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Out of sample forecasts of quadratic variation

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Author Info
Aït-Sahalia, Yacine
Mancini, Loriano

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Abstract

We compare the forecasts of Quadratic Variation given by the Realized Volatility (RV) and the Two Scales Realized Volatility (TSRV)Â computed from high frequency data in the presence of market microstructure noise, under several different dynamics for the volatility process and assumptions on the noise. We show that TSRV largely outperforms RV, whether looking at bias, variance, RMSE or out-of-sample forecasting ability. An empirical application to all DJIA stocks confirms the simulation results.

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File URL: http://www.sciencedirect.com/science/article/B6VC0-4TG9J0C-1/2/39829f4dfe5c92b7963f8391f6cb64c4
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Publisher Info
Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 147 (2008)
Issue (Month): 1 (November)
Pages: 17-33
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Handle: RePEc:eee:econom:v:147:y:2008:i:1:p:17-33

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Web page: http://www.elsevier.com/locate/jeconom

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Related research
Keywords: Market microstructure noise High frequency data Measurement error Realized volatility Two scales realized volatility Out of sample forecasts;

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  1. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-3, Swiss National Bank. [Downloadable!]
  2. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena. [Downloadable!]
  3. Fulvio Corsi & Davide Pirino & Roberto Reno, 2009. "Volatility Forecasting: The Jumps Do Matter," Global COE Hi-Stat Discussion Paper Series gd08-036, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
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