14 resultados para variance ratio

em Repositório digital da Fundação Getúlio Vargas - FGV


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In this study, we verify the existence of predictability in the Brazilian equity market. Unlike other studies in the same sense, which evaluate original series for each stock, we evaluate synthetic series created on the basis of linear models of stocks. Following Burgess (1999), we use the “stepwise regression” model for the formation of models of each stock. We then use the variance ratio profile together with a Monte Carlo simulation for the selection of models with potential predictability. Unlike Burgess (1999), we carry out White’s Reality Check (2000) in order to verify the existence of positive returns for the period outside the sample. We use the strategies proposed by Sullivan, Timmermann & White (1999) and Hsu & Kuan (2005) amounting to 26,410 simulated strategies. Finally, using the bootstrap methodology, with 1,000 simulations, we find strong evidence of predictability in the models, including transaction costs.

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A pesquisa teve como objetivo testar se preços no mercado futuro brasileiro seguem um passeio aleatório - uma das versões da chamada Hipótese do Mercado Eficiente. Foram estudados os preços dos contratos futuros de Ibovespa e de dólar comercial, de 30 de junho de 1994 a 31 de dezembro de 1998. Aplicação de testes paramétricos e não-paramétricos envolvendo a Relação de Variâncias (Variance Ratio) de Lo-MacKinlay levam à conclusão de que a hipótese testada não pode ser rejeitada, apontando, portanto, para eficiência em tais mercados.

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This paper investigates the impact of price limits on the Brazil- ian future markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. Our main finding is that price limits drive back prices as they approach the lower limit. There is a strong cool-off effect of the lower limit on the conditional mean, whereas the upper limit seems to entail a weak magnet effect on the conditional variance. We then build a trading strategy that accounts for the cool-off effect so as to demonstrate that the latter has not only statistical, but also economic signifi- cance. The resulting Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider.

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This paper presents an overview of the Brazilian macroeconomy by analyzing the evolution of some specific time series. The presentation is made through a sequence of graphs. Several remarkable historical points and open questions come up in the data. These include, among others, the drop in output growth as of 1980, the clear shift from investments to government current expenditures which started in the beginning of the 80s, the notable way how money, prices and exchange rate correlate in an environment of permanently high inflation, the historical coexistence of high rates of growth and high rates of inflation, as well as the drastic increase of the velocity of circulation of money between the 70s and the mid-90s. It is also shown that, although net external liabilities have increased substantially in current dollars after the Real Plan, its ratio with respect to exports in 2004 is practically the same as the one existing in 1986; and that residents in Brazil, in average, owed two more months of their final income (GNP) to abroad between 1995-2004 than they did between 1990 and 1994. Variance decompositions show that money has been important to explain prices, but not output (GDP).

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This paper investigates the impact of price limits on the Brazilian futures markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the S˜ao Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. The results indicate that the conditional mean features a floor cool-off effect, whereas the conditional variance significantly increases as the price approaches the upper limit. We then build a trading strategy that accounts for the cool-off effect in the conditional mean so as to demonstrate that the latter has not only statistical, but also economic significance. The in-sample Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider, whereas out-of-sample results evince similar performances.

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Este trabalho examinou as características de carteiras compostas por ações e otimizadas segundo o critério de média-variância e formadas através de estimativas robustas de risco e retorno. A motivação para isto é a distribuição típica de ativos financeiros (que apresenta outliers e mais curtose que a distribuição normal). Para comparação entre as carteiras, foram consideradas suas propriedades: estabilidade, variabilidade e os índices de Sharpe obtidos pelas mesmas. O resultado geral mostra que estas carteiras obtidas através de estimativas robustas de risco e retorno apresentam melhoras em sua estabilidade e variabilidade, no entanto, esta melhora é insuficiente para diferenciar os índices de Sharpe alcançados pelas mesmas das carteiras obtidas através de método de máxima verossimilhança para estimativas de risco e retorno.

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This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.

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Esta dissertação tem três objetivos. O primeiro é encontrar o melhor método para se calcular a taxa ótima de “hedge” no mercado brasileiro do boi gordo. Para isso, foram testados cinco modelos: BEKK, DCC de Tse e Tsui (2002), DCC de Engle e Sheppard (2001), BEKK com dummy de safra e BEKK com dummy de entressafra. O segundo é calcular o diferencial de razões de “hedge” entre a safra e entressafra, pois a taxa de “hedge” na entressafra deve ser maior devido a uma maior incerteza sobre um possível choque de oferta, o que afetaria negativamente os custos dos frigoríficos. O terceiro e último objetivo é desvendar o porquê da literatura brasileira de taxa ótima de “hedge” estar encontrando estimativas muito pequenas das taxas quando comparadas às realizadas no mercado. Conclui-se que os modelos DCC’s são os que, no geral, obtém um desempenho melhor pelo critério de redução de variância e aumento do índice de Sharpe e que a taxa de “hedge” na entressafra não deve ser maior que na safra. Nota-se também que a quebra da expectativa intertemporal com a mudança de contratos faz com que a variância da série dos retornos futuros aumente muito, diminuindo assim a taxa de “hedge”.

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A Reforma do Judiciário de 2004 é parte de um longo processo de tentativas políticas de implementação de mudanças que não surgiriam espontaneamente na cultura jurídica. A súmula vinculante é exemplar desse histórico, pois se trata de instrumento voltado para corrigir problemas persistentes que decorrem da ausência de uma cultura jurídica de precedentes no Brasil. Entretanto, o próprio funcionamento do instituto depende da adequada aplicação da lógica de precedentes, pois a clareza dos enunciados vinculantes aprovados decorre da clareza da ratio decidendi de seus respectivos precedentes. Além do estudo dos debates legislativos que criaram o instituto da súmula vinculante, bem como dos procedimentos de aprovação das súmulas vinculantes penais editadas até o final de 2010, pesquisou-se como o Supremo Tribunal Federal administrou o manejo deste instituto conflitante com a maneira tradicional de fundamentação judicial e de referência não-fática, mas conceitual, entre decisões passadas.

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This paper presents an overview of the Brazilian macroeconomy by analyzing the evolution of some specific time series. The presentation is made through a sequence of graphs. Several remarkable historical points and open questions come up in the data. These include, among others, the drop in output growth as of 1980, the clear shift from investments to government current expenditures which started in the beginning of the 80s, the notable way how money, prices and exchange rate correlate in an environment of permanently high inHation, the historical coexistence of high rates of growth and high rates of inHation, as well as the drastic increase of the velocity of circulation of money between the 70s and the mid-90s. It is also shown that, although net external liabilities have increased substantially in current dollars after the Real Plan, its ratio with respect to exports in 2004 is practically the same as the one existing in 1986; and that residents in Brazil, in average, owed two more months of their final income (GNP) to abroad between 1995-2004 than they did between 1990 and 1994. Variance decompositions show that money has been important to explain prices, but not output (GDP).

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This paper develops a general method for constructing similar tests based on the conditional distribution of nonpivotal statistics in a simultaneous equations model with normal errors and known reducedform covariance matrix. The test based on the likelihood ratio statistic is particularly simple and has good power properties. When identification is strong, the power curve of this conditional likelihood ratio test is essentially equal to the power envelope for similar tests. Monte Carlo simulations also suggest that this test dominates the Anderson- Rubin test and the score test. Dropping the restrictive assumption of disturbances normally distributed with known covariance matrix, approximate conditional tests are found that behave well in small samples even when identification is weak.

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This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.

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This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.

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Using the theoretical framework of Lettau and Ludvigson (2001), we perform an empirical investigation on how widespread is the predictability of cay {a modi ed consumption-wealth ratio { once we consider a set of important countries from a global perspective. We chose to work with the set of G7 countries, which represent more than 64% of net global wealth and 46% of global GDP at market exchange rates. We evaluate the forecasting performance of cay using a panel-data approach, since applying cointegration and other time-series techniques is now standard practice in the panel-data literature. Hence, we generalize Lettau and Ludvigson's tests for a panel of important countries. We employ macroeconomic and nancial quarterly data for the group of G7 countries, forming an unbalanced panel. For most countries, data is available from the early 1990s until 2014Q1, but for the U.S. economy it is available from 1981Q1 through 2014Q1. Results of an exhaustive empirical investigation are overwhelmingly in favor of the predictive power of cay in forecasting future stock returns and excess returns.