MARKET RISK MODEL IDENTIFICATION AND VALIDATION USING NOVEL STATISTICAL, PROBABILISTIC, AND MACHINE LEARNING TOOLS
- Model identification/validation based on conditional quantile moments analysis
- Novel risk and performance quantification methods
- Long-run stochastic equilibrium analysis in finance
- H. Woszczek, A. Chechkin, A. Wyłomańska: Scaled Brownian motion with random anomalous diffusion exponent, Communications in Nonlinear Science and Numerical Simulation 140(1), 108388, 2025
- A. Pacheco-Pozo, M. Balcerek, A. Wyłomańska, K. Burnecki, I. M. Sokolov, D. Krapf: Langevin equation in heterogeneous landscapes: how to choose the interpretation, Phys. Rev. Lett. 133, 067102, 2024
- A. M. Sathe, N. S. Upadhye, A. Wyłomańska: Forecasting multidimensional autoregressive time series model with symmetric alpha-stable noise using artificial neural networks, Statistical Methods & Applications 33, 783–805, 2024
- K. Pączek, D. Jelito, M. Pitera, A. Wyłomańska: Goodness-of-fit tests for the one-sided Levy distribution based on quantile conditional moments, Journal of Applied Statistics 1–24, 2024, https://doi.org/10.1080/02664763.2024.2340592
- K. Pączek, D. Jelito, M. Pitera, A. Wyłomańska: Estimation of stability index for symmetric alpha-stable distribution using quantile conditional variance ratios, TEST 33, 297–334, 2024
- A. Grzesiek, J. Gajda, S. Thapa, A. Wyłomańska: Distinguishing between fractional Brownian motion with random and constant Hurst exponent using sample autocovariance-based statistics, Chaos 34, 043154, 2024
- J. Janczura, A. Puć, Ł. Bielak, A. Wyłomańska: Product of bi-dimensional VAR(1) model components. An application to the cost of electricity load prediction errors Statistics & Risk Modeling 41 (1/2) 1-26, 2024
- M. Balcerek, A. Wyłomańska, K. Burnecki, R. Metzler, D. Krapft: Modelling intermittent anomalous diffusion with switching fractional Brownian motion, New J. Phys. 25 103031, 2023
- H. Woszczek, A. Wyłomańska: Autoregressive model with double Pareto distributed noise, Mathematica Applicanda 51(1), 121-141, 2023
- W. Wang, M. Balcerek, K. Burnecki, A. V. Chechkin, S.Janusonis, J. Ślęzak, T. Vojta, A. Wyłomańska, and R. Metzler: Memory-multi-fractional Brownian motion with continuous correlations, Phys. Rev. Research 5, L032025, 2023
- K. Maraj-Zygmąt, A. Grzesiek, G. Sikora, J. Gajda, A. Wyłomańska: Testing of two-dimensional Gaussian processes by sample cross-covariance function, Chaos 33, 073135, 2023
- M. Dhull, A. Kumar, A. Wyłomańska: The expectation-maximization algorithm for autoregressive models with normal inverse Gaussian innovations, Communications in Statistics - Simulation and Computation, 1-21, 2023, https://doi.org/10.1080/03610918.2023.2186334
- J. Gajda, A. Grzesiek, A. Wyłomańska: Ornstein - Uhlenbeck process driven by alpha-stable process and its Gamma subordination, Methodology and Computing in Applied Probability 25,9, 2023
- K. Maraj-Zygmąt, G. Sikora, M. Pitera, A. Wyłomańska: Goodness-of-fit test for stochastic processes using even empirical moments statistic, Chaos 33, 013128, 2023
- A. M. Sathe, N. S. Upadhye, A. Wyłomańska: Forecasting of symmetric alpha-stable autoregressive models by time series approach supported by artificial neural networks, Journal of Computational and Applied Mathematics 425, 115051, 2023
- J. Adamska, L. Bielak, J. Janczura, A. Wyłomańska: From Multi- to Univariate: A Product Random Variable with an Application to Electricity Market Transactions: Pareto and Student’s t-Distribution Case, Mathematics 10(18), 3371, 2021
- M. Balcerek, K. Burnecki, S. Thapa, A. Wyłomańska, A. Chechkin: Fractional Brownian motion with random Hurst exponent: accelerating diffusion and persistence transitions, Chaos 32, 093114, 2022
- D. Szarek, I. Jabłoński, D. Krapf, A. Wyłomańska: Multifractional Brownian motion characterization based on Hurst exponent estimation and statistical learning, Chaos 32, 083148, 2022
- D. Szarek, K. Maraj-Zygmąt, G. Sikora, D. Kraft, A. Wyłomańska: Statistical test for anomalous diffusion based on empirical anomaly measure for Gaussian processes, Computational Statistics & Data Analysis 168, 107401, 2022
- Ł. Bielak, A. Grzesiek, J. Janczura, A. Wyłomańska: Market risk factors analysis for an international mining company. Multi-dimensional heavy-tailed-based modelling, Resources Policy 74, 102308, 2021
- A. Grzesiek, M. Mrozinska, P. Giri, S. Sundar, A. Wyłomańska: The covariation-based Yule-Walker method for multidimensional autoregressive time series with alpha-stable distributed noise , Int J Adv Eng Sci Appl Math 13, 13, 394–414, 2021
- P. Giri, S. Sundar, A. Wyłomańska: Fractional lower order covariance (FLOC) based estimation for multidimensional PAR(1) model with alpha−stable noise, Int J Adv Eng Sci Appl Math 13, 215–235, 2021
- M. Markiewicz, A. Wyłomańska: Time series forecasting - problem of heavy-tailed distributed noise, Int J Adv Eng Sci Appl Math 13, 248–256, 2021
- K. Maraj, D. Szarek, G. Sikora, A. Wyłomańska: Time averaged mean squared displacements ratio test for Gaussian processes with unknown diffusion coefficient, Chaos 31, 073120, 2021
- M. Balcerek, K. Burnecki, G. Sikora, A. Wyłomańska: Discriminating Gaussian processes via quadratic form statistics, Chaos 31, 063101, 2021
Grant no.: 2020/37/B/HS4/00120 (OPUS)
Funding agency: National Science Centre (NCN), Poland
Funding period: 14.01.2021-13.01.2025
Partners: Jagiellonian University (M. Pitera), Polish Academy of Science (Ł. Stettner), Wrocław University of Science and Technology (A. Wyłomańska)
Total budget: 396 732 PLN
Tasks
Selected publications
Funding agency: National Science Centre (NCN), Poland
Funding period: 14.01.2021-13.01.2025
Partners: Jagiellonian University (M. Pitera), Polish Academy of Science (Ł. Stettner), Wrocław University of Science and Technology (A. Wyłomańska)
Total budget: 396 732 PLN
Tasks
Selected publications
NonGaussMech - NEW METHODS OF PROCESSING NON-STATIONARY SIGNALS (IDENTIFICATION, SEGMENTATION, EXTRACTION, MODELING) WITH NON-GAUSSIAN CHARACTERISTICS FOR THE PURPOSE OF MONITORING COMPLEX MECHANICAL STRUCTURES
- Radosław Zimroz
- Agnieszka Wyłomańska
- Mateusz Gabor (Ph.D. student)
- Katarzyna Skowronek (Ph.D. student)
- Wojciech Żuławiński (Ph.D. student)
- Daniel Kuzio (Ph.D. student)
- Impulsive noise modeling and nonstationary operational condition parametrisation
- Hidden Cyclicity/Periodicity detection (in case of non-existing second-order statistics)
- Multidimensional data processing algorithms for impulsive sources separation and signal of interest extraction
- D. Kuzio, R. Zimroz, A. Wyłomańska: A procedure for assessing of machine health index data prediction quality, Measurement 240, 116040, 2025
- J. Janczura, W. Żuławiński, H. Shiri, T. Barszcz, R. Zimroz, A. Wyłomańska: Prediction of machine state for non-Gaussian degradation model using Hidden Markov Model approach, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2025: 27(2), 2025
- J. Witulska, A. Zaleska, N. Kremzer-Osiadacz, A. Wyłomańska, I. Jabłoński: Robust variance estimators in application to segmentation of measurement data distorted by impulsive and non-Gaussian noise, Measurement 239, 115472, 2025
- W. Żuławiński, A. Wyłomańska: Errors-in-variables-based methodology of estimation and testing for infinite-variance periodic autoregressive models with additive noise, 32nd European Signal Processing Conference (EUSIPCO), Lyon, France, pp. 1087-1091, 2024
- K. Skowronek, R. Zimroz, A. Wyłomańska: Testing for finite variance with applications to vibration signals from rotating machines, J. Math. Industry 14(19), 2024
- K. Skowronek, M. Arendarczyk, R. Zimroz, A. Wyłomańska: Modified Greenwood statistic and its application for statistical testing, Journal of Computational and Applied Mathematics 452, 116122, 2024
- W. Żuławiński, J. Antoni, R, Zimroz, A. Wyłomańska: Robust coherent and incoherent statistics for detection of hidden periodicity in models with non-Gaussian additive noise, EURASIP J. Adv. Signal Process. 71, 2024
- W. Żuławiński, J. Antoni, R. Zimroz, A. Wyłomańska: Applications of robust statistics for cyclostationarity detection in non-Gaussian signals for local damage detection in bearings, Mechanical Systems and Signal Processing 214, 111367, 2024
- A. Michalak, R. Zdunek, R. Zimroz, A. Wylomanska: Influence of alpha-stable noise on the effectiveness of non-negative matrix factorization – simulations and real data analysis, Electronics 13(5), 829, 2024
- M. Gabor, R. Zdunek, R. Zimroz, A. Wyłomańska: Bearing damage detection with orthogonal and non-negative low-rank feature extraction, IEEE Transactions on Industrial Informatics 20(2), 2944-2955, 2024
- M. Gabor, R. Zdunek, R. Zimroz, A. Wyłomańska: Non-negative matrix underapproximation as optimal frequency band selector, In: IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society. [Danvers, MA]: IEEE, 1-6, 2023
- W. Żuławiński, A. Wyłomańska: Empirical study of periodic autoregressive models with additive noise - estimation and testing, Communications in Statistics - Simulation and Computation, 1-26, 2023, doi: 10.1080/03610918.2023.2286217
- D. Kuzio, R. Zimroz, A. Wyłomańska: Identification of fault frequency variation in the envelope spectrum in the vibration-based local damage detection in changing load/speed conditions, Measurement 218(15), 113148, 2023
- K. Skowronek, T. Barszcz, J. Antoni, R. Zimroz, A. Wyłomańska: Assessment of background noise properties in time and time-frequency domains in the context of vibration-based local damage detection in real environment, Mechanical Systems and Signal Processing 199(15), 110465, 2023
- M.Gabor, R. Zdunek, R. Zimroz, J. Wodecki, A. Wyłomańska: Non-negative tensor factorization for vibration-based local damage detection, Mechanical Systems and Signal Processing 198, 110430, 2023
- W. Żuławiński, R. Zimroz, A. Wyłomańska: Yule-Walker-Based Approaches for Estimation of Noise-Corrupted Periodic Autoregressive Model - Finite- and Infinite-Variance Cases, 31st European Signal Processing Conference (EUSIPCO), Helsinki, Finland, pp. 1978-1982, 2023
- W. Żuławiński, A. Grzesiek, R. Zimroz, A. Wyłomańska: Identification and validation of periodic autoregressive model with additive noise: finite-variance case, Journal of Computational and Applied Mathematics 427, 115131, 2023
- P. Giri, A. Grzesiek, W. Żuławiński, S. Sundar, A. Wyłomańska: The modified Yule-Walker method for multidimensional infinite-variance periodic autoregressive model of order 1, Journal of the Korean Statistical Society, 2022
Grant no.: 2021/40/Q/ST8/00024 (SHENG)
Funding agency: National Science Centre (NCN), Poland
Funding period: 1.02.2022-31.01.2025
Partners: Tsinghua University, Beijing (China); Faculty of Pure and Applied Mathematics (WMat) WUST (Poland); Faculty of Geoengineering, Mining and Geology (WGGG) WUST (Poland)
Total budget: 414 842 EUR
A key personnel consists of: prof. Fulei Chu (Tsinghua University), prof. Agnieszka Wyłomańska (WMat), prof. Radoslaw Zimroz (WGGG/KG/DMC).
Research team (WUST)
Tasks
Selected publications
Funding agency: National Science Centre (NCN), Poland
Funding period: 1.02.2022-31.01.2025
Partners: Tsinghua University, Beijing (China); Faculty of Pure and Applied Mathematics (WMat) WUST (Poland); Faculty of Geoengineering, Mining and Geology (WGGG) WUST (Poland)
Total budget: 414 842 EUR
A key personnel consists of: prof. Fulei Chu (Tsinghua University), prof. Agnieszka Wyłomańska (WMat), prof. Radoslaw Zimroz (WGGG/KG/DMC).
Research team (WUST)
Tasks
Selected publications
A UNIVERSAL DIAGNOSTIC AND PROGNOSTIC MODULE FOR CONDITION MONITORING SYSTEMS
OF COMPLEX MECHANICAL STRUCTURES OPERATING IN THE PRESENCE OF NON-GAUSSIAN DISTURBANCES AND VARIABLE OPERATING CONDITIONS
Grant no.: OIR.01.01.01-00-0350/21 (Szybka Ścieżka)
Funding agency: National Centre for Research and Development (NCBiR), Poland
Funding period: 1.10.2021-31.12.2023
Partners: Faculty of Pure and Applied Mathematics (WMat) WUST, Faculty of Geoengineering, Mining and Geology (WGGG) WUST, AMC Tech
Budget for WUST: 1 926 000 PLN (c.a. 421 500 Euro)
A key personnel consists of: prof. Agnieszka Wyłomańska (WMat), prof. Tomasz Barszcz (AMC Tech), prof. Radoslaw Zimroz (WGGG/KG/DMC).
See the web page of the project
Funding agency: National Centre for Research and Development (NCBiR), Poland
Funding period: 1.10.2021-31.12.2023
Partners: Faculty of Pure and Applied Mathematics (WMat) WUST, Faculty of Geoengineering, Mining and Geology (WGGG) WUST, AMC Tech
Budget for WUST: 1 926 000 PLN (c.a. 421 500 Euro)
A key personnel consists of: prof. Agnieszka Wyłomańska (WMat), prof. Tomasz Barszcz (AMC Tech), prof. Radoslaw Zimroz (WGGG/KG/DMC).
See the web page of the project
ANOMALOUS DIFFUSION PROCESSES
AND THEIR APPLICATION TO REAL DATA MODELLING
- Agnieszka Wyłomańska (leader of the project, principal investigator)
- Janusz Gajda (investigator)
- Aleksandra Grzesiek (Ph.D. student)
- Piotr Kruczek (Ph.D. student)
- Rafał Połoczański (Ph.D. student)
- Katarzyna Maraj (student)
- Wojciech Żuławiński (student)
- Aleksei Chechkin (international collaborator, Potsdam University, Germany)
- Arun Kumar (international collaborator, IIT Ropar, India)
- Diego Krapf (international collaborator, Colorado State University, USA)
- S. Sundar (international collaborator, IIT Madras, India)
- Samudrajit Thapa (international collaborator, Potsdam University, Germany)
- Prashant Giri (international collaborator, IIT Madras, India)
- Anna Panorska (international collaborator, University of Nevada, USA)
- Tomasz Kozubowski (international collaborator, University of Nevada, USA)
- Holger Kantz (international collaborator, Max Planck Institute, Dresden, Germany)
- Marc Hoell (international collaborator, Max Planck Institute, Dresden, Germany)
- Denis Grebenkov (international collaborator, Ecole Polytechnique, France)
- Yann Lanoiselee (international collaborator, Ecole Polytechnique, France)
- Analysis of subordinated processes with stationary increments
- Analysis of subordinated processes with inverse subordinators
- Analysis of long memory processes
- A. Grzesiek, M. Teuerle, G. Sikora, A. Wyłomańska: Spatio-temporal dependence measures for alpha-stable bivariate AR(1) models , Journal of Time Series Analysis 2020, https://doi.org/10.1111/jtsa.12517
- A. Grzesiek, M. Teuerle, A. Wyłomańska:Cross-codifference for bidimensional VAR(1) time series with infinite variance, Communications in Statistics - Simulation and Computation 2020, https://doi.org/10.1080/03610918.2019.1670840
- A. Grzesiek, A. Wyłomańska: Subordinated Processes with Infinite Variance, In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 111-135, Springer, Cham, 2020
- P. Poczynek, P. Kruczek, A. Wyłomańska: Ornstein-Uhlenbeck Process Delayed by Gamma Subordinator , In: Chaari F., Leskow J., Zimroz R., Wyłomańska A., Dudek A. (eds) Cyclostationarity: Theory and Methods – IV. CSTA 2017. Applied Condition Monitoring, vol 16, 147-165, Springer, Cham, 2020
- P. Kruczek, W. Żuławiński, P. Pagacz, A. Wyłomańska: Fractional lower order covariance based-estimator for Ornstein-Uhlenbeck process with stable distribution, Mathematica Applicanda 47, 259-292, 2019
- M. Szmigiel, A. Grzesiek, A. Wyłomańska, H. Kasprzak: Stable distribution in application to fixational eye movement description, Optica Applicata 49 (2), 365-377, 2019
- A. Kumar, A. Maheshwari, A. Wyłomańska: Linnik Levy Process and Its Generalization , Physica A 529, 121539, 2019
- G. Sikora, Ł. Bielak, A. Michalak, P. Miśta, A. Wyłomańska: Stochastic modelling of currency exchange rates with novel validation techniques, Physica A 523, 1202-1215, 2019
- A. Kumar, A. Wyłomańska, R. Połoczański, J. Gajda: Fractional Brownian motion delayed by tempered and inverse tempered stable subordinators, Methodology and Computing in Applied Probability 21(1), 185-202, 2019
- A. Grzesiek, S. Sundar, A. Wyłomańska: Fractional lower order covariance-based estimator for bidimensional AR(1) model with stable distribution, International Journal of Advances in Engineering Sciences and Applied Mathematics 11(3), 217-229, 2019
- J. Gajda Janusz, A. Wyłomańska, A. Kumar: Fractional Levy stable motion time-changed by gamma subordinator, Communications in Statistics - Theory and Methods 48, (24), 5953–5968, 2019
- A. Kumar, N. S. Upadhye, A. Wyłomańska, J. Gajda: Tempered Mittag-Leffler Levy Process, Communications in Statistics - Theory and Methods 48 (2), 396–411, 2019
- Y. Lanoiselee, D.S. Grebenkov, G. Sikora, A. Grzesiek, A. Wylomanska: Optimal parameters for anomalous diffusion exponent estimation from noisy data , Phys. Rev. E 98, 062139, 2018
- J. Gajda, A. Wyłomańska, H. Kantz, A. Chechkin, G. Sikora:Large deviations of time-averaged statistics for Gaussian processes , Statistics and Probability Letters 143, 47-55, 2018
- G. Sikora, A. Wyłomańska, D. Krapf:Recurrence statistics for anomalous diffusion regime change detection , Computational Statistics & Data Analysis 128, 380-394, 2018
- P. Kruczek, M. Polak, A. Wyłomańska, W. Kawalec, R. Zimroz: Application of compound Poisson process for modelling of ore flow in a belt conveyor system with cyclic loading,Journal International Journal of Mining, Reclamation and Environment 32(6), 376-391, 2018
- A. Grzesiek, J. Gajda, A. Wyłomańska, S. Sundar: Discriminating between scaled and fractional Brownian motion via p-variation statistics, International Journal of Advances in Engineering Sciences and Applied Mathematics 10(1), 9-14, 2018
- D. Kucharczyk, A. Wyłomańska, G. Sikora: Variance change point detection for fractional Brownian motion based on the likelihood ratio test, Physica A 490, 439-450, 2018
- G. Sikora, A. Wyłomańska, J. Gajda, L. Sole, E. J. Akin, M. M. Tamkun, D. Krapf: Elucidating distinct ion channel populations on the surface of hippocampal neurons via single-particle tracking recurrence analysis, Phys. Rev. E 96, 062404, 2017
- G. Sikora, M. Teuerle, A. Wyłomańska, D. Grebenkov: Statistical properties of the anomalous scaling exponent estimator based on time averaged mean square displacement, Phys. Rev. E 96, 022132, 2017
- A. Kumar, A. Wyłomańska, J. Gajda: Stable Levy motion with inverse Gaussian subordinator, Physica A 482, 486–500, 2017
- G. Sikora, K. Burnecki, A. Wyłomańska: Mean-squared displacement statistical test for fractional Brownian motion, Phys. Rev. E 95, 032110, 2017
- A. Kumar, A. Wyłomańska, J. Gajda: Generalized fractional Laplace motion, Statistics and Probability Letters 124, 101-109, 2017
- M. Jabłońska, M. Teuerle, A. Wyłomańska: Bivariate sub-Gaussian model for stock indices returns, Physica A 486(15), 628–637, 2017