Forecasting stock price crashes in the biotechnology sector – Evidence from the U.S. in 2002-2016

Abstract

This study examines determinants for stock price crashes in the U.S. biotechnology sector. Further, the study investigates three crash metrics’ consistency in firm-specific crash classification.

The study is quantitative in nature and applies both logistic and multiple regression to explore the ability of a set of chosen explanatory variables to predict crashes. Two existing crash risk metrics are used, and one additional metric is created as a part of the study. The sample consist of 1303 observations from the U.S. biotechnology/pharmaceutical industry in 2002-2016.

The results of this study suggest that volatility of a stock return is positively associated with future crash risk, and return on assets as well as firm size in terms of total assets and market capitalization are negatively associated with future stock price crash risk. In relation to the consistency of crash classifications, the results show that 20-30% of the classifications are inconsistent within the results of the three crash metrics used in this study.