中文摘要：

将向量自回归模型（VAR）中交易方向的预期格式应用于Madhavan等的MRR模型,从而构建一个能精确估计信息风险的模型——VAR-MRR模型.理论上MRR模型对交易的预期仅以一笔交易方向为信息预测下一笔交易,没有充分利用以往交易信息;而VAR-MRR模型充分利用以往交易信息,使得信息风险的度量更精确.选取2004年上证50做样本,发现并验证MRR模型不仅高估信息风险,且丢失的信息使其在准确度上偏差较大.进一步发现,在我国上证市场,流动成本占交易成本的主要部分,信息风险与流动成本的日内模式均表现为U型.

英文摘要：

Based on the VAR model,we modify MRR model（ Madhavan et al. 1997） by extending the expectation formula which measures the next trade sign. We argue that MRR model overestimates the information risk as the expectation formula in MRR model could not capture the full information. We present a VAR structure to replace the one period expectation formula in MRR model and give a new model（ VAR-MRR）. Using the high frequency data of the 50 stocks of the SSE 50 index of 2004,we estimate and test the information risks of MRR and VAR-MRR. The results show that MRR overestimates the information risk,and the incomplete information capturing results in inaccurate estimations in MRR. Further,the results show that the liquidity cost dominated the information risk. Shanghai Stock Exchange exhibit U-shape intraday patterns for the information risk and the liquidity cost.