Estimating the Variance Parameter From Noisy High Frequency Financial Data (Classic Reprint) - Softcover

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Excerpt from Estimating the Variance Parameter From Noisy High Frequency Financial Data

I call the diffusion process the signal process and the fit observation noise. The observation noise is the deviation of data from the continuous process and is assumed to be independent from the diffusion process. Many things contribute to this observation noise. In the currency market, for example, non-binding quoting error is part of the noise. In other markets, bid and offer difference also contributes to the observation noise. Many other micro structural behaviors are all included in this so - called observation noise. For low frequency observations, the observation noise is overwhelmed by the sig nal change. When observation frequency increases, the signal change becomes smaller and smaller while the size of the noise remains the same. The noise totally dominates the price change in ultra-high frequency data. Viewing high frequency data as observation with noise certainly captures many basic characteristics of high frequency financial time series mentioned above.

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