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This paper deals with the problem of how to take full use of prices information to model financial markets.A range decomposition technique is proposed to decompose the returns into two components.It is proved theoretically that these two components are bi-directional Granger causality,which makes it convenient to establish a vector autoregressive model(VAR).Both simulations and empirical studies are performed,and the results are consistent with the theoretical ones.The range decomposition approach presented in this paper is more efficient in information employment and suggests a new framework to model financial markets.
This paper deals with the problem of how to take full use of prices information to model financial markets. A range decomposition technique is proposed to decompose the returns into two components. It is proven theoretically that these two components are bi-directional Granger causality, which makes it convenient to establish a vector autoregressive model (VAR) .Both simulations and empirical studies are performed, and the results are consistent with the theoretical ones. The range decomposition approach presented in this paper is more efficient in information employment and suggests a new framework to model financial markets.