A state space model approach to integrated covariance matrix estimation with high frequency data

• المؤلفون الرئيسيون: Liu, Cheng, TANG, Cheng Yong
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2013
• الموضوعات: EM algorithm; High frequency data; Integrated covariance matrix; Kalman Filter; Microstructure noise; Missing data; Quasi-maximum likelihood; State Space Model; Econometrics; Economic Theory
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/lkcsb_research/5603; https://ink.library.smu.edu.sg/context/lkcsb_research/article/6602/viewcontent/A_state_space_model_approach_to_integrated_covariance_matrix_estimation_with_high_frequency_data.pdf
• المؤسسة: Singapore Management University

We consider a state space model approach forhigh frequency financial data analysis. An expectationmaximization(EM) algorithm is developed for estimatingthe integrated covariance matrix of the assets. The statespace model with the EM algorithm can handle noisy financialdata with correlated microstruc...