Paper: A Semiparametric Gaussian Copula Regression Model for Predicting Financial Risks from Earnings Calls

ACL ID P14-1109
Title A Semiparametric Gaussian Copula Regression Model for Predicting Financial Risks from Earnings Calls
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Earnings call summarizes the financial performance of a company, and it is an important indicator of the future financial risks of the company. We quantitatively study how earnings calls are correlated with the financial risks, with a special fo- cus on the financial crisis of 2009. In par- ticular, we perform a text regression task: given the transcript of an earnings call, we predict the volatility of stock prices from the week after the call is made. We pro- pose the use of copula: a powerful statis- tical framework that separately models the uniform marginals and their complex mul- tivariate stochastic dependencies, while not requiring any prior assumptions on the distributions of the covariate and the de- pendent variable. By performing probabil- ity integral transform, our approach m...