How Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noise

Yacine Aït-Sahalia (), Per A. Mykland () and Lan Zhang ()
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Yacine Aït-Sahalia: Princeton University, Bendheim Center for Finance
Per A. Mykland: The University of Chicago, Department of Statistics
Lan Zhang: Carnegie Mellon University, Department of Statistics

Chapter 1 in Stochastic Finance, 2006, pp 3-72 from Springer

Abstract: Summary In theory, the sum of squares of log returns sampled at high frequency estimates their variance. When market microstructure noise is present but unaccounted for, however, we show that the optimal sampling frequency is finite and derive its closed-form expression. But even with optimal sampling, using say five minute returns when transactions are recorded every second, a vast amount of data is discarded, in contradiction to basic statistical principles. We demonstrate that modelling the noise and using all the data is a better solution, even if one misspecifies the noise distribution. So the answer is: sample as often as possible.

Keywords: Noise Term; Stochastic Volatility; Asymptotic Variance; Price Process; Noise Distribution (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-28359-3_1

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DOI: 10.1007/0-387-28359-5_1

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