22 de noviembre de 2021
Resumen:
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.
Cita:
A. Rodríguez (2021), Leveraging unstructured data sources in asset pricing. Madrid (España).
