Aït-Sahalia, Yacine; Jacod, Jean Identifying the successive Blumenthal-Getoor indices of a discretely observed process. (English) Zbl 1297.62051 Ann. Stat. 40, No. 3, 1430-1464 (2012). Summary: This paper studies the identification of the Lévy jump measure of a discretely-sampled semimartingale. We define successive Blumenthal-Getoor indices of jump activity, and show that the leading index can always be identified, but that higher order indices are only identifiable if they are sufficiently close to the previous one, even if the path is fully observed. This result establishes a clear boundary on which aspects of the jump measure can be identified on the basis of discrete observations, and which cannot. We then propose an estimation procedure for the identifiable indices and compare the rates of convergence of these estimators with the optimal rates in a special parametric case, which we can compute explicitly. Cited in 14 Documents MSC: 62F12 Asymptotic properties of parametric estimators 62M05 Markov processes: estimation; hidden Markov models 60H10 Stochastic ordinary differential equations (aspects of stochastic analysis) 60J60 Diffusion processes Keywords:semimartingale; Brownian motion; jumps; finite activity; infinite activity; discrete sampling; high frequency PDF BibTeX XML Cite \textit{Y. Aït-Sahalia} and \textit{J. Jacod}, Ann. Stat. 40, No. 3, 1430--1464 (2012; Zbl 1297.62051) Full Text: DOI arXiv Euclid References: [1] Aït-Sahalia, Y. and Jacod, J. (2008). Fisher’s information for discretely sampled Lévy processes. Econometrica 76 727-761. · Zbl 1144.62070 [2] Aït-Sahalia, Y. and Jacod, J. (2009a). Estimating the degree of activity of jumps in high frequency financial data. Ann. Statist. 37 2202-2244. · Zbl 1173.62060 [3] Aït-Sahalia, Y. and Jacod, J. (2009b). Testing for jumps in a discretely observed process. Ann. Statist. 37 184-222. · Zbl 1155.62057 [4] Aït-Sahalia, Y. and Jacod, J. (2011). Testing whether jumps have finite or infinite activity. Ann. Statist. 39 1689-1719. · Zbl 1234.62117 [5] Aït-Sahalia, Y. and Jacod, J. (2012). Supplement to “Identifying the successive Blumenthal-Getoor indices of a discretely observed process.” . · Zbl 1297.62051 [6] Basawa, I. V. and Brockwell, P. J. (1982). Nonparametric estimation for nondecreasing Lévy processes. J. Roy. Statist. Soc. Ser. B 44 262-269. · Zbl 0491.62069 [7] Belomestny, D. (2010). Spectral estimation of the fractional order of a Lévy process. Ann. Statist. 38 317-351. · Zbl 1181.62151 [8] Blumenthal, R. M. and Getoor, R. K. (1961). Sample functions of stochastic processes with stationary independent increments. J. Math. Mech. 10 493-516. · Zbl 0097.33703 [9] Comte, F. and Genon-Catalot, V. (2009). Nonparametric estimation for pure jump Lévy processes based on high frequency data. Stochastic Process. Appl. 119 4088-4123. · Zbl 1177.62043 [10] Cont, R. and Mancini, C. (2011). Nonparametric tests for pathwise properties of semimartingales. Bernoulli 17 781-813. · Zbl 1345.62074 [11] Figueroa-López, J. E. and Houdré, C. (2006). Risk bounds for the non-parametric estimation of Lévy processes. In High Dimensional Probability (E. Giné, V. Koltchinskii, W. Li and J. Zinn, eds.). Institute of Mathematical Statistics Lecture Notes-Monograph Series 51 96-116. IMS, Beachwood, OH. · Zbl 1117.62085 [12] Jacod, J. and Shiryaev, A. N. (2003). Limit Theorems for Stochastic Processes , 2nd ed. Grundlehren der Mathematischen Wissenschaften [ Fundamental Principles of Mathematical Sciences ] 288 . Springer, Berlin. · Zbl 1018.60002 [13] Mancini, C. (2004). Estimating the integrated volatility in stochastic volatility models with Lévy type jumps. Technical report, Univ. Firenze. [14] Neumann, M. H. and Reiss, M. (2009). Nonparametric estimation for Lévy processes from low-frequency observations. Bernoulli 15 223-248. · Zbl 1200.62095 [15] Nishiyama, Y. (2008). Nonparametric estimation and testing time-homogeneity for processes with independent increments. Stochastic Process. Appl. 118 1043-1055. · Zbl 1144.62025 [16] Rosiński, J. (2007). Tempering stable processes. Stochastic Process. Appl. 117 677-707. · Zbl 1118.60037 [17] Todorov, V. and Tauchen, G. (2010). Activity signature functions for high-frequency data analysis. J. Econometrics 154 125-138. · Zbl 1431.62483 [18] Zolotarev, V. M. (1995). On representation of densities of stable laws by special functions. Theory Probab. Appl. 39 354-362. · Zbl 0872.60012 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.