Global ETD Search

71	Automatický obchodní systém založený na breakout strategii a veřejných fundamentálních datech / Automatic Trading System Based on Breakout Strategy and Public Fundamental Data Mičulka, Václav January 2014 (has links) This thesis focuses on design, implementation and optimalization of automated trading system based on breakout strategy and public fundamental data wich trades on FOREX. It descripes theoretical backgroud of financial markets and especially focuces on FOREX. This automated trade system is implemented in object oriented programing paradigm for MetaTrader 5 platform. Last part of thesis is aimed at testing implemented system on historical data in order to evaluate the correctness of system and optimalizations.
72	Návrh automatického obchodního systému s využitím fraktální geometrie / Design of Automatic Trading Systém Based on Fractal Geometry Malý, Petr January 2015 (has links) This thesis deals with an analysis and prediction of foreign exchange markets. The thesis is based on the fractal market hypothesis and it uses tools based on fractal geometry for prediction of markets. The thesis also describes ways of using advanced methods of artificial intelligence for analyzing markets. The outcome is designed and implemented automatic trading system. The thesis also deals with testing of designed system on historical data and on the latest data as well.
73	Optimalizace investičních strategií pomocí genetických algoritmů / Optimization of Investment Strategy Using Genetic Algorithms Novák, Tomáš January 2015 (has links) This thesis is focused on the design and optimization of automated trading system, which will be traded in FOREX. The aim is to create a business strategy that is relatively safe, stable and profitable. Optimization and testing on historical data are a prerequisite for the deployment into real trading.
74	Investiční modely v prostředí finančních trhů / The investment models in an environment of financial markets Barva, David January 2015 (has links) This master thesis evaluates about investing in the currency market, commonly known as Forex. The master thesis is primarily deal with proposal of automated trading system for trading in major currency pairs using breakout strategies. These strategies creation is based on market analysis, volatility, correlation and analysis revealing patterns of time during the trading day. In practical part is formed diversified investment portfolio composed of five investment profitable strategies, which were used during four-month testing period on unknown market data.
75	Investiční modely v prostředí finančních trhů / The Investment Models in an Environment of Financial Markets Bezděk, Petr January 2016 (has links) The content of my master´s thesis is the creation of automatic trading system which will be applied on real trading account mainly on financial markets of currency pairs. The thesis is divided to several parts where the theoretical part will introduce the problem of trading on financial markets. Following part analyses needs of small trader on the financial markets, selecting suitable instruments which will be used in automatic trading system. The part of the own solution design will create the mentioned automatic trading system which will be applied on broker´s demo account where the system will be tested mainly on historical data. Based on test results, system will be optimized and in case of usable results of testing also system will be applied on real trading account in trading company.
76	Návrh a optimalizace automatického obchodního systému / Design and Optimalization of Automatic Trading System Boček, František January 2016 (has links) The goal of this work is to describe approaches to financial market analysis and implement chosen approaches in automatic trading system in the MetaQuote Language environment for Metatrader platform. Another objective is to optimise the designed trading system and test additional rules to achieve maximum profit during minimalization risks.
77	Využití SVM v prostředí finančních trhů / The Use of SVM in Environment of Financial Markets Štechr, Vladislav January 2016 (has links) This thesis deals with use of regression or classification based on support vector machines from machine learning field. SVMs predict values that are used for decisions of automatic trading system. Regression and classification are evaluated for their usability for decision making. Strategy is being then optimized, tested and evaluated on foreign exchange market Forex historic data set. Results are promising. Strategy could be used in combination with other strategy that would confirm decisions for entering and exiting trades.
78	Návrh automatického obchodního systému na devizových trzích s využitím fraktální geometrie / Automatic Trading System on the Foreign Exchange Market Based on a Fractal Geometry Babič, Vojtěch January 2016 (has links) The main focus of the thesis are approaches to technical analysis, trading systems and it summarizes interesting findings, according to which a FOREX automated trading system was designed and implemented. Optimization and testing were a prerequisite for a real-world deployment, so the automated trading system was tested on historical data and some of its input parameters were optimized for maximum stability and profit.
79	Sequence-to-sequence learning of financial time series in algorithmic trading / Sekvens-till-sekvens-inlärning av finansiella tidsserier inom algoritmiskhandel Arvidsson, Philip, Ånhed, Tobias January 2017 (has links) Predicting the behavior of financial markets is largely an unsolved problem. The problem hasbeen approached with many different methods ranging from binary logic, statisticalcalculations and genetic algorithms. In this thesis, the problem is approached with a machinelearning method, namely the Long Short-Term Memory (LSTM) variant of Recurrent NeuralNetworks (RNNs). Recurrent neural networks are artificial neural networks (ANNs)—amachine learning algorithm mimicking the neural processing of the mammalian nervoussystem—specifically designed for time series sequences. The thesis investigates the capabilityof the LSTM in modeling financial market behavior as well as compare it to the traditionalRNN, evaluating their performances using various measures. / Prediktion av den finansiella marknadens beteende är i stort ett olöst problem. Problemet hartagits an på flera sätt med olika metoder så som binär logik, statistiska uträkningar ochgenetiska algoritmer. I den här uppsatsen kommer problemet undersökas medmaskininlärning, mer specifikt Long Short-Term Memory (LSTM), en variant av rekurrentaneurala nätverk (RNN). Rekurrenta neurala nätverk är en typ av artificiellt neuralt nätverk(ANN), en maskininlärningsalgoritm som ska efterlikna de neurala processerna hos däggdjursnervsystem, specifikt utformat för tidsserier. I uppsatsen undersöks kapaciteten hos ett LSTMatt modellera finansmarknadens beteenden och jämförs den mot ett traditionellt RNN, merspecifikt mäts deras effektivitet på olika vis. deep learning machine learning quantitative finance algorithmic trading blackbox trading lstm rnn time series forecasting prediction tensorflow keras forex neural network econometrics finans algoritmisk handel tidsserier prediktion maskininlärning forex neurala nätverk tensorflow keras kvantitativ finans lstm rnn ekonometri Information Systems
80	Možnosti předvídání vývoje měnového kurzu v mezinárodním podnikání / The possibilities of currency rate prediction in international business Antoš, Josef January 2012 (has links) The diploma thesis deals with currency market analysis. There are three main types of analysis: fundamental, technical and psychological analysis. Each of these methods contains explanation of logic, on which the method is based, its advantages, disadvantages and specific examples of this analysis. Neural networks are furher explained in technical analysis. The practical part of the diploma thesis builds on knowledge of technical analysis and tests functionality of the neural networks in the environment of currency markets. The model is calibrated first and then it is used to predict the development of major currency pairs. The prediction is carried out on a monthly chart for December 2013.

Search results