期刊论文

Kong, Xin-Bing

英文

Journal of Statistical Planning and Inference

0378-3758

2013

143

10

1708-1718

10.1016/j.jspi.2013.05.003

The authors would like to thank the editor, an associate editor and referees for their constructive suggestions that improved this paper considerably. Li's work is supported by the Fundamental Research Funds for the Central Universities ( lzujbky-2012-179 ). Kong's work is supported in part by the NSF China ( 11201080 ) and in part by the Humanity and Social Science Youth Foundation of Chinese Ministry of Education ( 12YJC910003 ). JING's research is supported by Hong Kong RGC Grants HKUST6019/10P and HKUST6019/12P , and in part by the Fundamental Research Funds for the Central Universities , Research Funds of Renmin University of China (Grant no. 10XNL007 ), and by NSF China (Grant no. 71071010 ).

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In this paper, we are concerned with the inference of the integrated self-weighted cross volatility, ∫01g(Xt,Yt)σtXYdt, where g is some real function, σtXY is the instantaneous cross volatility of two continuous semi-martingales X and Y. We assume that processes X and Y are sampled with microstructure noise and in an asynchronous way. The asymptotic normality is investigated and a consistent estimator of the resulting limiting conditional variance is presented yielding a studentized central limit theorem. Simulation is given to...