8 resultados para Absorption and emission cross-section

em Repositório digital da Fundação Getúlio Vargas - FGV


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We use a factor-augmented vector autoregression (FAVAR) to estimate the impact of monetary policy shocks on the cross-section of stock returns. Our FAVAR combines unobserved factors extracted from a large set of nancial and macroeconomic indicators with the Federal Funds rate. We nd that monetary policy shocks have heterogeneous e ects on the crosssection of stock returns. These e ects are very well explained by the degree of external nance dependence, as well as by other sectoral characteristics.

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Neste trabalho testa-se inicialmente se fundos com gestão ativa apresentam alfa (excesso de retorno) em relação aos índices de referência de fundos passivos. Simulações via bootstrap visam indicar se o excesso de retorno apresentado pode ser atribuído apenas à sorte. Com esta metodologia concluiu-se que a carteira agregada de fundos de investimentos de ação com gestão ativa no Brasil não apresenta excesso de retorno em relação aos principais índices da bolsa brasileira, quando líquidos de taxas e despesas. As simulações de bootstrap sugerem que uma quantidade maior de fundos apresenta retornos ajustados ao benchmark do que o esperado pelo efeito da aleatoriedade nos resultados.

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Essa tese se propõe fazer uma comparação entre duas técnicas alternativas para estudo de impactos marginais de variáveis sócio-econômicas sobre as taxas de crescimento per-capita de grupos de países durante período de 1965 1985: regressão em sistemas de equações com dados em seções transversais, usada por Barro Sala-i-Martin (1995), entre outros, e a regressão em painel com coeficientes individuais. Tentaremos mostrar que os resultados associados certas variáveis são bastante diferentes procuraremos entender algumas causas dessas diferenças. Além disso, estaremos preocupados em avaliar como os resultados são afetados ao alterarmos conjunto de países estudado, em particular quando tomamos grupos de países com uma série de características semelhantes.

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This paper investigates the impact of monopoly power on trade policy. Annual panel-databases of Brazilian industries for the years 1988 through 1994 were used. The regressions reported here are robust to openness indicator, concentration index, control variables and sample size, and suggest that industries with higher monopoly power are more protected than competitive sectors. In the period of study the country experienced a major trade liberalization, but the results in the paper show that the reduction in protection was smaller in sectors with higher monopoly power. We thus have evidence favoring recent growth literature which stresses that interest groups with control over creasing productivity. The results here confirm the first part of this argument and show that organized groups in fact are able to obtain policy advantages that reduce competition.

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In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.