, Rogers, Rogers and Zhou and Horst et al. The importance of opening, highest, lowest and closing (OHLC in short) prices information is well-known and has been used by a number of authors, including Rogers and Satchell, Rogers et al. All of the models of stocks market have focused on the behavior of price returns and losing the possibility of embodying information from opening price, highest price and lowest price. In all of those studies, stock or currency is represented by univariate time series its price. MST has also been used to analyze the properties of FX markets based on correlation in different methods by many authors such as McDonald et al. Some examples of this method were used in the context of financial markets by Bonanno et al. Since the work of Mantegna, MST has become an indispensable tool in econophysics to filter important information contained in the complex structure of a correlation matrix among stocks in a given portfolio. See also Mantegna and Stanley for a more pedagogical approach.
The stocks network visually constructs the relationship between stocks, which is extracted by the MST based on the correlations between stocks’ price returns. In econophysics, stocks network was introduced by Mantegna for investigating the interaction between stocks using the minimal spanning tree (MST) method. However, the extraction of information from the correlation matrix is not as straightforward as it seems. In this regard, the correlation matrix has long been used to quantify the interactions, and the information generated can be very helpful if enough data has been provided beforehand.
Thus, to capture the pricing mechanism of stocks market, it is important to study and figure out the interactions. The system of stocks market is extremely complex and it is continuously evolving through various heterogeneous interactions between them.
0 kommentar(er)
