Large-Dimensional Factor Modeling Based on High-Frequency Observations

Large-Dimensional Factor Modeling Based on High-Frequency Observations
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Total Pages : 125
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ISBN-10 : OCLC:1304490811
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Book Synopsis Large-Dimensional Factor Modeling Based on High-Frequency Observations by : Markus Pelger

Download or read book Large-Dimensional Factor Modeling Based on High-Frequency Observations written by Markus Pelger and published by . This book was released on 2018 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops a statistical theory to estimate an unknown factor structure based on financial high-frequency data. We derive an estimator for the number of factors and consistent and asymptotically mixed-normal estimators of the loadings and factors under the assumption of a large number of cross-sectional and high-frequency observations. The estimation approach can separate factors for continuous and rare jump risk. The estimators for the loadings and factors are based on the principal component analysis of the quadratic covariation matrix. The estimator for the number of factors uses a perturbed eigenvalue ratio statistic. In an empirical analysis of the S&P 500 firms we estimate four stable continuous systematic factors, which can be approximated very well by a market and industry portfolios. Jump factors are different from the continuous factors.

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