Modeling and forecasting a firm’s financial statements with a VAR – VECM model

This paper reports the development and estimation of a Vector Autoregressive (VAR) econometric model representing the financial statements of a firm. Although the model can be generalized to represent the financial statements of any firm, this work was carried out as a case study, where the chosen company is Petrobras S/A. The methodology comprises correlation analysis, unit root tests, cointegration analysis, VAR modeling, Granger causality tests, in addition to impulse response and variance decomposition methods. Besides the endogenous financial statement variables, an exogenous variable vector was utilized including the Brazilian GDP, domestic and foreign interest rates, the international oil price, the exchange rate, and country risk. The model’s final version is a Vector Error Correction Model (VECM), which takes into account the cointegrating relationships among the endogenous variables. After estimation and validation, the model is used to forecast the firm’s financial statements. Estimates for the exogenous variables and dividend forecasts were also used to estimate the firm’s market value. The results are apparently robust and might contribute to the field of financial planning and forecasting.