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对股票信息风险进行准确的测度无论对资产定价、风险管理还是市场绩效的衡量都有着重要意义。Easley,Kiefer,O’Hara and Paperman(1996)最早提出了直接测度信息风险的经典PIN模型,此后该模型成为测度信息风险的炙手可热的模型。然而,PIN模型隐含的买卖指令之间的负相关性与实际数据中买卖指令之间的正相关性并不相符。本文在Easley,Kiefer,O’Hara and Paperman(1996)提出的经典的PIN模型基础上,通过增加交易动机,提出了修正的PIN模型。本文基于中国股票的逐笔交易数据,利用修正的PIN模型对我国股票具有的信息风险进行的实证研究表明,修正的PIN模型隐含的买卖指令之间的相关性和买卖指令的方差能够更好地与实际数据相匹配。经典的PIN模型由于忽视了市场指令流冲击事件发生时引起的交易动机,倾向于高估股票具有的信息风险。
Accurate measurement of the risk of stock information is of great significance both in asset pricing, in risk management and in the measurement of market performance. Easley, Kiefer, O’Hara, and Paperman (1996) first proposed a classic PIN model that directly measures information risk, which has since become the hottest model for measuring information risk. However, the negative correlation between the implied buy and sell orders in the PIN model does not match the positive correlation between buy and sell orders in the real data. Based on the classic PIN model proposed by Easley, Kiefer, O’Hara and Paperman (1996), this paper proposes a revised PIN model by increasing the trading motivation. Based on the transaction-by-transaction data of Chinese stocks, an empirical study of the information risk posed by Chinese stocks using the revised PIN model shows that the correlation between the implied sales orders and the variance of the sales orders can be better Match with the actual data. The classic PIN model tends to overestimate the information risk possessed by the stock due to ignoring the trading motivation arising from the market instruction flow shock event.