With the availability of ultra high frequency financial data, the task of finding an appropriate econometric model to describe the movement of financial variables at the tick-by-tick level has become an important goal in financial econometric research. The task has both theoretical and empirical dimensions. From an empirical perspective, the near continuous recording of financial asset prices has opened up the intriguing possibility of fitting the quadratic variation process empirically, leading to what is possibly the most direct nonparametric measure of asset price volatility. The resulting quantity has become known in the financial econometrics literature as realized variance (RV) and measures the accumulated or integrated variance (IV) of the efficient price process from some given initialization. This quantity is now the focal point of much of the latest research on market volatility.
PHILLIPS, Peter C. B. and YU, Jun.
Comment on "Realized Variance and Market Microstructure Noise" by Peter R. Hansen and Asger Lunde. (2005). Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/855
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