Prof. dr. P.J.C. (Peter) Spreij
Faculty of Science
KDV
Visiting address
- Science Park 107
- Room number: F3.35
Postal address
- Postbus 94248
1090 GE Amsterdam
Contact details
Social media
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Publications
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. J. M., Spreij, P. J. C., & van Wijnbergen, S. J. G. (2022). Accounting Noise and the Pricing of Contingent Convertible Bonds (Cocos). International Journal of Theoretical and Applied Finance. https://doi.org/10.2139/ssrn.3162588, https://doi.org/10.1142/S0219024922500285, https://doi.org/10.1142/S0219024922500285
- Gugushvili, S., van der Meulen, F., Schauer, M., & Spreij, P. (2022). Nonparametric Bayesian volatility learning under microstructure noise. Japanese Journal of Statistics and Data Science. https://doi.org/10.1007/s42081-022-00185-9
- Michielon, M., Khedher, A., & Spreij, P. (2022). Proxying credit curves via Wasserstein distances. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04552-3
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), [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), [2150041]. 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, 1-23. 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. 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]
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). Brussel, België: Koninklijke Vlaamse Academie van België voor Wetenschappen en Kunsten. [details]
2012
- Gugushvili, S., & Spreij, P. (2012). Parametric inference for stochastic differential equations: a smooth and match approach. Alea, 9(2), 609-635. [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. [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) Compiègne, France: Université de Technologie de Compiègne. [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]
2018
- Van Der Meulen, F., Spreij, P., Gugushvili, S. & Schauer, M. (12-10-2018). Code accompanying the paper "Bayesian wavelet de-noising with the caravan prior". Zenodo. https://doi.org/10.5281/zenodo.1460346
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Ancillary activities
- No ancillary activities
Belomestny, D., Gugushvili, S., Schauer, M., & Spreij, P. (2022). Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations. Bernoulli, 28(4), 2151-2180.