Estimating the quadratic covariation matrix from noisy observations: Local method of moments and efficiency

Arbeitspapier

An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under high-frequency asymptotics. Our approach relies on an asymptotically equivalent continuous-time observation model where a local generalised method of moments in the spectral domain turns out to be optimal. Asymptotic semiparametric efficiency is established in the Cramér-Rao sense. Main findings are that non-synchronicity of observation times has no impact on the asymptotics and that major efficiency gains are possible under correlation. Simulations illustrate the finite-sample behaviour.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2013-017

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Financial Econometrics ; General Financial Markets: General (includes Measurement and Data)
• Subject: adaptive estimation ; asymptotic equivalence ; asynchronous observations ; integrated covolatility matrix ; quadratic covariation ; semiparametric efficiency ; microstructure noise ; spectral estimation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bibinger, Markus ; Hautsch, Nikolaus ; Malec, Peter ; Reiss, Markus
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/79613
• Last update: 10.03.2025, 11:44 AM CET