基于股市和汇市成交量信息视角的股价波动预测

以往研究忽略了汇市成交量包含的信息对股价波动的影响,可能导致模型参数的有偏估计.基于泊松分布的随机波动率模型不仅可有效解决传统做法对成交量信息使用不足的问题,而且通过将汇市成交量信息引入模型,与现有文献形成有益补充.通过SMC算法编程实现了SV-VOL模型的有效估计,发现股市成交量信息有助于股价波动预测;汇市成交量信息是通过股市流入净资本这一间接渠道最终影响股票收益率与股市量价关系.

Forecast of stock price fluctuation based on the perspective of volume information in stock and foreign exchange market

Previous studies have neglected the influence of the information contained in the volume of foreign exchange market on the stock price volatility, which leads to the biased estimation of the model parameters probably. SV-VOL model based on Poisson distribution, not only can effectively solve the traditional the problem of insufficient use of volume information, but also form a useful supplement to the existing literature by introducing the volume information into the model through weighted processing. SMC algorithm by programming to achieve the effective estimation of the SV-VOL model, found that the stock market trading volume information is helpful to the stock price volatility forecast, exchange market volume information ultimately affects stock returns and stock price-volume relationship through the indirect channel of net capital in-flows of stock market.