An Alternative Model of Risk in Non-financial Companies Applied to the Brazilian Pulp and Paper Industry

Hsia Hua Sheng (), Cristiane Karcher () and Paulo Hubert ()
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Hsia Hua Sheng: FGV-EAESP
Cristiane Karcher: IME-USP

Brazilian Review of Finance, 2009, vol. 7, issue 3, 347-360

Abstract: Earnings at Risk (EaR) is a financial risk measure that can be applied to non-financial companies, similarly to Cash Flow at Risk (CFaR). It is based on a relation that can be quantified using a multiple linear regression model, where the dependent variable is the change on the company's results and the independent variables are changes in distinct risk factors. The presence of correlation between explanatory factors (multicollinearity) in this kind of model may cause problems when calculating EaR and CFaR. In this paper, we indicate some possible consequences of these problems when calculating EaR, and propose a method to solve it based on Principal Component Analysis technique. To test the model, we choose the Brazilian agriculture-business industry, more specifically the paper and pulp sectors. We will show that, on the absence of significant correlation between variables, the proposed model has equivalent performance to usual multiple linear regression models. We find evidence that when correlation appears, the model here proposed yields more accurate and reliable forecasts.

Keywords: risk management; PCR model; international finance; earning at risk. (search for similar items in EconPapers)
JEL-codes: G32 M16 (search for similar items in EconPapers)
Date: 2009
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