Prof. dr. P.J.C. (Peter) Spreij
Faculty of Science
KDV
Visiting address
- Science Park 107
Postal address
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Postbus 94248
1090 GE Amsterdam
Contact details
Social media
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Publications
2024
Finesso, L., & Spreij, P. (2024). Synchronous deautoconvolution algorithm for discrete-time positive signals via I-divergence approximation. Journal of Computational and Applied Mathematics, 451, Article 116025. https://doi.org/10.1016/j.cam.2024.116025 [details]- He, J., Khedher, A., & Spreij, P. (2024). A dimension reduction approach for loss valuation in credit risk modeling. International Journal of Financial Engineering, 11(1), Article 2350058. https://doi.org/https://arxiv.org/abs/2401.00085, https://doi.org/10.1142/S2424786323500640 [details]
- Michielon, M., Franquinho, D., Gentile, A., Khedher, A., & Spreij, P. (2024). Neural network empowered liquidity pricing in a two-price economy under conic finance settings. Quantitative Finance, 24(8), 1129-1156. https://doi.org/10.1080/14697688.2024.2390947
- Michielon, M., Khedher, A., & Spreij, P. (2024). Proxying credit curves via Wasserstein distances. Annals of Operations Research, 336(1-2), 1351-1367. https://doi.org/10.1007/s10479-022-04552-3 [details]
- Schiphorst, B., Mandjes, M., Spreij, P., & Winands, E. (2024). A Structural Credit Risk Model with Default Contagion. In M. Corazza, F. Gannon, F. Legros, C. Pizzi, & V. Touzé (Eds.), Mathematical and Statistical Methods for Actuarial Sciences and Finance: MAF2024 (pp. 280-285). Springer. https://doi.org/10.1007/978-3-031-64273-9_46
- Zhao, C., van Beek, M., Spreij, P., & Ba, M. (2024). Polynomial approximation of discounted moments. Finance and Stochastics. https://doi.org/10.1007/s00780-024-00550-4
2023
- Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2023). Weak solutions to gamma-driven stochastic differential equations. Indagationes Mathematicae, 34(4), 820-829. https://doi.org/10.1016/j.indag.2023.03.004 [details]
- Finesso, L., & Spreij, P. (2023). The Inverse Problem of Positive Autoconvolution. IEEE Transactions on Information Theory, 69(6), 4081-4092. https://doi.org/10.1109/TIT.2023.3244407 [details]
- Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2023). Nonparametric Bayesian volatility learning under microstructure noise. Japanese Journal of Statistics and Data Science, 6(1), 551-571. https://doi.org/10.1007/s42081-022-00185-9 [details]
- Magra, A., Baarslag, T., & Spreij, P. (2023). Querying User Preferences in Automated Negotiation. In R. Hadfi, W. Li, & T. Ito (Eds.), Proceedings - 2023 IEEE International Conference on Agents, ICA 2023 (pp. 71-76). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICA58824.2023.00021
- Michielon, M., Khedher, A., & Spreij, P. (2023). On Wasserstein distances, barycenters, and the cross-section methodology for proxy credit curves. International Journal of Financial Engineering, 10( 2), Article 2250037. https://doi.org/10.1142/S2424786322500372 [details]
2022
- Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2022). Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations. Bernoulli, 28(4), 2151-2180. https://doi.org/10.3150/21-BEJ1413 [details]
- Delsing, G. A., Mandjes, M. R. H., Spreij, P. J. C., & Winands, E. M. M. (2022). On capital allocation for a risk measure derived from ruin theory. Insurance: Mathematics and Economics, 104, 76-98. https://doi.org/10.1016/j.insmatheco.2022.02.001 [details]
- Derksen, M., Spreij, P., & Wijnbergen, S. V. (2022). Accounting Noise and the Pricing of Cocos. International Journal of Theoretical and Applied Finance, 25(7-8), Article 2250028. https://doi.org/10.2139/ssrn.3162588, https://doi.org/10.1142/S0219024922500285
2021
- He, J., Khedher, A., & Spreij, P. J. C. (2021). A Kalman particle filter for online parameter estimation with applications to affine models. Statistical Inference for Stochastic Processes, 24(3), 353-403. https://doi.org/10.1007/s11203-021-09239-3 [details]
- Michielon, M., Khedher, A., & Spreij, P. (2021). From bid-ask credit default swap quotes to risk-neutral default probabilities using distorted expectations. International Journal of Theoretical and Applied Finance, 24(3), Article 2150017. https://doi.org/10.48550/arXiv.2108.06578, https://doi.org/10.1142/S0219024921500175 [details]
- Michielon, M., Khedher, A., & Spreij, P. (2021). Liquidity-free implied volatilities: an approach using conic finance. International Journal of Financial Engineering, 8(4), Article 2150041. Advance online publication. https://doi.org/10.1142/S2424786321500419 [details]
2020
- Delsing, G. A., Mandjes, M. R. H., Spreij, P. J. C., & Winands, E. M. M. (2020). Asymptotics and Approximations of Ruin Probabilities for Multivariate Risk Processes in a Markovian Environment. Methodology and Computing in Applied Probability, 22(3), 927-948. https://doi.org/10.1007/s11009-019-09742-4 [details]
- Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2020). Nonparametric bayesian estimation of a hölder continuous diffusion coefficient. Brazilian Journal of Probability and Statistics, 34(3), 537-559. https://doi.org/10.1214/19-BJPS433 [details]
- van Beek, M., Mandjes, M., Spreij, P., & Winands, E. (2020). Regime switching affine processes with applications to finance. Finance and Stochastics, 24(2), 309-333. https://doi.org/10.1007/s00780-020-00419-2 [details]
2019
- Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2019). Nonparametric Bayesian inference for Gamma-type Lévy subordinators. Communications in Mathematical Sciences, 17(3), 781-816. https://doi.org/10.4310/CMS.2019.v17.n3.a8 [details]
- Delsing, G. A., Mandjes, M. R. H., Spreij, P. J. C., & Winands, E. M. M. (2019). An optimization approach to adaptive multi-dimensional capital management. Insurance: Mathematics and Economics, 84, 87-97. https://doi.org/10.1016/j.insmatheco.2018.10.001 [details]
- Finesso, L., & Spreij, P. (2019). Approximation of nonnegative systems by moving averages of fixed order. Automatica, 107, 1-8. https://doi.org/10.1016/j.automatica.2019.05.007 [details]
- Gugushvili, S., Van der Meulen, F., Schauer, M., & Spreij, P. (2019). Bayesian wavelet de-noising with the caravan prior. ESAIM - Probability and Statistics, 23, 947-978. https://doi.org/10.1051/ps/2019019 [details]
- Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2019). Nonparametric Bayesian Volatility Estimation. In D. R. Wood, J. de Gier, C. E. Praeger, & T. Tao (Eds.), 2017 MATRIX Annals (pp. 279-302). (MATRIX Book Series; Vol. 2). Springer. https://doi.org/10.1007/978-3-030-04161-8_19 [details]
- Mandjes, M., Starreveld, N., Bekker, R., & Spreij, P. (2019). Dynamic Erdős-Rényi Graphs. In B. Steffen, & G. Woeginger (Eds.), Computing and Software Science : State of the Art and Perspectives (pp. 123-140). (Lecture Notes in Computer Science; Vol. 10000). Springer. https://doi.org/10.48550/arXiv.1703.05505, https://doi.org/10.1007/978-3-319-91908-9_8 [details]
- Spreij, P., & Storm, J. (2019). Diffusion Limits for a Markov Modulated Binomial Counting Process. Probability in the Engineering and Informational Sciences, 34(2), 235-257. https://doi.org/10.1017/S0269964818000578
2018
- Gugushvili, S., van der Meulen, F., & Spreij, P. (2018). A non-parametric Bayesian approach to decompounding from high frequency data. Statistical Inference for Stochastic Processes, 21(1), 53-79. https://doi.org/10.1007/s11203-016-9153-1 [details]
2017
- Mandjes, M., & Spreij, P. (2017). A note on the central limit theorem for the idleness process in a one-sided reflected Ornstein–Uhlenbeck model. Statistica Neerlandica, 71(3), 225-235. https://doi.org/10.1111/stan.12108 [details]
2016
- Finesso, L., & Spreij, P. (2016). Factor analysis models via I-divergence optimization. Psychometrika, 81(3), 702-726. Advance online publication. https://doi.org/10.1007/s11336-015-9486-5 [details]
- Gugushvili, S., & Spreij, P. (2016). Posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient of a stochastic differential equation. ESAIM-Probability and Statistics, 20, 143-153. https://doi.org/10.1051/ps/2016008 [details]
- Huang, G., Jansen, H. M., Mandjes, M., Spreij, P., & De Turck, K. (2016). Markov-modulated Ornstein-Uhlenbeck processes. Advances in Applied Probability, 48(1), 235-254. https://doi.org/10.1017/apr.2015.15 [details]
- Huang, G., Mandjes, M., & Spreij, P. (2016). Large deviations for Markov-modulated diffusion processes with rapid switching. Stochastic Processes and their Applications, 126(6), 1785-1818. https://doi.org/10.1016/j.spa.2015.12.005 [details]
- Mandjes, M., & Spreij, P. (2016). Explicit Computations for Some Markov Modulated Counting Processes. In J. Kallsen, & A. Papapantoleon (Eds.), Advanced Modelling in Mathematical Finance: In Honour of Ernst Eberlein (pp. 63-89). (Springer Proceedings in Mathematics & Statistics; Vol. 189). Springer. https://doi.org/10.1007/978-3-319-45875-5_3 [details]
2015
- Finesso, L., & Spreij, P. (2015). Approximation of Nonnegative Systems by Finite Impulse Response Convolutions. IEEE Transactions on Information Theory, 61(8), 4399-4409. https://doi.org/10.1109/TIT.2015.2443786 [details]
- Gugushvili, S., van der Meulen, F., & Spreij, P. (2015). Nonparametric Bayesian inference for multidimensional compound Poisson processes. Modern Stochastics : Theory and Applications, 2(1), 1-15. https://doi.org/10.15559/15-VMSTA20 [details]
- van Beek, M., Mandjes, M. R. H., Spreij, P. J. C., & Winands, E. M. M. (2015). Regime switching affine processes and applications in finance. In Prodeedings Stochastic & Computational Finance 2015 — From Academia to Industry
2014
- Gugushvili, S., & Spreij, P. (2014). Consistent non-parametric Bayesian estimation for a time-inhomogeneous Brownian motion. ESAIM-Probability and Statistics, 18, 332-341. https://doi.org/10.1051/ps/2013039 [details]
- Gugushvili, S., & Spreij, P. (2014). Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations. Lithuanian Mathematical Journal, 54(2), 127-141. https://doi.org/10.1007/s10986-014-9232-1 [details]
- Huang, G., Mandjes, M., & Spreij, P. (2014). Limit theorems for reflected Ornstein-Uhlenbeck processes. Statistica Neerlandica, 68(1), 25-42. https://doi.org/10.1111/stan.12021 [details]
- Huang, G., Mandjes, M., & Spreij, P. (2014). Weak convergence of Markov-modulated diffusion processes with rapid switching. Statistics & Probability Letters, 86, 74-79. https://doi.org/10.1016/j.spl.2013.12.013 [details]
- Klein, A., & Spreij, P. (2014). A block Hankel generalized confluent Vandermonde matrix. Linear Algebra and Its Applications, 455, 32-72. https://doi.org/10.1016/j.laa.2014.05.002 [details]
- van Beek, M., Mandjes, M., Spreij, P., & Winands, E. (2014). Markov switching affine processes and applications to pricing. In M. Vanmaele, G. Deelstra, A. De Schepper, J. Dhaene, W. Schoutens, S. Vanduffel, & D. Vyncke (Eds.), Actuarial and Financial Mathematics Conference, Interplay between Finance and Insurance: February 6-7, 2014 (pp. 97-102). Koninklijke Vlaamse Academie van België voor Wetenschappen en Kunsten. http://www.afmathconf.ugent.be/FormerEditions/Proceedings2014.pdf [details]
2012
- Gugushvili, S., & Spreij, P. (2012). Parametric inference for stochastic differential equations: a smooth and match approach. Alea, 9(2), 609-635. http://alea.impa.br/articles/v9/09-24.pdf [details]
- Klein, A., & Spreij, P. J. C. (2012). Transformed statistical distance measures and the fisher information matrix. Linear Algebra and Its Applications, 437(2), 692-712. https://doi.org/10.1016/j.laa.2012.03.002 [details]
- Spreij, P., & Veerman, E. (2012). Affine diffusions with non-canonical state space. Stochastic Analysis and Applications, 30(4), 605-641. https://doi.org/10.1080/07362994.2012.684322 [details]
2011
- Gugushvili, S., van Es, B., & Spreij, P. (2011). Deconvolution for an atomic distribution: rates of convergence. Journal of Nonparametric Statistics, 23(4), 1003-1029. https://doi.org/10.1080/10485252.2011.576763 [details]
- Leijdekker, V. J. G., Mandjes, M. R. H., & Spreij, P. J. C. (2011). Sample-path large deviations in credit risk. Journal of applied mathematics, 2011. https://doi.org/10.1155/2011/354171 [details]
- Leijdekker, V., & Spreij, P. (2011). Explicit computations for a filtering problem with point process observations with applications to credit risk. Probability in the Engineering and Informational Sciences, 25(3), 393-418. https://doi.org/10.1017/S0269964811000076 [details]
- Spreij, P., Veerman, E., & Vlaar, P. (2011). An affine two-factor heteroskedastic macro-finance term structure model. Applied Mathematical Finance, 18(4), 331-352. https://doi.org/10.1080/1350486X.2010.517664 [details]
- van Es, B., & Spreij, P. (2011). Estimation of a multivariate stochastic volatility density by kernel deconvolution. Journal of Multivariate Analysis, 102(3), 683-697. https://doi.org/10.1016/j.jmva.2010.12.003 [details]
- van Es, B., Spreij, P., & van Zanten, H. (2011). Nonparametric methods for volatility density estimation. In G. di Nunno, & B. Øksendal (Eds.), Advanced Mathematical Methods for Finance (pp. 293-312). (Springer for Research & Development). Springer. http://rd.springer.com/chapter/10.1007/978-3-642-18412-3_11 [details]
2010
- Finesso, L., Grassi, A., & Spreij, P. (2010). Approximation of stationary processes by hidden Markov models. Mathematics of control, signals, and systems, 22(1), 1-22. https://doi.org/10.1007/s00498-010-0050-7 [details]
- Finesso, L., Grassi, A., & Spreij, P. (2010). Two-step nonnegative matrix factorization algorithm for the approximate realization of hidden Markov models. In A. Edelmayer (Ed.), Proceedings of the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010), Budapest, Hungary (pp. 369-374). Eötvös Loránd University. http://arxiv.org/abs/1007.3435 [details]
- Gugushvili, S., Klaassen, C., & Spreij, P. (2010). Editorial introduction. Statistica Neerlandica, 64(3), 255-256. https://doi.org/10.1111/j.1467-9574.2010.00459.x [details]
- Klein, A., & Spreij, P. (2010). Tensor Sylvester matrices and the Fisher information matrix of VARMAX processes. Linear Algebra and Its Applications, 432(8), 1975-1989. https://doi.org/10.1016/j.laa.2009.06.027 [details]
2009
- Klein, A., & Spreij, P. (2009). Matrix differential calculus applied to multiple stationary time series and an extended Whittle formula for information matrices. Linear Algebra and Its Applications, 430(2-3), 674-691. https://doi.org/10.1016/j.laa.2008.09.019 [details]
- van Veelen, M., & Spreij, P. (2009). Evolution in games with a continuous action space. Economic Theory, 39(3), 355-376. https://doi.org/10.1007/s00199-008-0338-8 [details]
2008
- Finesso, L., Grassi, A., & Spreij, P. (2008). Approximation of the I-divergence between stationary and hidden Markov processes. In Proceedings of the 2008 International Workshop on Applied Probability (IWAP 2008) Université de Technologie de Compiègne. http://staff.science.uva.nl/~spreij/hmmIWAP2008.pdf [details]
- van Es, B., Gugushvili, S., & Spreij, P. (2008). Deconvolution for an atomic distribution. Electronic Journal of Statistics, 2, 265-297. https://doi.org/10.1214/07-EJS121 [details]
2020
- Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2020). Fast and scalable non-parametric Bayesian inference for Poisson point processes. Researchers.One. https://researchers.one/articles/19.06.00001 [details]
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Ancillary activities
No ancillary activities
Finesso, L., & Spreij, P. (2024). Synchronous deautoconvolution algorithm for discrete-time positive signals via I-divergence approximation. Journal of Computational and Applied Mathematics, 451, Article 116025.