Publications 

C. Amorino, A. Jaramillo and M. Podolskij (2023): Quantitative and stable limits of high-frequency statistics of L´evy processes: a Stein’s method approach. 

C. Amorino, F. Pina Monzo and M. Podolskij (2024):  Sampling effects on Lasso estimation of drift functions in high-dimensional diffusion processes.

D. Belomestny, M. Podolskij and S.-Y. Zhou (2024): On nonparametric estimation of the interaction function in particle system models. 

C.Amorino, D. Belomestny, V. Pilipauskaite, M. Podolskij and S.-Y. Zhou (2024+): Polynomial rates via deconvolution for nonparametric estimation in McKean-Vlasov SDEs. To appear in Probability Theory and Related Fields. 

G. Ciolek, D. Marushkevych and M. Podolskij (2024+): On Lasso estimator for the drift function in diffusion models. To appear in Bernoulli. 

S. Campese, N. Lengert and M. Podolskij (2024): Limit theorems for general functionals of Brownian local times Electronic Journal of Probability, paper no. 128, 1–18. 

C. Amorino, A. Jaramillo and M. Podolskij (2024): Optimal estimation of local time and occupation time measure for an α-stable Lévy process. Modern Stochastics: Theory and Applications 11(2), 149–168. 

A. Basse-O’Connor and M. Podolskij (2024): Asymptotic theory for quadratic variation of harmonizable fractional stable processes. Theory of Probability and Mathematical Statistics 110, 3–12. 

F. Mies and M. Podolskij (2023): Estimation of mixed fractional stable processes using high-frequency data. Annals of Statistics 51(5), 1946–1964. 

C. Amorino, A. Heidari, V. Pilipauskaite and M. Podolskij (2023): Parameter estimation of discretely observed interacting particle systems. Stochastic Processes and Their Applications 163, 350–386. 

K. Christensen, M.S. Nielsen and M. Podolskij (2023): High-dimensional estimation of quadratic variation based on penalized realized variance. Statistical Inference for Stochastic Processes 26, 331–359. 

D. Belomestny, V. Pilipauskaite and M. Podolskij (2023): Semiparametric estimation of McKean-Vlasov SDEs. Annales de l’Institut Henri Poincar´e 59(1), 79–96. 

J. Ivanovs and M. Podolskij (2022): Optimal estimation of some random quantities of a Lévy process. Electronic Journal of Statistics 16(1), 892–934. 

M. Ljungdahl and M. Podolskij (2022): Multi-dimensional parameter estimation of heavy-tailed moving averages. Scandinavian Journal of Statistics 49(2), 593–624. 

A. Basse-O’Connor, T. Grønbæk and M. Podolskij (2021): Local asymptotic self-similarity for heavy-tailed harmonizable fractional Lévy motions. ESAIM: Probability and Statistics 25, 286–297. 

J. Heiny and M. Podolskij (2021): On estimation of quadratic variation for multivariate pure jump semimartingales. Stochastic Processes and Their Applications 138, 234–254. 

A. Basse-O’Connor, V.Pilipauskaite and M. Podolskij (2021): Power variations for fractional type infinitely divisible random fields. Electronic Journal of Probability 26(55), 1–35. 

G. Ciolek, D. Marushkevych and M. Podolskij (2020): On Dantzig and Lasso estimators of the drift in a high dimensional Ornstein-Uhlenbeck model. Electronic Journal of Statistics 14(2), 4395–4420. 

M.M. Ljungdahl and M. Podolskij (2020): A minimal contrast estimator for the linear fractional stable motion. Statistical Inference for Stochastic Processes 23, 381–413. 

A. Basse-O’Connor, M. Podolskij and C. Thäle (2020): A Berry-Esse´en theorem for partial sums of functionals of heavy-tailed moving averages. Electronic Journal of Probability 25(31), 1–31. 

M. Podolskij, B. Veliyev and N. Yoshida (2020): Edgeworth expansion for Euler approximation of continuous diffusion processes. Annals of Applied Probability 30(4), 1971–2003. 

S. Mazur, D. Otryakhin and M. Podolskij (2020): Estimation of the linear fractional stable motion. Bernoulli 26(1), 226–252. 

A. Basse-O’Connor, C. Heinrich and M. Podolskij (2019): On limit theory for functionals of stationary increments Lévy driven moving averages. Electronic Journal of Probability 24(79), 1–42. 

M.M. Ljungdahl and M. Podolskij (2019): A note on parametric estimation of Lévy moving average processes. Stochastic Models, Statistics and Their Applications, eds. A. Steland, E. Rafajlowicz and O. Okhrin, Springer Proceedings in Mathematics and Statistics. 

T. Huschto, M. Podolskij and S. Sager (2019): The asymptotic error of chaos expansion approximations for stochastic differential equations. Modern Stochastics: Theory and Applications 6(2), 145–165. 

M.M. Ljungdahl and M. Podolskij (2018): A limit theorem for a class of stationary increments Lévy moving average process with multiple singularities. Modern Stochastics: Theory and Applications 5(3), 297–316. 

J. Jacod and M. Podolskij (2018): On the minimal number of driving Lévy motions in a multivariate price model. Journal of Applied Probability 55(3), 823–833. 

M. Podolskij and M. Rosenbaum (2018): Comment on: Limit of random measures associated with the increments of a Brownian semimartingale. Asymptotic behavior of local times related statistics for fractional Brownian motion. Journal of Financial Econometrics 16(4), 588–598. 

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

K. Christensen, U. Hounyo and M. Podolskij (2018): Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach. Journal of Econometrics 205(2), 336–362. 

A. Basse-O’Connor, R. Lachi`eze-Rey and M. Podolskij (2017): Power variation for a class of stationary increments Lévy driven moving averages. Annals of Probability, 45(6B), 4477–4528. 

J. Lebovits and M. Podolskij (2017): Estimation of the global regularity of a multifractional Brownian motion. Electronic Journal of Statistics 11(1), 78–98. 

K. Christensen, M. Podolskij, N. Thamrongrat and B. Veliyev (2017): Inference from high-frequency data: A subsampling approach. Journal of Econometrics 197(2), 245–272. 

T. Fissler and M. Podolskij (2017): Testing the maximal rank of the volatility process for continuous diffusions observed with noise. Bernoulli 23(4B), 3021–3066. 

M. Podolskij, C. Schmidt and M. Vetter (2017): On U- and V-statistics for discontinuous Itô semimartingales. Annales de l’Institut Henri Poincar´e 53(3), 1007–1050. 

M. Podolskij, B. Veliyev and N. Yoshida (2017): Edgeworth expansion for the pre-averaging estimator. Stochastic Processes and Their Applications 127, 3558–3595. 

A. Basse-O’Connor and M. Podolskij (2017): On critical cases in limit theory for stationary increments Lévy driven moving averages. Festschrift for Bernt Øksendal, Stochastics 81(1), 360–383. 

M. Podolskij and N. Thamrongrat (2016): A weak limit theorem for numerical approximation of Brownian semi-stationary processes. Stochastics of Environmental and Financial Economics, eds. F.E. Benth and G. Di Nunno, Springer Proceedings in Mathematics and Statistics. 

M. Podolskij and N. Yoshida (2016): Edgeworth expansion for functionals of continuous diffusion processes. Annals of Applied Probability 26(6), 3415–3455. 

M. Duembrgen and M. Podolskij (2015): High-frequency asymptotics for path-dependent functionals of Itô semimartingales. Stochastic Processes and Their Applications 125(4), 1195–1217. 

J.M. Corcuera, D. Nualart and M. Podolskij (2015): Asymptotics of weighted random sums. Communications in Applied and Industrial Mathematics. 

M. Podolskij (2015): Ambit fields: survey and new challenges. XI Symposium of Probability and Stochastic Processes, eds. R.H. Mena, J.C. Pardo, V. Rivero and G. Uribe Bravo, Progress in Probability, Springer. 

M. Podolskij, C. Schmidt and J. Fasciati Ziegel (2014): Limit theorems for nondegenerate U-statistics of continuous semimartingales. Annals of Applied Probability 24(6), 2491–2526. 

K. Christensen, R. Oomen and M. Podolskij (2014): Fact or friction: Jumps at ultra-high frequency. Journal of Financial Economics 114(3), 576–599. 

K. Gärtner and M. Podolskij (2014): On non-standard limits of Brownian semistationary processes. Stochastic Processes and Their Applications 125(2), 653–677. 

O. E. Barndorff-Nielsen, J. M. Corcuera and M. Podolskij (2013): Limit theorems for functionals of higher order differences of Brownian semi-stationary processes. In ”Prokhorov and Contemporary Probability Theory”, eds. A.N. Shiryaev, S.R.S. Varadhan and E.L. Presman, Springer. 

N. Hautsch and M. Podolskij (2013): Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: theory, implementation, and empirical evidence. Journal of Business and Economic Statistics 31(2), 165–183. 

M. Podolskij and K. Wasmuth (2013): Goodness-of-fit testing for fractional diffusions. Statistical Inference for Stochastic Processes 16(2), 147-159. 

J.M. Corcuera, E. Hedevang, M. Pakkanen and M. Podolskij (2013): Asymptotic theory for Brownian semi-stationary processes with application to turbulence. Stochastic Processes and Their Applications 123, 2552-2574. 

K. Christensen, M. Podolskij and M. Vetter (2013): On covariation estimation for multivariate continuous Ito semimartingales with noise in non-synchronous observation schemes. Journal of Multivariate Analysis 120, 59-84. 

J. Jacod and M. Podolskij (2013): A test for the rank of the volatility process: the random perturbation approach. Annals of Statistics, 41(5), 2391–2427. 

K. Christensen and M. Podolskij (2012): Asymptotic theory of range-based multipower variation. Journal of Financial Econometrics 10(3), 417–456. 

O. E. Barndorff-Nielsen, J. M. Corcuera and M. Podolskij (2011): Multipower variation for Brownian semi-stationary processes. Bernoulli 17(4), 1159–1194. 

M. Podolskij and M. Rosenbaum (2011): Testing the local volatility assumption: a statistical approach. Annals of Finance 8(1), 31–48. 

M. Podolskij and M. Vetter (2010): Understanding limit theorems for semimartingales: a short survey. Statistica Nederlandica 64(3), 329–351. 

I. Nourdin, G. Peccati and M. Podolskij (2010): Quantitative Breuer-Major theorems. Stochastic Processes and Their Applications 121, 793–812. 

J. Jacod, M. Podolskij and M. Vetter (2010): Limit theorems for moving averages of discretized processes plus noise. Annals of Statistics, 38(3), 1478–1545. 

M. Podolskij and D. Ziggel (2010): New tests for jumps in semimartingale models. Statistical Inference for Stochastic Processes 13(1), 15–41. 

M. Podolskij (2010): Semimartingales. Encyclopedia of Quantitative Finance, eds. R. Cont. 

K. Christensen, R. Oomen and M. Podolskij (2010): Realised quantile-based estimation of the integrated variance. Journal of Econometrics 159, 74–98. 

K. Christensen, S. Kinnebrock and M. Podolskij (2010): Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data. Journal of Econometrics 159, 116–133. 

J. Jacod, Y. Li, P. Mykland, M. Podolskij and M. Vetter (2009): Microstructure noise in the continuous case: the pre-averaging approach. Stochastic Processes and Their Applications 119, 2249–2276. 

K. Christensen, M. Podolskij and M. Vetter (2009): Bias-correcting the realised range-based variance in the presence of market microstructure noise. Finance and Stochastics 13(2), 239–268. 

M. Podolskij and M. Vetter (2009): Estimation of volatility functionals in the simultaneous presence of microstructure noise and jumps. Bernoulli 15(3), 634–658. 

M. Podolskij and M. Vetter (2009): Bipower-type estimation in a noisy diffusion setting. Stochastic Processes and Their Applications 119, 2803–2831. 

O. E. Barndorff-Nielsen, J. M. Corcuera, M. Podolskij and J. H. C. Woerner (2009): Bipower variation for Gaussian processes with stationary increments. Journal of Applied Probability 46, 132–150. 

O. E. Barndorff-Nielsen, J. M. Corcuera and M. Podolskij (2009): Power variation for Gaussian processes with stationary increments. Stochastic Processes and Their Applications 119, 1845–1865. 

S. Kinnebrock and M. Podolskij (2008): A note on the central limit theorem for bipower variation of general functions. Stochastic Processes and Their Applications 118, 1056–1070. 

H. Dette and M. Podolskij (2008): Testing the parametric form of the volatility in continuous time diffusion models - an empirical process approach. Journal of Econometrics 143, 56–73. 

K. Christensen and M. Podolskij (2007): Realised range-based estimation of integrated variance. Journal of Econometrics 141, 323–349. 

O. E. Barndorff-Nielsen, S. E. Graversen, J. Jacod, M. Podolskij and N. Shephard (2006): A central limit theorem for realised power and bipower variations of continuous semimartingales. In From Stochastic Analysis to Mathematical Finance, Festschrift for Albert Shiryaev, Springer. 

H. Dette, M. Podolskij and M. Vetter (2006): Estimation of integrated volatility in continuous time financial models with applications to goodness-of-fit testing. Scandinavian Journal of Statistics 33, 259–278. 

Review of Mod-ϕ convergence. Normality zones and precise deviations by V. Féray, P.-L. Méliot and A. Nikehgbali. Newsletter 107, European Mathematical Society. 

Review of How to Cheat with Statistics — and Get Away with It by Gunter Meissner. Quantitative Finance.