Publications

These publications have received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 318984 -RARE‌ 

 

 

In no particular order:

1. X. Zhou and O. Menoukeu-Pamen (2017). Efficient Piecewise Trees for the Generalized Skew Vasicek Model with Discontinuous Drift. International Journal of Theoretical and Applied Finance. In press

2. O. Menoukeu-Pamen, R. Momeya (2017). Maximum Principle for Markov Regime-Switching Forward-Backward Stochastic Differential Games and Applications. Mathematical Methods of Operations Research, doi:10.1007/s00186-017-0574-4

3. L. Bai, K. Debicki, E. Hashorva, L.  Luo (2017). On Generalised Piterbarg Constants. Methodology and Computing in Applied Probability, doi:10.1007/s11009-016-9537-0

4. I. Czarna, Y. Li, Z. Palmowski, C. Zhao (2017). The joint distribution of the Parisian ruin time and the number of claims until Parisian ruin in the classical risk model, Journal of Computational and Applied Mathematics 313, 499-514, doi:10.1016/j.cam.2016.09.045

5. I. Czarna, Z. Palmowski, P. Swiatek (2017). Binomial discrete time ruin probability with Parisian delay, Scandinavian Actuarial Journal, doi:10.1080/03461238.2016.1261734

6. E. Marciniak, Z. Palmowski (2017). On the Optimal Dividend Problem in the Dual Models with Surplus-Dependent Premiums, Journal of Optimization Theory and Applications, doi:10.1007/s10957-016-1050-7

7. E. Hashorva, G. Ratovomirija, M. Tamraz (2017). Some New Dependence Models derived from Multivariate Collective Models in Insurance Applications. Scandinavian Actuarial Journal, doi:10.1080/03461238.2016.1243574

8. M. Cadena, M. Kratz, E. Omey (2017). On the order of functions at infinity. Journal of Mathematical Analysis and Applications.

9. K. Debicki,  E. Hashorva, L. Ji , C. Ling (2017). Comparison Inequalities for Order Statistics of Gaussian Arrays. Latin American Journal of Probability and Mathematical Statistics.

10. E. Baurdoux, Z. Palmowski, M. Pistorius (2017). On future drawdowns of Lévy processes, Stochastic Processes and their Applications, doi:10.1016/j.spa.2016.12.008

11. J. Grimm, E. Metin Elci, Z. Zhou, T. M. Garoni, Y. Deng (2017). Geometric explanation of anomalous finite-size scaling in high dimensions Phys. Rev. Lett. In Press. 

12. Z. Sun, J. Guo, X. Zhang (2017). Maximum Principle for Markov Regime-Switching Forward–Backward Stochastic Control System with Jumps and Relation to Dynamic Programming, Springer Science+Business Media New York 2017, doi:10.1007/s10957-017-1068-5

13. X. Liang, C. Tsai, Y. Lu (2016). Valuing guaranteed equity-linked contracts under piecewise constant forces of mortality, Insurance: Mathematics and Economics 70 (2016) 150–161, doi:10.1016/j.insmatheco.2016.06.004

14. X. Liang, L. Bai (2016). Minimizing expected time to reach a given capital level before ruin, Journal of Industrial and Management Optimization, 13(2):18-18, doi:10.3934/jimo.2017018 

15. Z. Sun, X. Zhang, J. Guo (2016). A stochastic maximum principle for processes driven by G-Brownian motion and applications to finance, Optim. Control Appl. Meth. 2016; 1–15, doi:10.1002/oca.2299

16. A. Collevecchio, T. M. Garoni, T. Hyndman, D. Tokarev  (2016). The worm process for the Ising model is rapidly mixing J. Stat. Phys. 164, 1082-1102, doi:10.1007/s10955-016-1572-2 

17. R. Kutadinata, W. Moase, C. Manzie, L. Zhang, T. M. Garoni (2016). Enhancing the performance of existing urban traffic light control through extremum-seeking, Transportation Research Part C Emerging Technologies 62:1-20, doi:10.1016/j.trc.2015.10.016

18. X. Liang, J. Guo (2016). Optimal investment, consumption, and life insurance in an incomplete market, Communications in Statistics - Theory and Methods, 45:13, 3884-3903, doi:10.1080/03610926.2014.911907

19. M. Kratz (2016). On the estimation of the distribution of aggregated heavy tailed risks. Application to risk measure. In Extreme events in finance. A Handbook of Extreme Value Theory and its Applications, Chap.11. Ed. F. Longin. Wiley, doi:10.1002/9781118650318.ch11

20. H. Godinez-Olivares, C. Boado-Penas, S. Haberman (2016). Optimal strategies for pay-as-you-go pension finance: A sustainability framework. Insurance: Mathematics and Economics 69, 117-126, doi:10.1016/j.insmatheco.2016.05.001

21. O. Menoukeu-Pamen and D. Taguchi (2016). Strong rate of convergence for the Euler–Maruyama approximation of SDEs with Holder continuous drift coefficient. Stochastic Processes and Their Applications, doi:10.1016/j.spa.2016.11.008

22. K. Dȩbicki, E. Hashorva, P. Liu (2016). Ruin probabilities and passage times of Gamma-reflected Gaussian processes with stationary increments,

23. C. Constantinescu, S. Dai, W. Ni, Z. Palmowski (2016). Ruin probabilities with dependence on the number of claims within a fixed time window, Risks 4(2), doi:10.3390/risks4020017

24. S. Kapodistria, Z. Palmowski (2016). A matrix geometric approach for random walks in the quadrant, Proceedings of the Ninth International Conference on Matrix-Analytic Methods in Stochastic Models, 157-163.

25. Z. Palmowski (2016), Problem optymalizacyjny de Finettiego dla procesów Lévy'ego, Wiadomości matematyczne 52(1), 1-19.

26. M. Kratz, Y. Lok, A. McNeil (2016). A multinomial test to discriminate between models. ASTIN 2016 Proceedings, Lisbon.

27. P. Albin, E. Hashorva, L. Ji , C. Ling (2016). Extremes and limit theorems for difference of chi-type processes. ESAIM: Probability and Statistics, 20, 349-366, doi:10.1051/ps/2016018

28. E. Hashorva, C. Ling (2016). Maxima of skew elliptical triangular arrays. Communications in Statistics - Theory and Methods, 45, 3692-3705, doi:10.1080/03610926.2014.906613

29. E. Hashorva, Z. Peng, Z. Weng (2016). Higher-order expansions of distributions of maxima in a Hüsler-Reiss model. Methodology and Computing in Applied Probability, 18, 181-196, doi:10.1007/s11009-014-9407-6

30. K. Dȩbicki, P. Liu (2016). Extremes of stationary Gaussian storage models, Extremes, doi:10.1007/s10687-016-0240-x

31. V. Asimit, E. Hashorva, D. Kortschak (2016). Aggregation of randomly weighted large risks. IMA Journal of Management Mathematics, doi:10.1093/imaman/dpv020

32. M. Cadena, and M. Kratz (2016). New results for tails of probability distributions according to their asymptotic decay. Stat. Probab. Letters 109, 178-183, doi:10.1016/j.spl.2015.10.018

33. K. Debicki, E. Hashorva, L. Ji (2016). On Parisian ruin over a finite-time horizon. Science China Mathematics, 59(3), 557-572, doi:10.1007/s11425-015-5073-6

34. E. Hashorva, L. Ji (2016). Extremes of alpha(t)-locally stationary Gaussian random fields. Transactions of the American Math Soc., 368(1), 1-26.

35. M. Kratz, W. Nagel (2016). On the capacity functional of excursion sets of Gaussian random fields on R^2. Adv. Appl. Probab. 48:3  http://projecteuclid.org/euclid.aap/1474296311

36. E. Marciniak, Z. Palmowski (2016). On the optimal dividend problem for insurance risk models with surplus-dependent premiums, Journal of Optimization Theory and Applications 168, 723–-742, doi:10.1007/s10957-015-0755-3

37. K. Debicki, E. Hashorva, L. Ji (2016). Extremes of a class of non-homogeneous Gaussian random fields. Annals of Probability. Volume 44, Number 2 (2016), 984-1012, doi:10.1214/14-AOP994

38. V. I. Piterbarg (2016). High extrema of Gaussian chaos processes. Extremes, doi:10.1007/s10687-016-0239-3

39. V. I. Piterbarg (2016). Large extremes of Gaussian chaos processes. Doklady Mathematics, doi:10.1134/S1064562416020058

40. V. I. Piterbarg, A. Zhdanov (2015). On probability of high extremes for product of two independent gaussian stationary processes. Extremes. 18, no.1, 99–108. Doi:10.1007/s10687-014-0205-x

41. C. Vidal-Meliá, C. Boado-Penas, F. Navarro-Cabo (2015). “Notional Defined Contribution Pension Systems: Why does only Sweden distribute the Survivor Dividend”. Journal of Economic Policy Reform, doi:10.1080/17487870.2015.1028547

42. Z. Michna, Z. Palmowski, M. Pistorius (2015). The distribution of the supremum for spectrally asymmetric Lévy processes, Electronic Communications in Probability 20, doi:10.1214/ECP.v20-2999

43. X. Liang, J. Guo (2015). Optimal life insurance purchase and consumption/investment under mean-reverting returns (in Chinese). Sci Sin Math, 2015, 45: 623-638, doi:10.1360/N012015-00054

44. A. Mazur, V. I. Piterbarg (2015). Gaussian copula time series with heavy tails and strong time dependence.  Moscow University Mathematics Bulletin 70, no. 5. ,P. 197–201, doi:10.3103/S0027132215050010

45. E. Kremena, V. I. Piterbarg, J. Hüsler (2015). On shape of trajectories of Gaussian processes having large massive excursions. II. Theory of Probability and its Applications. 60, no 3, 613-621, doi:10.1137/S0040585X97T98782X

46. B. Li, W. Ni, C. Constantinescu (2015). Risk models with premiums adjusted to claims number. Insurance: Mathematics and Economics, 65. pp. 94-102, doi:10.1016/j.insmatheco.2015.09.001

47. Y. Liu, T. Kozubowski (2015). A folded Laplace distribution, Journal of Statistical Distributions and Applications, 2(10), doi:10.1186/s40488-015-0033-9

48. L. T. Truong, M. Sarvi, G. Currie, T. M. Garoni (2015), Required traffic micro-simulation runs for reliable multivariate performance estimates, Volume 50, Issue 3, April 2016, Pages 296–314, doi:10.1002/atr.1319 

49. P. Liu, E. Hashorva, L. Ji (2015). On the γ-reflected processes with fBm input. Lithuanian Mathematical Journal, 55(3), 402-414, doi:10.1007/s10986-015-9288-6

50. P. Lorek, R. Szekli (2015). Strong Stationary Duality for Mobius Monotone Markov Chains: Examples", Probability and Mathematical Statistics, doi:10.1007/s11134-012-9284-z

51. O. Menoukeu-Pamen (2015): Optimal Control for Stochastic Delay Systems under Model Uncertainty: A Stochastic Differential Game Approach. Journal of Optimization Theory Applications (2015) 167:998–1031

52. O. Menoukeu-Pamen (2015). Non-linear time-advanced backward stochastic partial differential equations with jumps. Stochastic Analysis and Applications. 33, 673–700

53. O. Menouke-Pamen and R. Momeya (2015). Local risk minimization under Markov modulated exponential Levy model”. International Journal of Theoretical and Applied Finance. 18, (23 pages)

54. E. Hashorva, L. Ji (2015) Piterbarg theorems for chi-processes with trend. Extremes, 18(1), 37-64, doi:10.1007/s10687-014-0201-1

55. E. Hashorva, J. Li (2015). Tail Behavior of Weighted Sums of Order Statistics of Dependent Risks. Stochastic Models, 31(1), 1-19, doi:10.1080/15326349.2014.954133

56. E. Hashorva, Y. Mishura, O. Seleznjev (2015). Boundary non-crossing probabilities for fractional Brownian motion with trend. Stochastics An International Journal of Probability and Stochastic Processes, 87(6), 946-965, doi:10.1080/17442508.2015.1019882

57. E. Hashorva, L. Peng, Z. Weng (2015). Maxima of a triangular array of multivariate Gaussian sequence. Statistics & Probability Letters, 103, 62-72, doi:10.1016/j.spl.2015.04.007

58. E. Hashorva, G. Ratovomirija (2015). ON SARMANOV MIXED ERLANG RISKS IN INSURANCE APPLICATIONS. ASTIN Bulletin, 45(01), 175-205, doi:10.1017/asb.2014.24

59. E. Hashorva, Z. Tan (2015). Piterbarg's max-discretization theorem for stationary vector Gaussian processes observed on different grids. Statistics, 49(2), 338-360, doi:10.1080/02331888.2014.982653

60. E. Hashorva, Z. Weng (2015). Limit Laws for Maxima of Contracted Stationary Gaussian Sequences. Communications in Statistics - Theory and Methods, 44(21), 4641-4650, doi:10.1080/03610926.2013.784994

61. D. Korshunov, V. I. Piterbarg, E. Hashorva (2015). On the asymptotic Laplace method and its application to random chaos. Mathematical Notes. 97, no. 5-6, 878–891, doi:10.1134/S0001434615050235

62. T. Kozubowski, A. Panorska, M. Forister (2015). A discrete truncated Pareto distribution, Statistical Methodology, 26, 135-150, doi:10.1016/j.stamet.2015.04.002

63. K. Dȩbicki, E. Hashorva, L. Ji, C. Ling (2015). Extremes of order statistics of stationary processes. TEST, 24(2), 229-248, doi:10.1007/s11749-014-0404-4

64. K. Dȩbicki, E. Hashorva, L. Ji, K. Tabiś (2015). Extremes of vector-valued Gaussian processes: Exact asymptotics. Stochastic Processes and their Applications, 125(11), 4039-4065, doi:10.1016/j.spa.2015.05.015

65. K. Debicki, E. Hashorva, L. Ji (2015). Parisian ruin of self-similar Gaussian risk processes. J. Applied Probability, 52(3), 688-702, doi:10.1017/S0021900200113373

66. K. Debicki, E. Hashorva, N. Soja-Kukieła (2015). Extremes of homogeneous Gaussian random fields. Journal of Applied Probability, 52(1), 55-67. http://projecteuclid.org/euclid.jap/1429282606

67. S. Emmer, M. Kratz, D. Tasche (2015). What is the best risk measure in practice? A comparison of standard risk measures. Journal of Risk 18:2, 31-60, doi:10.21314/JOR.2015.318

68. H. Godínez-Olivares, C. Boado-Penas, A. Pantelous (2015). “How to Finance Pensions: Optimal Strategies for Pay-as-you-go Pension Systems”. Journal of Forecasting, doi:10.1002/for.2351

69. H. Godínez-Olivares, C. Boado-Penas (2015). An alternative pension reform for Spain based on optimisation techniques. Spanish Actuarial Annals.

70. E. Hashorva, D. Korshunov, V. I. Piterbarg (2015). Asymptotic expansion of Gaussian chaos via probabilistic approach. Extremes18. 315-347, doi:10.1007/s10687-015-0215-3

71. B. Das, S. Engelke, E. Hashorva (2015). Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process. Stochastic Processes and their Applications, 125(2), 780-796, doi:10.1016/j.spa.2014.09.006

72. J. Akahori, T. Amaba, K. Okuma (2015). A Discrete-Time Clark-Ocone Formula and its Application to an Error Analysis, JOTP., doi:10.1007/s10959-016-0666-8

73. M. Anabila, T. Kozubowski (2015). A skew Pareto distribution on the real line, Journal of Probability and Statistical Science 13(2), 179-196.

74. S. Arnold (-Gaille), C. Boado-Penas, H. Godínez-Olivares (2015). “Longevity Risk in Notional Defined Contribution Pension Schemes: a Solution”. Geneva Papers on Risk and Insurance, doi:10.1057/gpp.2015.15

75. E. Hashorva (2015). Extremes of aggregated Dirichlet risks. Journal of Multivariate Analysis 133, 334-345, doi:10.1016/j.jmva.2014.09.018

76. J. Li (2015). Asymptotics for large claims reinsurance in a time-dependent renewal risk model. Scandinavian Actuarial Journal 2015(2), 172-183, doi:10.1016/j.jmaa.2011.10.012

77. X. Liang, X. Peng, J. Guo (2014). Optimal investment, consumption and timing of annuity purchase under a preference change. Journal of Mathematical Analysis and Applications 413, 905-938, doi:10.1016/j.jmaa.2013.12.036

78. E. Hashorva, J. Li (2014). Asymptotics for a discrete-time risk model with the emphasis on financial risk. Probability in the Engineering and Informational Sciences 28(4), 573-588, doi:10.1080/03461238.2015.1004802

79. E. Hashorva, J. Li (2014). Extremes and first passage times of correlated fBm's. Stochastic Models 30(3), 272-299, doi:10.1080/15326349.2014.903159

80. E. Hashorva, S. Nadarajah, T. Pogany  (2014). Extremes of perturbed bivariate Rayleigh risks, REVSTAT- Statistical Journal 2(2), 157-168.

81. E. Hashorva, L. Ji (2014). Random Shifting and Scaling of Insurance Risks, Risks 2, 277-288, doi:10.3390/risks2030277

82. E. Hashorva, L. Ji (2014). Asymptotics of the Finite-time Ruin Probability for the Sparre Andersen Risk Model Perturbed by an Inflated Stationary Chi-process. Communications in Statistics -Theory and Methods 43(10-12), 2540-2548, doi:10.1080/03610926.2012.759974

83. E. Hashorva, C. Ling, Z. Peng (2014). Second-order tail asymptotics of deflated risk. Insurance: Mathematics and Economics 56, 88-101, doi:10.1016/j.insmatheco.2014.04.003

84. E. Hashorva, C. Ling, Z. Peng (2014). Tail asymptotic expansions for L-Statisitcs. Science China Mathematics 57, 1993-2012, doi:10.1007/s11425-014-4841-z

85. E. Hashorva, D. Kortschak (2014). Tail asymptotics of random sum and maximum of log-normal risks. Statistics and Probability Letters, 87, 167-174, doi:10.1016/j.spl.2014.01.018

86. E. Hashorva, Y. Mishura (2014). Boundary non-crossings of additive Wiener fields. Lithuanian Mathematical Journal 54(3), 277-289, doi:10.1007/s10986-014-9243-y

87. E. Hashorva, Z. Weng (2014). Berman's inequality under random scaling. Statistics and its interface 7, 339-349, doi:10.4310/SII.2014.v7.n3.a4

88. A. Buddana, T. Kozubowski (2014). Discrete Pareto distributions, Economic Quality Control, 29(2), 143-156, doi:10.1515/eqc-2014-0014

89. E. Hashorva, Z. Weng (2014). Maxima and minima of complete and incomplete stationary sequences. Stochastics 86(5), 707-720, doi:10.1080/17442508.2013.876423

90. E. Hashorva, Z. Weng (2014). Joint Limiting Distribution of Minima and Maxima of Complete and Incomplete Samples of Stationary Sequences. Stochastics An International Journal of Probability and Stochastic Processes, doi:10.1080/17442508.2013.876423

91. M. Busse, M. Dacorogna, M. Kratz (2014). The impact of systemic risk on the diversification benefits of a risk portfolio, Risks 2, 260-276.

92. K. Debicki, E. Hashorva, L. Ji (2014). Gaussian Approximation of Perturbed Chi-Square Risks. Statistics and Its Interface 3, 363-373, doi:10.4310/SII.2014.v7.n3.a6

93. K. Debicki, E. Hashorva, L. Ji (2014). Tail asymptotics of supremum of certain gaussian processes over threshold dependent random intervals. Extreme 17(3), 411-429, doi:10.1007/s10687-014-0186-9

94. K. Debicki, E. Hashorva, L. Ji, Z. Tan (2014). Finite-time Ruin Probability of Aggregate Gaussian Processes. Markov Processes and Related Fields 20, 435–450.

95. K. Debicki, E. Hashorva, L. Ji, K. Tabis (2014). On the probability of conjunctions of stationary Gaussian processes. Statistics and Probability Letters 88, 141-148, doi:10.1016/j.spl.2014.02.004

96. K. Debicki, K. M. Kosinski (2014). On the infimum attained by the relected fractional Brownian motion. Extremes 17(3), 431-446, doi:10.1007/s10687-014-0188-7

97. P. Embrechts, E. Hashorva, T. Mikosch (2014). Aggregation of log-linear risks. Journal of Applied Probability 51A, 203-212, doi:10.1239/jap/1417528476

98. A. Guillou, M. Kratz, Y. Le, Strat (2014). An Extreme Value Theory approach for the early detection of time clusters. A simulation-based assessment and an illustration to the surveillance of Salmonella. Statistics in Medicine 33, 5015-5027, doi:10.1002/sim.6275

99. D. A. Korshunov, V. I. Piterbarg, E. Hashorva (2013). On Extremal Behavior of Gaussian Chaos. Doklady Mathematics, 88(2), 566–568, doi:10.1134/S1064562413050220

100. E. Hashorva, J. Li (2013). ECOMOR and LCR reinsurance with gamma-like claims. Insurance: Mathematics and Economics, 53(1), 206-215, doi:10.1016/j.insmatheco.2013.05.004

101. E. Hashorva, Z. Tan (2013). Large deviations of Shepp statistics for fractional Brownian motion. Statistics & Probability Letters, 83(10), 2242-2247, doi:10.1016/j.spl.2013.06.013

102. E. Hashorva, L. Ji, V. I. Piterbarg (2013). On the supremum of gamma-reflected processes with fractional Brownian motion as input. Stochastic Processes and their Applications, 123(11), 4111-4127, doi:10.1016/j.spa.2013.06.007

103. E. Hashorva, Z. Peng, Z. Weng (2013). On Piterbarg theorem for the maxima of stationary Gaussian sequences. Lithuanian Mathematical Journal, 53(3), 280-292. Accepted (in press) publications, doi:10.1007/s10986-013-9208-6

104. K. Debicki, E. Hashorva, L. Ji (2013). Gaussian risk models with financial constrains. Scandinavian Actuarial Journal, doi:10.1080/03461238.2013.850442

105. J. Farkas, E. Hashorva (2013). Tail approximation for reinsurance Portfolios of Gaussian-like risks. Scandinavian Actuarial Journal, doi:abs/10.1080/03461238.2013.825639

106. E. Hashorva, L. Ji (2013). Approximation of passage times of gamma-reflected processes with fBm input. Journal of Applied Probability, doi:10.1239/jap/1409932669

107. E. Hashorva, Z. Peng, Z. Weng (2013). Limit properties of exceedances point processes of scaled stationary Gaussian sequences. Probability and Mathematical Statistics.

108. E. Hashorva, C. Ling, Z. Peng (2013). Modeling of censored bivariate extremal events. Journal of the Korean Statistical Society, doi:10.1016/j.jkss.2013.10.004

109. E. Hashorva, Z. Weng (2013). Tail asymptotic of Weibull-type risks. Statistics, doi:10.1080/02331888.2013.800520

110. D. Kortschak, E. Hashorva (2013). Second order asymptotics of aggregated logelliptical risk. Meth. Comp. Appl. Probab, doi:10.1007/s11009-013-9356-5