This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is l...This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is linear or not. The novelty of this work is based on intraday data from both markets. The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities. Moreover, non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality, a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.展开更多
Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariat...Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built： ARFIMA, vector autoregressive （VAR）, and vector error correction （VEC）. Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.展开更多
supported by the National Natural Science Foundation of China under Grant Nos.71125005 70871108 and 70810107020;; Outstanding Talents Funds of Organization Department Beijing Committee of CPC
文摘This paper builds on the literature of the relationship between oil spot and futures prices from the NYNEX market, both in their means and in their conditional volatilities, to investigate whether the association is linear or not. The novelty of this work is based on intraday data from both markets. The empirical findings indicate the presence of nonlinearities both in means and conditional volatilities. Moreover, non-linear causality estimations both in means and in volatilities reveal the presence of bi-directional causality, a fact that provides additional support to the hypothesis that both markets are driven by the same information sets.
文摘Data from the World Federation of Exchanges show that Brazil＇s Sao Paulo stock exchange is one of the largest worldwide in terms of market value. Thus, the objective of this study is to obtain univariate and bivariate forecasting models based on intraday data from the futures and spot markets of the BOVESPA index. The interest is to verify if there exist arbitrage opportunities in Brazilian financial market. To this end, three econometric forecasting models were built： ARFIMA, vector autoregressive （VAR）, and vector error correction （VEC）. Furthermore, it presents the results of a Granger causality test for the aforementioned series. This type of study shows that it is important to identify arbitrage opportunities in financial markets and, in particular, in the application of these models on data of this nature. In terms of the forecasts made with these models, VEC showed better results. The causality test shows that futures BOVESPA index Granger causes spot BOVESPA index. This result may indicate arbitrage opportunities in Brazil.
基金supported by the National Natural Science Foundation of China under Grant Nos.71001096,70933003,and 71071170
文摘supported by the National Natural Science Foundation of China under Grant Nos.71125005 70871108 and 70810107020;; Outstanding Talents Funds of Organization Department Beijing Committee of CPC
