股票市场在金融领域的影响举足轻重，各类金融、经济与社会因素均不同程度地影响着股票价格走势。但随着金融自由化的推进，跨国股票价格间的关联更加紧密，股市受到的影响更明显。基于此背景，为了研究影响因素对股票价格的作用，发掘各因素对国际股票市场作用的普遍规律，本文应用跨国面板数据对股票价格的影响因素进行研究。
已有的股价影响因素研究涉及到经济、金融、社会等各方面因素，本文根据此分类完成文献综述，并做出相关文献评价。基于此，在影响因素的理论分析中，本文从宏观经济、金融市场以及社会结构角度分析了经济、金融与人口等各因素对于股票价格的影响作用，并此理论分析作为实证模型构建与分析的重要依据。
在实证分析中，本文应用44个国家1999年至2019年的面板数据构建平衡面板模型，以股票价格为被解释变量，应用静态与动态面板回归法、空间面板回归法与面板分位数回归法，研究各变量对股票价格的影响效果，通过空间面板模型的构建分析空间地理因素对股票价格的影响，以及考察在不同分位点下解释变量对股票价格的影响情况。
实证结果显示，在一定程度上股票市场反映了宏观经济的状况，GDP、GDP平减指数以及货币增长率对股票价格的增长有正向的效应，而债务增长率对股票价格的增长有负向的效应；在金融市场变量方面，金融市场从多方面影响股价走势，市场利率、大宗商品价格、黄金价格与美元指数变量对股票价格的增长有负向影响，而原油价格对股票价格的增长表现出正向影响；社会结构因素对股票价格指数的影响显著，且影响作用较强，其中高收入人群收入份额变量对股票价格有显著正向影响，老龄化增长率对股票价格的影响负向显著。之后，在空间面板回归结果中，股票价格存在显著空间相关性，部分解释变量存在显著空间溢出效应，GDP平减指数、货币增长率等变量表现出显著的正向间接效应，债务增长率表现出显著的负向间接效应，说明这些解释变量会对基于空间关联的临近地区的股票价格产生影响。接着，在面板分位数回归结果中，各变量系数显著性与符号的正负与其他面板模型相同，确保实证分析的稳健性，但不同分位点下各变量的影响程度表现出不同显著的显著情况，说明各影响因素在股票价格处于不同分位点时的显著性存在差异。
最后，基于实证研究结果，文章提出了实施积极且稳健的经济发展政策、加强金融制度建设、健全与完善国家金融体制、完善社会保障体系、积极应对社会老龄化、收入不平等等问题等方面的若干政策建议，并建议投资者积极考虑跨国股票市场的空间关联效应以及金融市场因素的影响，积极做好股票市场的风险对冲与分散。

The stock market plays an important role in the financial field. Various financial, economic and social factors affect the trend of stock prices in varying degrees. However, with the promotion of financial liberalization, the correlation between transnational stock prices is closer, and the impact on the stock market is more obvious, and the correlation between transnational stock prices is closer. The development of the international stock market reflects a certain universal law. Based on this background, for the sake of studying the impact of influence factors on the stock price and finding universal pattern of the role of influence factors on the international stock market, this research uses transnational panel data to study the influence factors of stock price.
The existing research on the influence factors of stock price involves economic, financial, social and other factors. According to this classification, this paper completes the literature review and makes the relevant literature evaluation. Based on this, in the theoretical analysis of influence factors, this research analyzes the impact of economic, financial and demographic factors on stock prices from the views of macro-economy, financial market and social structure, and this theoretical analysis is used as an important basis for the construction and analysis of empirical model.
In the empirical analysis, this paper uses the panel data of 44 countries from 1999 to 2019 to construct a balanced panel model. Taking the stock price as the explanatory variable, this research uses static and dynamic panel regression, spatial panel regression and panel quantile regression to study the impact of various variables on the stock price, analyze the impact of spatial geographical factors on the stock price through the construction of a spatial panel model, and investigate the significance of explanatory variables on stock price under different quantiles.
The empirical results show that the stock market reflects the macroeconomic situation to a certain extent. GDP, GDP deflator and monetary growth rate have a positive effect on the growth of stock price, while debt growth rate has a negative effect on the growth of stock price; In terms of financial market variables, the financial market affects the stock price trend from many aspects. Market interest rate, commodity price, gold price and US dollar index variables influence the growth of stock price negatively, while oil price influences on the growth of stock price positively; Social structure have a significant and strong impact on the stock price index, positively influence the stock price. Income share of high-income group has a significant positive impact on the stock price, and the aging growth rate has a significant negative impact on the stock price; Then, in the spatial panel regression results, the stock price has significant spatial correlation, some explanatory variables have significant spatial spillover effects, GDP deflator, currency growth rate and other variables show significant positive indirect effects, and debt growth rate shows significant negative indirect effects, indicating that these explanatory variables will have an impact on the stock price of adjacent areas based on spatial correlation. In addition, in the panel quantile regression results, the significance and sign of each variable coefficient are the same as that of other panel models to ensure the robustness of the empirical analysis, but the influence degree of each variable under different quantiles shows different significant situations, indicating that the significance of each influencing factor is different when the stock price is at different quantiles.
Finally, based on the empirical research results, there are some suggestions on implementing active and stable economic development policies, strengthening the construction of financial system, improving and perfecting the national financial system, improving the social security system and actively dealing with social aging, income inequality and other issues, and suggests investors to actively consider the spatial correlation effect of transnational stock market and the influence of financial market factors, actively hedge and diversify risks in the stock market.