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We empirically analyze how the Brazilian Central Bank (BCB) communication affects the term structure of future interest rates. Using principal components analysis, we construct a measure of the Monetary Policy Committee Minutes content that reflects policy makers optimism about the economic conditions. We call this measure the Optimism Factor (OF). When policy makers are more optimistic, reflected by increments in the OF, markets expectations respond and long-term future interest rates drop. Furthermore, when policy makers are pessimistic, reflected by a decrease in the OF, volatility on future interest rates increases. Our result indicates that policy maker communication has an effective impact on market expectations. Analisamos empiricamente como as atas do Banco Central do Brasil (BCB) afetam a estrutura a termos da taxa de juros. Usando Análise de Componentes Principais, construímos uma medida do conteúdo dessas atas que reflete o otimismo dos gesto-res de política monetária em relação às condições economicas. Nomeamos essa me-dida de Fator de Otimismo (OF). Quando os gestores estão mais otimistas, de forma que o OF aumenta, as taxas de juros de longo prazo caem respondendo às expectati-vas de mercados. Além disso, quando os gestores estão pessimistas, de modo que o OF cai, a volatilidade das taxas de juros futuras aumenta. Nossos resultados suge-rem que a comunicação dos gestores de política monetária tem um impacto efectivo nas expectativas do mercado.

According to theory, the level of short-selling can predict short-run future returns throughout two channels. One is related to the demand-side of the stock lending market: short-sellers are informed. The other is related to the supply-side: short-sellers are restricted. Measuring the importance of each channel is empirically challenging once, in general, supply and demand in the stock lending market are not directly observable. This paper takes advantage of a unique dataset that contains actual shifts in lending supply for stocks on the Brazilian market, and proposes an identification strategy for the effects of both supply and demand on stock prices. We find that both channels are important.

This paper proposes a forecasting model that combines a factor augmented VAR (FAVAR) methodology with the Nelson and Siegel (NS) parametrization of the yield curve to predict the Brazilian term structure of interest rates. Importantly, we extract the principal components for the FAVAR from a large data set containing forward-looking macroeconomic and financial variables. Our forecasting model significantly improves the predicting accuracy of extant models in the literature, particularly at short-term horizons. For instance, the mean absolute forecast errors are 15-40% lower than the random walk benchmark on predictions at the three month horizon. The out-of-sample analysis shows that including forward-looking indicators is the key to improve the predictive ability of the model.

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