergencija, Bolingerio ribos, santykinis stiprumas, stochastikas. Šiais indikarotiais nustatyti pagrindiniai signalai ir apskaičiuotas pelnas punktais. Taip pat apskaičiuota kiekvienos valiutos rizika, su kuria susiduria kiekvienas investuotojas. Norint gauti maksimalų pelną buvo sudarytas Markowitz portfelis. / This master's work is analyzing: practical application of technical analysis in the Forex market, risk assessment and creating portfolio. The main goal of the work is to explore the investments in Forex market and to substantiate them using investment economic analysis. The main indicators are analyzed in the work: Moving Average Convergence/Divergence, Bollinger bands, Relative Strength Index, Stochastic oscillator. These indicators identify the key signals and the estimated gain points. Also was calculated the risks of each currency faced by each investor. In order to get the maximum profit was made Markowitz portfolio.

Magistro baigiamajame darbe išanalizuota ir įvertinta tarptautinė valiutų rinka, jos struktūra bei analizės ir prognozės būdai. Taip pat analizuojami neuronini tinklai bei įvairios jų struktūros: daugiasluoksnis perseptronas, radialinių bazinių funkcijų neuroniniai tinklai, GRNN bei rekurentiniai neuroniniai tinklai. Tyrimu siekiama nustatyti ar valiutų kursų prognozavimo tikslumas, taikant neuroninius tinklus, priklauso nuo investavimo rizikos lygio. Darbas susideda iš trijų skyrių. Pirmame skyriuje nagrinėjama tarptautinės valiutų rinkos teorija, didesnį dėmesį atkreipiant į pačia FOREX koncepciją, rinkos dalyvius bei jų elgesį ir finansinius instrumentus, naudojamus šioje rinkoje. Tiriami pagrindiniai valiutų kursų prognozės bei analizės būdai, skirstant juos fundamentalią ir techninę analizę. Analizė atliekama, tiriant Lietuvos ir užsienio mokslininkų darbus valiutų rinkos prognozavimo srityje. Antrame skyriuje analizuojami neuroniniai tinklai. Aprašoma neuroninių tinklų koncepcija bei taikymo sritys. Naudojant literatūros analizės metodą, tiriami Lietuvos ir užsienio autorių moksliniai darbai, kuriuose aprašomi neuroninių tinklų tyrimai valiutų rinkos prognozavimo srityje. Pateikiama aktualiausių straipsnių meta analizė. Trečiame skyriuje atliekamas tyrimas su pasirinktų tyrimų duomenimis. Aprašomi šių pasirinkimo motyvai. Skyriaus galia pateikti statistiniai analizės rezultatai: MAE (angl. Mean absoliute error), MAPE (angl. Mean absolute percentage error) krypties... [toliau žr. visą tekstą] / The master thesis analyses the application of the neural networks for foreign exchange market forecast. Multilayer perceptron, radial basis functionneural networks, GRNN and recurrent neural networks are analyzed in order to find the correlation level between the forecast accuracy and the level of the investment risk. The work consists of three main parts. The first part analyses the conception, the main participants, trading characteristics and trading instruments of the FOREX market as well as the trading strategies and the methods of forecasting currency market. The second part is appointed to analyze the neural networks. The analyzes the conception, the structure and the application of the neural networks is made. The Meta-analyses of the main scientific articles are provided in every sub-part. In the third part the forecasting data analysis is performed to evaluate the correlation rate between the forecast accuracy and the level of the investment risk. Mean absolute error, Mean absolute percentage error, sign function andStandard deviation are used as indicators.

Magíster en Gestión de Operaciones / Ingeniero Civil Industrial / El análisis técnico es utilizado extensamente por la mayoría de los inversionistas de mercados financieros, siendo el mercado de divisas el con mayor desarrollo y volumen de transacciones a nivel mundial. Pese a su utilización el 90% de los inversionistas pierde dinero y sólo el 10% restante es exitoso invirtiendo en los mercados financieros. En la actualidad, el uso de sistemas de transacción automatizados basados en indicadores de análisis técnico es una herramienta utilizada cada día más por los inversionistas debido al fácil acceso de software de transacción que permite automatizar las operaciones de los clientes. Con el presente trabajo, se busca encontrar estrategias de compra rentables para la divisa más líquida, el euro-dólar, utilizando reglas de decisión complementadas con estrategias de money management. Por lo anterior, el objetivo principal del proyecto es encontrar reglas de asociación rentables de compra en un horizonte de 12 años utilizando indicadores técnicos que cuantifican tendencia, volatilidad y momentum. El sistema constituido por las reglas de decisión encontradas serán programadas en MT4 para realizar el backtesting correspondiente del sistema y al mismo tiempo tener un prototipo funcional que permita generar operaciones automáticas de compra en el mercado de divisas. La metodología se enfoca en encontrar las relaciones de orden existentes entre los valores de los indicadores técnicos y el movimiento en el precio del euro-dólar en base a datos transaccionales pasados. Se realiza un análisis univariado utilizando indicadores de cada categoría por separado y posteriormente se conjugan todos los indicadores en un análisis multivariado. Para evaluar cada regla de asociación se utilizan los indicadores de soporte, confianza y se introduce la contraconfianza como indicador, que busca registrar los escenarios negativos asociados a una regla de decisión determinada. El resultado obtenido es un sistema de transacción automatizado de compras constituido por 98 reglas de asociación que luego de incorporar estrategias de money management y algoritmos genéticos para optimizar los niveles de take profit y stop loss, en un horizonte de 12 años tuvo un desempeño superior en un 24% a la estrategia buy and hold y que superó en el peor de los casos en un 96% al resultado obtenido por sistemas automatizados de trading utilizando las señales obtenidas por un sólo indicador técnico. Como conclusión del trabajo realizado se obtiene que las relaciones entre los valores de indicadores técnicos y el movimiento del precio de una divisa pueden ser correctamente evaluadas con el sistema construido, ya que las decisiones de compra basadas en su utilización permitieron obtener resultados económicos positivos y superar a los resultados obtenidos por otros sistemas basados en otras reglas. Finalmente, dentro de las extensiones a este trabajo, se encuentran evaluar reglas de asociación asociadas a compra y venta y extender el análisis a otras divisas o incluso a otros activos pertenecientes a mercados financieros diferentes.