Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/122608
Title: Portfolio theory: managing big data
Author: Maura Rivero, Roberto Rafael
Director/Tutor: Nualart, Eulàlia
Vives i Santa Eulàlia, Josep, 1963-
Keywords: Anàlisi de variància
Treballs de fi de grau
Models matemàtics
Dades massives
Optimització matemàtica
Python (Llenguatge de programació)
Analysis of variance
Bachelor's thesis
Mathematical models
Big data
Mathematical optimization
Python (Computer program language)
Issue Date: 19-Jan-2018
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.
Note: Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2018, Director: Eulàlia Nualart i Josep Vives i Santa Eulàlia
URI: http://hdl.handle.net/2445/122608
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

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