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Asymptotic Theory for Power Variation of LSS Processes

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Ambit Stochastics

Abstract

This chapter provides an in-depth study of power variation and its asymptotics for Brownian and Lévy semistationary (BSS and LSS) processes. Power variation techniques are used to draw inference on the integrated variance process. The theory is rather well-developed for semimartingales, in particular for the Brownian case, but some theory can also be developed for Lévy-driven models. Beyond the semimartingale framework, the asymptotic theory for power variation for LSS processes turns out to be even harder and the corresponding proofs rely on different techniques, e.g. using concepts from Malliavin calculus. We present the key results in the semimartingale and the nonsemimartingale case. The latter, particularly in the context of LSS rather than BSS processes, is still a relatively open area.

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References

  • Aït-Sahalia, Y. & Jacod, J. (2014), High-Frequency Financial Econometrics, Princeton University Press, Princeton, New Jersey.

    Book  MATH  Google Scholar 

  • Aldous, D. J. & Eagleson, G. K. (1978), ‘On mixing and stability of limit theorems’, Annals of Probability 6(2), 325–331.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E., Corcuera, J. & Podolskij, M. (2011b), ‘Multipower variation for Brownian semistationary processes’, Bernoulli 17(4), 1159–1194.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E., Corcuera, J. & Podolskij, M. (2013b), Limit theorems for functionals of higher order differences of Brownian semistationary processes, in A. E. Shiryaev, S. R. S. Varadhan & E. Presman, eds, ‘Prokhorov and Contemporary Probability’, Vol. 33 of Springer Proceedings in Mathematics and Statistics, pp. 69–96.

    Google Scholar 

  • Barndorff-Nielsen, O. E., Graversen, S. E., Jacod, J., Podolskij, M. & Shephard, N. (2006a), A central limit theorem for realised power and bipower variations of continuous semimartingales, in ‘From stochastic calculus to mathematical finance’, Springer, Berlin, pp. 33–68.

    Chapter  Google Scholar 

  • Barndorff-Nielsen, O. E., Graversen, S. E., Jacod, J. & Shephard, N. (2006b), ‘Limit theorems for bipower variation in financial econometrics’, Econometric Theory 22(4), 677–719.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E., Pakkanen, M. & Schmiegel, J. (2014e), ‘Assessing relative volatility/intermittency/energy dissipation’, Electronic Journal of Statistics 8(21), 1996–2021.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E. & Schmiegel, J. (2009), Brownian semistationary processes and volatility/intermittency, in H. Albrecher, W. Rungaldier & W. Schachermeyer, eds, ‘Advanced Financial Modelling’, Radon Series on Computational and Applied Mathematics 8, W. de Gruyter, Berlin, pp. 1–26.

    MATH  Google Scholar 

  • Barndorff-Nielsen, O. E. & Shephard, N. (2002), ‘Econometric analysis of realized volatility and its use in estimating stochastic volatility models’, Journal of the Royal Statistical Society. Series B. Statistical Methodology 64(2), 253–280.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E. & Shephard, N. (2003), ‘Realized power variation and stochastic volatility models’, Bernoulli 9(2), 243–265.

    Article  MathSciNet  MATH  Google Scholar 

  • Barndorff-Nielsen, O. E. & Shephard, N. (2004), ‘Power and bipower variation with stochastic volatility and jumps’, Journal of Financial Econometrics 2(1), 1–37.

    Article  Google Scholar 

  • Barndorff-Nielsen, O. E., Shephard, N. & Winkel, M. (2006d), ‘Limit theorems for multipower variation in the presence of jumps’, Stochastic Processes and their Applications 116(5), 796–806.

    Article  MathSciNet  MATH  Google Scholar 

  • Basse-O’Connor, A., Heinrich, C. & Podolskij, M. (2018), ‘On limit theory for Lévy semi-stationary processes’, Bernoulli 24(4A), 3117–3146.

    Article  MathSciNet  MATH  Google Scholar 

  • Basse-O’Connor, A., Lachieze-Rey, R. & Podolskij, M. (2017), ‘Power variation for a class of stationary increments Lévy driven moving averages’, Annals of Probability 45(6B), 4477–4528.

    Article  MathSciNet  MATH  Google Scholar 

  • Basse-O’Connor, A. & Podolskij, M. (2017), ‘On critical cases in limit theory for stationary increments Lévy driven moving averages’, Stochastics 89(1), 360–383.

    Article  MathSciNet  MATH  Google Scholar 

  • Corcuera, J. M., Hedevang, E., Pakkanen, M. S. & Podolskij, M. (2013b), ‘Asymptotic theory for Brownian semi-stationary processes with application to turbulence’, Stochastic Processes and their Applications 123(7), 2552–2574. A Special Issue on the Occasion of the 2013 International Year of Statistics.

    Google Scholar 

  • Corcuera, J., Nualart, D. & Podolskij, M. (2014), ‘Asymptotics of weighted random sums’, Communications in Applied and Industrial Mathematics 6(1), e–486, 11.

    Google Scholar 

  • Diop, A., Jacod, J. & Todorov, V. (2013), ‘Central limit theorems for approximate quadratic variations of pure jump Itô semimartingales’, Stochastic Processes and their Applications 123(3), 839–886.

    Article  MathSciNet  MATH  Google Scholar 

  • Gärtner, K. & Podolskij, M. (2015), ‘On non-standard limits of Brownian semi-stationary processes’, Stochastic Processes and their Applications 125(2), 653–677.

    Article  MathSciNet  MATH  Google Scholar 

  • Granelli, A. (2016), Limit theorems and stochastic models for dependence and contagion in financial markets, PhD thesis, Imperial College London.

    Google Scholar 

  • Granelli, A. & Veraart, A. E. D. (2017), ‘A weak law of large numbers for estimating the correlation in bivariate Brownian semistationary processes’, ArXiv e-prints. E-print 1707.08505.

    Google Scholar 

  • Granelli, A. & Veraart, A. E. D. (2018+), ‘A central limit theorem for the realised covariation of a bivariate Brownian semistationary process’, Bernoulli. Accepted for publication.

    Google Scholar 

  • Jacod, J. (2008), ‘Asymptotic properties of realized power variations and related functionals of semimartingales’, Stochastic Processes and their Applications 118(4), 517–559.

    Article  MathSciNet  MATH  Google Scholar 

  • Jacod, J. & Protter, P. (2012), Discretization of processes, Vol. 67 of Stochastic Modelling and Applied Probability, Springer, Heidelberg.

    Google Scholar 

  • Jacod, J. & Shiryaev, A. N. (2003), Limit theorems for stochastic processes, Vol. 288 of Grundlehren der Mathematischen Wissenschaften [Fundamental Principles of Mathematical Sciences], second edn, Springer-Verlag, Berlin.

    Google Scholar 

  • Mancini, C. (2001), ‘Disentangling the jumps of the diffusion in a geometric jumping Brownian motion’, Giornale dell’Instituto Italiano degli Attuari 64, 19–47.

    Google Scholar 

  • Mancini, C. (2004), Estimating the integrated volatility in stochastic volatility models with Lévy jumps. Technical report, Università di Firenze.

    Google Scholar 

  • Mancini, C. (2009), ‘Non-parametric threshold estimation for models with stochastic diffusion coefficient and jumps’, Scandinavian Journal of Statistics 36(2), 270–296.

    Article  MathSciNet  MATH  Google Scholar 

  • Mancino, M. E., Recchioni, M. C. & Sanfelici, S. (2017), Fourier-Malliavin volatility estimation: Theory and practice, Springer Briefs in Quantitative Finance, Springer.

    Book  MATH  Google Scholar 

  • Passeggeri, R. & Veraart, A. E. D. (2017), ‘Limit theorems for multivariate Brownian semistationary processes and feasible results’, ArXiv e-prints. E-print 1712.03564.

    Google Scholar 

  • Podolskij, M. (2015), Ambit fields: survey and new challenges, in R. H. Mena, J. C. Pardo, V. Rivero & G. U. Bravo, eds, ‘XI Symposium of Probability and Stochastic Processes: CIMAT, Mexico, November 18–22, 2013’, Vol. 69 of Progress in Probability, Springer, pp. 241–279.

    Google Scholar 

  • Protter, P. E. (2005), Stochastic integration and differential equations, Vol. 21 of Stochastic Modelling and Applied Probability, Springer-Verlag, Berlin. Second edition. Version 2.1, Corrected third printing.

    Google Scholar 

  • Rényi, A. (1963), ‘On stable sequences of events’, Sankhyā (Statistics). The Indian Journal of Statistics. Series A 25, 293–302.

    MathSciNet  MATH  Google Scholar 

  • Todorov, V. & Tauchen, G. (2012), ‘Realized Laplace transforms for pure-jump semimartingales’, The Annals of Statistics 40(2), 1233–1262.

    Article  MathSciNet  MATH  Google Scholar 

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Barndorff-Nielsen, O.E., Benth, F.E., Veraart, A.E.D. (2018). Asymptotic Theory for Power Variation of LSS Processes. In: Ambit Stochastics. Probability Theory and Stochastic Modelling, vol 88. Springer, Cham. https://doi.org/10.1007/978-3-319-94129-5_3

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