Stochastic methods applied in the pharmaceutical and biotechnology sector

Abstract

This paper evaluates the efficiency of a stochastic approach called Arithmetic Brownian Motion in the pharmaceutical sector. This method allows us to assess companies accurately, deciding whether they are undervalued or overvalued. Through some literature review, I concluded the strengths of using this method when evaluating companies, as it can also incorporate multiple risks when comparing with the Geometric Brownian Motion. This thesis provides a reliable prediction of the pharmaceutical companies, as I evaluate more than one Company and compare my results with some specialists. Also, I consider some robustness tests to check other scenarios in my forecasting. These tests provide evidence about similarities in the capital structure from American pharma/biotech companies, while Europeans differ when comparing the results.

Date of Award	29 Jun 2021
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Leon Bogdan Stacescu (Supervisor)