03361ntm a22005657i 4500 000264307 CZ-PrVSE 20220907191439.0 m d cr n|||||||||| 220907s2022 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Jedličková, Zuzana ISIS:108453 dis Modeling and forecasting stock market returns eng Modeling and forecasting stock market returns / Zuzana Jedličková 2022 ?? stran : digital, PDF soubor Vedoucí práce: Ondřej Šimpach Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2022 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2022 In this thesis, five models are introduced, discussed, and applied – autoregressive integrated moving average (ARIMA), artificial neural network (ANN), convolutional neural network (CNN), long short-term memory (LSTM) and hybrid CNN+ANN+LSTM. For the analysis, data about daily adjusted closing prices of six pharmaceutical stocks from 1st January till 3rd June 2022 were obtained, transformed into logarithmic returns, and split into training, validation, and testing sets. Models were estimated on the training data, evaluated on the validation set and their performance was compared on the test data. To compare models’ predictive power, the forecast accuracy metric Root Mean Square Error (RMSE) was used. The primary aim of this thesis is to study and explain the concept of introduced models, as well as to construct own models and compare their predictive power in order to answer given research questions. The research questions investigated throughout this thesis are as follows: 1) Is it possible to predict stock market returns with a decent forecast accuracy? 2) Do machine learning algorithms provide with more accurate forecasts than classical ARIMA models? Způsob přístupu: Internet data analysis and modeling [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas Time series forecasting ARIMA ANN CNN LSTM Šimpach, Ondřej jo2013796555 ths Bílková, Diana mzk2004248684 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/78643/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/78643 Hlavní práce https://insis.vse.cz/zp/78643/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/78643/posudek/oponent/76113 Oponentura https://insis.vse.cz/zp/78643/priloha/24690 Přiloha k práci https://insis.vse.cz/zp/78643/priloha/24691 Přiloha k práci https://insis.vse.cz/zp/78643/priloha/24702 Přiloha k práci https://insis.vse.cz/zp/78643/podrobnosti dc:identifier NEPOSILAT VSKP vse78643 220826 78643