The thesis deals with design, implementation and optimization of a model based on artificial intelligence and neural networks, which is able to predict future time series prices on a stock market. Main goal is to create an object oriented application for successful future trend prediction of financial derivatives with the use of cooperating methods such as Hurst exponent evaluation and automated market simulation.

This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.

This study aims to see if it is possible to generate abnormal returns in the Swedishstock market through the use of three different trading strategies based on technicalindicators. As the indicators are based on historical price data only, the study assumesweak market efficiency according to the efficient market hypothesis. The study isconducted using daily prices for OMX Stockholm PI and STOXX 600 Europe from theperiod between 1 January 2010 and 31 December 2019. Trading positions has beentaken in the OMX Stockholm PI index while STOXX 600 Europe has been used torepresent the market portfolio. Abnormal returns has been defined as the Jensen’s αin a Fama French three factor model with Carhart ­extension. This period has beencharacterised by increasing prices (a bull market) which may have had an impact onthe results. Furthermore, a higher frequency of rebalancing for the Fama ­French andCarhart model could also increase the quality of the results. The results indicate thatall three strategies has generated abnormal returns during the period. / Denna studie syftar till att se om det är möjligt att generera överavkastning på densvenska aktiemarknaden genom att använda tre olika handelsstrategier baserade påtekniska indikatorer. Eftersom indikatorerna endast baseras på historiska prisdataantar studien svag marknadseffektivitet enligt den effektiva marknadshypotesen.Studien genomförs med hjälp av dagliga priser för OMX Stockholm PI och STOXX 600Europe från perioden 1 januari 2010 till 31 december 2019. Positionerna i studien hartagits i OMX Stockholm PI medan STOXX 600 Europe har använts för att representeramarknadsportföljen . Överavkastning har definierats som Jensens α i en Fama French trefaktormodell med Carhart-­utvidgning. Perioden som används i studien har präglatsav stigande priser (en bull market) som kan ha påverkat resultatet. Dessutom skulleen högre frekvens av ombalansering av Fama ­French och Carhart-­modellen ocksåkunna öka kvaliteten på resultaten. Resultaten visar att alla tre strategier har genereratonormal avkastning under perioden.

Master´s thesis goal that the author hopes to achieve is a design of an application aiding stock technical analysis based on identified needs. Based on analysis regarding modules for technical analysis of current trading platforms, I found out there is a certain space for improvement. Implemented trading rules and technical indicators of the application itself are further examined in terms of prognostic success rate on historical data. Selected chapters of technical analysis are fundamental base for this master´s thesis.