Bias-optimal vol-of-vol estimation: the role of window overlapping

We derive a feasible criterion for the bias-optimal selection of the tuning parameters involved in estimating the integrated volatility of the spot volatility via the simple realized estimator by Barndorff-Nielsen and Veraart (2009). Our analytic results are obtained assuming that the spot volatility is a continuous mean-reverting process and that consecutive local windows for estimating the spot volatility are allowed to overlap in a finite sample setting. Moreover, our analytic results support some optimal selections of tuning parameters prescribed in the literature, based on numerical evidence. Interestingly, it emerges that window-overlapping is crucial for optimizing the finite-sample bias of volatility-of-volatility estimates.

[1]  Lan Zhang,et al.  Inference for Continuous Semimartingales Observed at High Frequency , 2009 .

[2]  Dennis Kristensen,et al.  ESTIMATION OF STOCHASTIC VOLATILITY MODELS BY NONPARAMETRIC FILTERING , 2010, Econometric Theory.

[3]  H. P. Boswijk,et al.  Estimating spot volatility with high-frequency financial data , 2014 .

[4]  Campbell R. Harvey,et al.  An Empirical Comparison of Alternative Models of the Short-Term Interest Rate , 1992 .

[5]  M. E. Mancino,et al.  Robustness of Fourier estimator of integrated volatility in the presence of microstructure noise , 2008, Comput. Stat. Data Anal..

[6]  Lan Zhang,et al.  A Tale of Two Time Scales , 2003 .

[7]  S. Ross,et al.  AN INTERTEMPORAL GENERAL EQUILIBRIUM MODEL OF ASSET PRICES , 1985 .

[8]  Christian Schlag,et al.  Volatility-of-Volatility Risk , 2018, Journal of Financial and Quantitative Analysis.

[9]  Volatility-of-Volatility Risk , 2018, Journal of Financial and Quantitative Analysis.

[10]  P. Mykland,et al.  Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics , 2008 .

[11]  S. Heston A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options , 1993 .

[12]  P. Malliavin,et al.  A Fourier transform method for nonparametric estimation of multivariate volatility , 2009, 0908.1890.

[13]  J. Jacod,et al.  High-Frequency Financial Econometrics , 2014 .

[14]  J. Teichmann,et al.  Fourier transform methods for pathwise covariance estimation in the presence of jumps , 2013, 1301.3602.

[15]  Almut E. D. Veraart,et al.  Stochastic Volatility of Volatility in Continuous Time , 2009 .

[16]  M. C. Recchioni,et al.  Fourier-Malliavin Volatility Estimation: Theory and Practice , 2017 .

[17]  T. Bollerslev,et al.  Estimating Stochastic Volatility Diffusion Using Conditional Moments of Integrated Volatility , 2001 .

[18]  Roberto Renò,et al.  Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting , 2008 .

[19]  L. Gillemot,et al.  Statistical theory of the continuous double auction , 2002, cond-mat/0210475.

[20]  Almut E. D. Veraart,et al.  Stochastic volatility and stochastic leverage , 2009 .

[21]  Eduardo S. Schwartz,et al.  Analyzing Convertible Bonds , 1980, Journal of Financial and Quantitative Analysis.

[22]  Yacine Ait-Sahalia,et al.  A Hausman Test for the Presence of Market Microstructure Noise in High Frequency Data , 2017, Journal of Econometrics.

[23]  T. Bollerslev,et al.  Expected Stock Returns and Variance Risk Premia , 2007 .

[24]  Jón Dańıelsson,et al.  On Time-Scaling of Risk and the Square-Root-Of-Time Rule , 2005 .

[25]  F. Bandi,et al.  Price and Volatility Co-Jumps , 2014 .

[26]  Mathias Vetter,et al.  Estimation of integrated volatility of volatility with applications to goodness-of-fit testing , 2011, 1206.5761.

[27]  F. Diebold,et al.  The distribution of realized stock return volatility , 2001 .

[28]  Stephen A. Ross,et al.  An Analysis of Variable Rate Loan Contracts , 1980 .

[29]  Joanna Goard,et al.  STOCHASTIC VOLATILITY MODELS AND THE PRICING OF VIX OPTIONS , 2013 .

[30]  J. Jacod,et al.  Statistical Properties of Microstructure Noise , 2013, 1302.1047.

[31]  D. Xiu,et al.  Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency , 2015 .

[32]  N. Shephard,et al.  Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation , 2005 .

[33]  Jim Gatheral,et al.  Zero-intelligence realized variance estimation , 2009, Finance Stochastics.

[34]  Mathias Vetter Estimation of integrated volatility of volatility with applications to goodness-of-fit testing , 2011 .

[35]  Jean Jacod,et al.  Do price and volatility jump together , 2010, 1010.4990.

[36]  Peter Christoffersen,et al.  Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns and Option Prices , 2007 .

[37]  Jianqing Fan,et al.  Estimation of the Continuous and Discontinuous Leverage Effects , 2015, Journal of the American Statistical Association.

[38]  R. Roll,et al.  A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market , 2008 .

[39]  A Hausman test for the presence of market microstructure noise in high frequency data , 2019, Journal of Econometrics.

[40]  Daniel B. Nelson ARCH models as diffusion approximations , 1990 .

[41]  T. Bollerslev,et al.  Expected Stock Returns and Variance Risk Premia , 2009 .

[42]  Lars Winkelmann,et al.  Common price and volatility jumps in noisy high-frequency data , 2014, 1407.4376.

[43]  S. Sanfelici,et al.  High-frequency volatility of volatility estimation free from spot volatility estimates , 2015 .

[44]  Jianqing Fan,et al.  The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency , 2011 .