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.

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This article examines the existence of lead-lag effects between the U.S. stock market (NYSE) and the Brazilian stock market (Bovespa), i.e., whether upward and downward price movements in the NYSE are followed, on average, by similar movements in Bovespa, which would enable predicting stock prices in the Brazilian market, thus providing arbitrage opportunities. The existence of this effect would indicate a relative segmentation between these two markets, which would violate the efficient market hypothesis, whereby stock prices are unpredictable. Cointegration between the two markets was identified as well as the existence of bidirectional causality (Granger test). The results obtained from VECM, TSLS and GARCH regressions showed that the two markets are segmented and that returns of the Bovespa Index (Ibovespa) are to a large extent explained by the stock price movements in the Dow Jones Index some minutes beforehand. However, the results also show that the practice of arbitrage based on the lead-lag effects is not economically feasible due to transaction costs.

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