Jump-robust estimation of volatility with simultaneous presence of microstructure noise and multiple observations

Finance and Stochastics - Tập 21 - Trang 427-469 - 2017
Zhi Liu1,2
1University of Macau, Macau SAR, China
2UM Zhuhai Research Institute, Zhuhai, China

Tóm tắt

In this paper, we develop the multipower estimators for the integrated volatility in (Barndorff-Nielsen and Shephard in J. Financ. Econom. 2:1–37, 2004); these estimators allow the presence of jumps in the underlying driving process and the simultaneous presence of microstructure noise and multiple records of observations. By multiple records we mean more than one observation recorded on a single time stamp, as often seen in stock markets, in particular, for heavily traded securities, for a data set with even millisecond frequency. We establish the consistency and asymptotic normality of the estimators for both noise-free and noise-present cases. Simulation studies confirm our theoretical results. We apply the estimators to a real high-frequency data set.

Tài liệu tham khảo

Aït-Sahalia, Y., Jacod, J.: Is Brownian motion necessary to model high frequency data? Ann. Stat. 38, 3093–3128 (2010) Aït-Sahalia, Y., Jacod, J.: Analyzing the spectrum of asset returns: jump and volatility components in high frequency data. J. Econ. Lit. 50, 1007–1050 (2012) Aït-Sahalia, Y., Xiu, D.: Increased correlation among asset classes: are volatility or jumps to blame, or both? J. Econom. 194, 205–219 (2016) Aldous, D., Eagleson, G.: On mixing and stability of limit theorems. Ann. Probab. 6, 325–331 (1978) Andersen, T.G., Bollerslev, T., Diebold, F., Labys, P.: The distribution of realized exchange rate volatility. J. Am. Stat. Assoc. 96, 42–55 (2001) Andersen, T.G., Bollerslev, T., Diebold, F., Labys, P.: Modeling and forecasting realized volatility. Econometrica 71, 579–625 (2003) Andersen, T.G., Dobrev, D., Schaumburg, E.: Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns. J. Appl. Econom. 25, 233–261 (2010) Bachelier, L.: Théorie de la Spéculation. Gauthier-Villars, Paris (1900) Barndorff-Nielsen, O., Graversen, S., Jacod, J., Podolskij, M., Shephard, N.: A central limit theorem for realised power and bipower variations of continuous semimartingales. In: Kabanov, Y., Liptser, R. (eds.) From Stochastic Analysis to Mathematical Finance, Festschrift for Albert Shiryaev, pp. 33–68. Springer, Berlin (2006) Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A., Shephard, N.: Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 76, 1481–1536 (2008) Barndorff-Nielsen, O.E., Hansen, P.R., Lunde, A., Shephard, N.: Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. J. Econom. 162, 149–169 (2011) Barndorff-Nielsen, O.E., Shephard, N.: Power and bipower variation with stochastic volatility and jumps. J. Financ. Econom. 2, 1–37 (2004) Black, F., Scholes, M.: The pricing of options and corporate liabilities. J. Polit. Econ. 81, 637–654 (1973) Christensen, K., Kinnebrock, S., Podolskij, M.: Pre-averaging estimators of the expost covariance matrix in noisy diffusion models with non-synchronous data. J. Econom. 159, 116–133 (2010) Christensen, K., Podolskij, M.: Asymptotic theory of range-based multipower variation. J. Financ. Econom. 10, 417–456 (2012) Cont, R., Tankov, P.: Financial Modelling with Jump Processes. Chapman & Hall/CRC Press, London (2004) Delbaen, F., Schachermayer, W.: A general version of the fundamental theorem of asset pricing. Math. Ann. 300, 463–520 (1994) Dimson, E.: Risk measurement when shares are subject to infrequent trading. J. Financ. Econ. 7, 197–226 (1979) Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50, 987–1007 (1982) Hayashi, T., Jacod, J., Yoshida, N.: Irregular sampling and central limit theorems for power variations: the continuous case. Ann. Inst. Henri Poincaré Probab. Stat. 47, 1197–1218 (2011) Hayashi, T., Yoshida, N.: Asymptotic normality of a covariance estimator for nonsynchronously observed diffusion processes. Ann. Inst. Stat. Math. 60, 367–406 (2008) Heston, S.L.: A closed-form solution for options with stochastic volatility with applications to bond and currency options. Rev. Financ. Stud. 6, 327–343 (1993) Hudson, W.N., Mason, J.D.: Variational sums for additive processes. Proc. Am. Math. Soc. 55, 395–399 (1976) Jacod, J., Li, Y., Mykland, P.A., Podolskij, M., Vetter, M.: Microstructure noise in the continuous case: the pre-averaging approach. Stoch. Process. Appl. 119, 2249–2276 (2009) Jacod, J., Podolskij, M., Vetter, M.: Limit theorems for moving averages of discretized processes plus noise. Ann. Stat. 38, 1478–1545 (2010) Jacod, J., Protter, P.: Discretization of Processes. Springer, New York (2012) Jacod, J., Shiryayev, A.V.: Limit Theorems for Stochastic Processes, 2nd edn. Springer, New York (2003) Jing, B., Kong, X., Liu, Z., Mykland, P.: On the jump activity index for semimartingales. J. Econom. 166, 213–223 (2012) Jing, B., Liu, Z., Kong, X.: Estimating the volatility functionals with multiple transactions. Econom. Theory 33, 331–365 (2017) Li, Y., Mykland, P., Renault, E., Zhang, L., Zheng, X.: Realized volatility when sampling times are possibly endogenous. Econom. Theory 30, 580–605 (2014) Liu, Z.: Estimating integrated co-volatility with partially miss-ordered high frequency data. Stat. Inference Stoch. Process. 19, 175–197 (2015) Merton, R.C.: Theory of rational option pricing. Bell J. Econ. Manag. Sci. 4, 141–183 (1973) Podolskij, M., Vetter, M.: Bipower-type estimation in a noisy diffusion setting. Stoch. Process. Appl. 119, 2803–2831 (2009) Renyi, A.: On stable sequences of events. Sankhya, Ser. A 25, 293–302 (1963) Revuz, D., Yor, M.: Continuous Martingales and Brownian Motion, 3rd edn. Springer, New York (2005) Todorov, V., Tauchen, G.: Activity signature functions for high frequency data analysis. J. Econom. 154, 125–138 (2010) Woerner, J.H.C.: Power and multipower variation: inference for high frequency data. In: Shiryaev, A.N., et al. (eds.) Stochastic Finance, pp. 343–363. Springer, Boston (2006) Xiu, D.: Quasi-maximum likelihood estimation of volatility with high frequency data. J. Econom. 159, 235–250 (2010) Zhang, L.: Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach. Bernoulli 12, 1019–1043 (2006) Zhang, L., Mykland, P., Aït-Sahalia, Y.: A tale of two time scales: determining integrated volatility with noisy high-frequency data. J. Am. Stat. Assoc. 100, 1394–1411 (2005)