Geography and distance effect on financial dynamics in the Chinese stock market

Abstract

Geography effect is investigated for the Chinese stock market including the Shanghai and Shenzhen stock markets, based on the daily data of individual stocks. The Shanghai city and the Guangdong province can be identified in the stock geographical sector. By investigating a geographical correlation on a geographical parameter, the stock location is found to have an impact on the financial dynamics, except for the financial crisis time of the Shenzhen market. Stock distance effect is further studied, with a crossover behavior observed for the stock distance distribution. The probability of the short distance is much greater than that of the long distance. The average stock correlation is found to weakly decay with the stock distance for the Shanghai stock market, but stays nearly stable for different stock distance for the Shenzhen stock market.

Home bias and local equity portfolio decisions of Chinese insurance institutional investors

“…By far, the motives that lead to local preference of investors are driven by information advantages or behavioral bias is a subject of debate in various strands of literature [8,10,16,17]. Geography and distance effect has an important impact for the Chinese stock market [18]. Despite the rapid growth of the insurance sector, there is relatively little understanding of how insurance equity managers decide their equity portfolios and, in turn, how their choices affect the underlying funds' efficiency; thus, our paper fills this gap by explicitly analyzing the geographical preferences when China's insurance companies choose equity investment allocations.…”

Quantifying the Cross-Correlations between Online Market Participation Willingness and Stock Market Dynamics

“…First, we focus on the relationship between investors' market participation willingness and the stock market. Existing literature about behavioral finance mainly focused on investor happiness [23,24], investor sentiment [25][26][27], investor attention [28][29][30], and geographical information [31,32]. is paper is the first one to give empirical analysis on the nonlinear cross-correlation between investors' market participation willingness and Chinese stock market performance.…”