02503cam a22002657 4500001000600000003000500006005001700011008004100028100002500069245015900094260006600253490004100319500001600360520119900376530006101575538007201636538003601708690011201744690017001856700002002026710004202046830007602088856003702164856003602201w9611NBER20170816224519.0170816s2003 mau||||fs|||| 000 0 eng d1 aAit-Sahalia, Yacine.10aHow Often to Sample a Continuous-Time Process in the Presence of Market Microstructure Noiseh[electronic resource] /cYacine Ait-Sahalia, Per A. Mykland. aCambridge, Mass.bNational Bureau of Economic Researchc2003.1 aNBER working paper seriesvno. w9611 aApril 2003.3 aClassical statistics suggest that for inference purposes one should always use as much data as is available. We study how the presence of market microstructure noise in high-frequency financial data can change that result. We show that the optimal sampling frequency at which to estimate the parameters of a discretely sampled continuous-time model can be finite when the observations are contaminated by market microstructure effects. We then address the question of what to do about the presence of the noise. We show that modelling the noise term explicitly restores the first order statistical effect that sampling as often as possible is optimal. But, more surprisingly, we also demonstrate that this is true even if one misspecifies the assumed distribution of the noise term. Not only is it still optimal to sample as often as possible, but the estimator has the same variance as if the noise distribution had been correctly specified, implying that attempts to incorporate the noise into the analysis cannot do more harm than good. Finally, we study the same questions when the observations are sampled at random time intervals, which are an essential feature of transaction-level data. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web. 7aG12 - Asset Pricing • Trading Volume • Bond Interest Rates2Journal of Economic Literature class. 7aC22 - Time-Series Models • Dynamic Quantile Regressions • Dynamic Treatment Effect Models • Diffusion Processes2Journal of Economic Literature class.1 aMykland, Per A.2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w9611.4 uhttp://www.nber.org/papers/w961141uhttp://dx.doi.org/10.3386/w9611