Leveraging unstructured data sources in asset pricing

  1. Rodríguez Gallego, Alejandro
Supervised by:
  1. Isabel Figuerola Ferreti Garrigues Director
  2. Sara Lumbreras Sancho Co-director

Defence university: Universidad Pontificia Comillas

Fecha de defensa: 22 November 2021

Committee:
  1. Gabriel de la Fuente Herrero Chair
  2. Cristina Puente Águeda Secretary
  3. Ricardo Correia Committee member
  4. Paloma Bilbao Calabuig Committee member
  5. Pedro Jose Serrano Jimenez Committee member

Type: Thesis

Teseo: 703633 DIALNET

Abstract

This thesis analyzes the impact on various aspects of asset valuation of the recent technological advances and the vast amount of data available today. Specifically, Chapter 2 frames the current state of the discipline in the new context generated by the latest technological disruptions. Next, Chapter 3 conducts a systematic literature review to identify an unexplored gap at the intersection among sustainability, asset valuation, and modern techniques such as Natural Language Processing (NLP). Subsequently, chapter 4 delves empirically into this gap, producing sustainability metrics for US companies with NLP and demonstrating their convenience when included in the Fama-French asset valuation model. Finally, Chapter 5 contributes to the persistent debate on the financial analysts’ predictive capability by comparing oil price forecasts with futures contracts using unstructured data.