Abstract
We analyze the properties of different estimators of multivariate volatilities in the presence of microstructure noise, with particular focus on the Fourier estimator. This estimator is consistent in the case of asynchronous data and is robust to microstructure effects; further, we prove the positive semi-definiteness of the estimated covariance matrix. The in-sample and forecasting properties of the Fourier method are analyzed through Monte Carlo simulations. We study the economic benefit of applying the Fourier covariance estimation methodology over other estimators in the presence of market microstructure noise from the perspective of an asset-allocation decision problem. We find that using Fourier methodology yields statistically significant economic gains under strong microstructure effects.
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© 2011 Maria Elvira Mancino and Simona Sanfelici
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Mancino, M.E., Sanfelici, S. (2011). Covariance Estimation and Dynamic Asset-Allocation under Microstructure Effects via Fourier Methodology. In: Gregoriou, G.N., Pascalau, R. (eds) Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures. Palgrave Macmillan, London. https://doi.org/10.1057/9780230298101_1
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DOI: https://doi.org/10.1057/9780230298101_1
Publisher Name: Palgrave Macmillan, London
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