diplomsko delo
Grega Kranjec (Author), Tomaž Hovelja (Mentor)

Abstract

Diplomsko delo obravnava primerjavo treh metod za napovedovanje vrednosti delniških indeksov. Dve metodi za napovedovanje sta uporabljali izključno strojno učenje, ena pa je slonela na statistični analizi. Cilj dela je bil ugotoviti, če se vrednosti delniških indeksov da napovedovati in katera od izbranih metod je najboljša. Primerjava se je naredila na podatkih treh različnih indeksov iz treh različnih trgov. Napovedi so se primerjale po različnih merah, največja teža pa je bila dana vrednosti končnega kapitala. Za simulacijo trgovanja sta bila razvita dva različna algoritma. Rezultati so prikazali, da se vrednosti delniških indeksov da napovedovati, vendar ne z vsemi metodami. Izkazalo se je tudi, da na končni kapital lahko vplivamo tudi s samim algoritmom za trgovanje. Vse metode so napovedovale bolje kot strategija kupi in drži, ena od metod pa je napovedovala tudi z dobičkom v primerjavi z inflacijo. Ugotovilo se je, da na primeru napovedovanja vrednosti delniških trgov standardne mere za ocenjevanje kakovosti rezultatov niso vedno primerne.

Keywords

delniški indeksi;napovedovanje vrednosti;časovne vrste;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [G. Kranjec]
UDC: 004.85:336.761(043.2)
COBISS: 170228483 Link will open in a new window
Views: 56
Downloads: 14
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Other data

Secondary language: English
Secondary title: Comparison of methods for stock index forecasting
Secondary abstract: This thesis compares three different methods for predicting the value of stock indices. Two of the methods use machine learning to forecast values, while one uses a combination of statistical analysis and machine learning. The aim of the thesis was to figure out if it is possible to predict future stock index values and to find which of the methods is the best. The comparison was done on data of three different stock indices in three different markets. The forecasted values were compared using multiple different metrics, where the value of final equity was given the biggest weight. Two different algorithms were developed for the purpose of trading simulation. The results showed that it is possible to predict future values of stock indices, but not with all methods. They also showed that the results can be positively influenced by trading algorithms. All methods provided predictions good enough to trade better than the buy and hold strategy. One of the methods also ended with a positive final capital even with subtracted inflation. It was found that the standard metrics for assessing the quality of the results are not always suitable, especially in the case of predicting stock index values.
Secondary keywords: stock index;stock index forecasting;machine learning;comparison;time series;computer science;diploma;Strojno učenje;Delnice;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 65 str.
ID: 20029591