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memoria.pdf (506.57 KB)

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Bachelor thesis

Publication date

2018-01-19

Publication license

cc-by-nc-nd (c) Roberto Rafael Maura Rivero, 2018
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/122608

Portfolio theory: managing big data

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Abstract

[en] Long and extense is the literature of the portfolio theory. The main goal of it is basically deciding which one is the best possible investment given a set of available assets. During the last decades, there has been great improvement in the way of dealing with the problem and some fundamental changes in the hypothesis taken. The main issue that we will discuss here is that, so far, there is a trade off between the accuracy of the model and the computational time complexity. In this work, we will discuss some of those famous models that have appeared during history, its particular application and restrictions nowadays, emphasizing in the computational problems derived when working with big data. After that, we will code some of the models and compare them. Finally, we will propose one new model and will compare it with the previous ones.

Description

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Eulàlia Nualart i Josep Vives i Santa Eulàlia

Subject

Anàlisi de variància, Treballs de fi de grau, Models matemàtics, Dades massives, Optimització matemàtica, Python (Llenguatge de programació)

Subject (English)

Analysis of variance, Bachelor's theses, Mathematical models, Big data, Mathematical optimization, Python (Computer program language)

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Treballs Finals de Grau (TFG) - Matemàtiques

Citation

MAURA RIVERO, Roberto Rafael. Portfolio theory: managing big data. [consulted: 7 of August of 2026]. Available at: https://hdl.handle.net/2445/122608

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