A Tale of Two Time Scales: Determining Integrated Volatility with Noisy High Frequency Data
University of Illinois at Chicago - Department of Finance
Princeton University - Department of Economics; National Bureau of Economic Research (NBER)
Per A. Mykland
University of Chicago - Department of Statistics
NBER Working Paper No. w10111
It is a common practice in finance to estimate volatility from the sum of frequently-sampled squared returns. However market microstructure poses challenges to this estimation approach, as evidenced by recent empirical studies in finance. This work attempts to lay out theoretical grounds that reconcile continuous-time modeling and discrete-time samples. We propose an estimation approach that takes advantage of the rich sources in tick-by-tick data while preserving the continuous-time assumption on the underlying returns. Under our framework, it becomes clear why and where the usual' volatility estimator fails when the returns are sampled at the highest frequency.
Number of Pages in PDF File: 30working papers series
Date posted: November 19, 2003
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