Abstract
In this study, a modeling method to analyze multidimensional time series based on complex networks is proposed. The rate of return sequence of the closing price and the trading volume fluctuation sequence of the Shanghai Composite Index, the Shenzhen Component Index, the S & P 500 index, and the Dow Jones Industrial Average are analyzed. The two-dimensional time series is transformed into a complex network. We analyze the spatial distribution characteristics of the network to determine the relationship between volume and price. It is found that the interaction of stock return and volume in China’ stock market is more obvious than that in the American market.
Highlights
Most scholars apply econometric or variance models to analyze time series of financial markets
We present two-dimensional or multidimensional time series analysis methods based on complex networks
These are applied to stock market volume and price analysis by studying the relationship between prices and trading volume fluctuations for the Shanghai Composite Index, the Shenzhen Component Index, the S & P 500 index and the Dow Jones Industrial Average
Summary
Most scholars apply econometric or variance models to analyze time series of financial markets. It is difficult to develop models that accurately describe relationships in complex financial systems using traditional time series analysis. Many scholars have applied complex scientific methods to the analysis of time series, and have discussed the relationship between the dynamic characteristics of time series and complex network topology, which is especially suitable for complex systems research where a precise mathematical model cannot be established. These studies are limited to the analysis of one-dimensional time series data, and rarely observe the structural features and evolution mechanism of the entire financial market from the viewpoint of multidimensional time series. We study the quantity-price relationship in the stock market using the complex network methodology and develop a method to analyze multidimensional time series data. We use closing price index series data from the Shanghai Composite Index, the Shenzhen stock index, the S & P 500 index, and the Dow Jones Industrial Average to study the relationship between volume and price in different markets, as well as differences between securities markets in China and the United States
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