Hoencamp, J., Jain, S., & Kandhai, D. (2023). A Semi-Static Replication Method for Bermudan Swaptions under an Affine Multi-Factor Model. Risks, 11(10), Article 168. https://doi.org/10.3390/risks11100168[details]
Hoencamp, J. H., de Kort, J. P., & Kandhai, B. D. (2022). The Impact of Stochastic Volatility on Initial Margin and MVA for Interest Rate Derivatives. Applied Mathematical Finance, 29(2), 141-179. https://doi.org/10.1080/1350486X.2022.2156900[details]
Anagnostou, I., Squartini, T., Kandhai, D., & Garlaschelli, D. (2021). Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling. Quantitative Finance, 21(9), 1501-1518. https://doi.org/10.1080/14697688.2021.1890807[details]
Boersma, M., Maliutin, A., Sourabh, S., Hoogduin, L. A., & Kandhai, D. (2020). Reducing the complexity of financial networks using network embeddings. Scientific Reports, 10, Article 17045. https://doi.org/10.1038/s41598-020-74010-2[details]
Anagnostou, I., & Kandhai, D. (2019). Risk Factor Evolution for Counterparty Credit Risk under a Hidden Markov Model. Risks, 7(2), Article 66. https://doi.org/10.3390/risks7020066[details]
Moysiadis, G., Anagnostou, I., & Kandhai, D. (2019). Calibrating the Mean-Reversion Parameter in the Hull-White Model Using Neural Networks. In C. Alzate, & A. Monreale (Eds.), ECML PKDD 2018 Workshops: MIDAS 2018 and PAP 2018, Dublin, Ireland, September 10-14, 2018 : proceedings (pp. 23-36). (Lecture Notes in Computer Science; Vol. 11054), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-13463-1_2[details]
2018
Anagnostou, I., Sourabh, S., & Kandhai, D. (2018). Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory. Complexity, 2018, Article 6076173. https://doi.org/10.1155/2018/6076173[details]
Boersma, M., Sourabh, S., Hoogduin, L., & Kandhai, D. (2018). Financial statement networks: an application of network theory in audit. The Journal of Network Theory in Finance, 4(4), 59-85. https://doi.org/10.21314/JNTF.2018.048[details]
Sourabh, S., Hofer, M., & Kandhai, D. (2018). Liquidity risk in derivatives valuation: an improved credit proxy method. Quantitative Finance, 18(3), 467-481 . Advance online publication. https://doi.org/10.1080/14697688.2017.1315166[details]
de Graaf, C. S. L., Kandhai, D., & Sloot, P. M. A. (2017). Efficient Estimation of Sensitivities for Counterparty Credit Risk with the Finite Difference Monte Carlo Method. Journal of Computational Finance, 21(1), 83-113. Advance online publication. https://doi.org/10.2139/ssrn.2521431, https://doi.org/10.21314/JCF.2016.325[details]
Simaitis, S., de Graaf, C. S. L., Hari, N., & Kandhai, D. (2016). Smile and Default: The Role of Stochastic Volatility and Interest Rates in Counterparty Credit Risk. Quantitative Finance, 16(11), 1725-1740. https://doi.org/10.1080/14697688.2016.1176240[details]
Savickas, V., Hari, N., Wood, T., & Kandhai, D. (2014). Super Fast Greeks: An Application to Counterparty Valuation Adjustments. Wilmott, 69, 76-80. https://doi.org/10.1002/wilm.10291[details]
de Graaf, C. S. L., Feng, Q., Kandhai, D., & Oosterlee, C. W. (2014). Efficient Computation of Exposure Profiles for Counterparty Credit Risk. International Journal of Theoretical and Applied Finance, 17(4), Article 1450024. https://doi.org/10.1142/S0219024914500241[details]
Quax, R., Kandhai, D., & Sloot, P. M. A. (2013). Information dissipation as an early-warning signal for the Lehman Brothers collapse in financial time series. Scientific Reports, 3, Article 1898. https://doi.org/10.1038/srep01898[details]
Qiu, G., Kandhai, D., Johnson, N. F., & Sloot, P. M. A. (2012). Understanding complex dynamics in derivatives finance: why do options markets smile? Advances in Complex Systems, 15(5), Article 1250050. https://doi.org/10.1142/S0219525912500506[details]
Kromkamp, J., van den Ende, D., Kandhai, B. D., Sman, R. G. M., & Boom, R. M. (2006). Lattice Boltzmann simulation of 2D and 3D non-Brownian suspensions in Couette flow. Chemical Engineering Science, 61, 858-873. https://doi.org/10.1016/j.ces.2005.08.011[details]
2005
Kromkamp, J., van den Ende, D., Kandhai, B. D., Sman, R. G. M., & Boom, R. M. (2005). Shear-induced self-diffusion and microstructure in non-Brownian suspensions at non-zero Reynolds numbers. Journal of Fluid Mechanics, 529, 253-278. https://doi.org/10.1017/S0022112005003551[details]
Rohde, M., Kandhai, B. D., & den Akker, H. E. A. V. (2005). A generic, mass conservative local grid refinement technique for lattice-Boltzmann schemes. International Journal for Numerical Methods in Fluids, 51, 439-468. https://doi.org/10.1002/fld.1140
2004
Artoli, A. M. M., Kandhai, D., Hoefsloot, H. C. J., Hoekstra, A. G., & Sloot, P. M. A. (2004). Lattice BGK simulations of flow in a symmetric bifurcation. Future Generation Computer Systems, 20(6), 909-916. https://doi.org/10.1016/j.future.2003.12.002[details]
Hlushkou, D., Kandhai, B. D., Seidel-Morgenstern, A., & Tallarek, U. (2004). Coupled lattice-Boltzmann method and finite-difference simulations of electroosmosis in microfluidic channels. International Journal for Numerical Methods in Fluids, 507-532. http://www3.interscience.wiley.com/cgi-bin/fulltext/112210359/PDFSTART
van Wageningen, W. F. C., Kandhai, B. D., Mudde, R. F., & van den Akker, H. E. A. (2004). Dynamic flow in a Kenics static mixer: An assessment of various CFD methods. AIChE Journal, 50, 1684-1696. https://doi.org/10.1002/aic.10178
2003
Artoli, A. M. M., Kandhai, B. D., Hoefsloot, H. C. J., Hoekstra, A. G., & Sloot, P. M. A. (2003). Lattice Boltzmann, a robust and accurate solver for interactive computational hemodynamics. In P. M. A. Sloot, D. Abrahamson, A. V. Bagdanov, J. J. Dongarra, A. Y. Zomaya, & Y. E. Gorbachev (Eds.), Computational Science - ICCS 2003 (Vol. 2657, pp. 1034-1043). Melbourne, Australia and St. Petersburg, Russia: Springer Verlag. [details]
Kandhai, B. D., Derksen, J. J., & den Akker, H. E. A. V. (2003). Interphase drag coefficients in gas-solid flows. AIChE Journal, 49, 1060-1065. https://doi.org/10.1002/aic.690490423
Rohde, M., Kandhai, B. D., Derksen, J. J., & den Akker, H. E. A. V. (2003). Improved bounce-back methods for no-slip walls in lattice-Boltzmann schemes: Theory and simulations. Physical Review E, 67, 066703.
2002
Kandhai, B. D., Hlushkou, D., Hoekstra, A. G., Sloot, P. M. A., van As, H., & Tallarek, U. (2002). Influence of Stagnant Zones on Transient and Asymptotic Dispersion in Macroscopically Homogeneous Porous Media. Physical Review Letters, 88(23), 1-4. [details]
Kandhai, B. D., Tallarek, U., Hlushkou, D., Hoekstra, A., Sloot, P. M. A., & Van As, H. (2002). Numerical simulation and measurement of liquid hold-up in biporous media containing discrete stagnant zones. Philosophical Transactions of the Royal Society A - Mathematical, Physical and Engineering Sciences, 360(1792), 521-534. https://doi.org/10.1098/rsta.2001.0952[details]
2001
Artoli, A. M. M., Kandhai, B. D., Hoefsloot, H. G., Hoekstra, A. G., & Sloot, P. M. A. (2001). Shear Stress in Lattice Boltzmann Simulations. In F. Hossfeld, & K. Binder (Eds.), Europhysics Conference on Computational Physics in series Publication Series of the John von Neumann Institute for computing (Vol. 8, pp. A127) [details]
Kandhai, B. D., Koponen, A., Hoekstra, A. G., & Sloot, P. M. A. (2001). Iterative momentum relaxation for fast lattice-Boltzmann Simulations. Future Generation Computer Systems, 18(1), 89-96. https://doi.org/10.1016/S0167-739X(00)00078-9[details]
2000
Bal, H., Bhoedjang, R., Hofman, R., Jacobs, C., Kielmann, T., Maassen, J., van Nieuwpoort, R., Romein, J., Renambot, L., Rühl, T., Veldema, R., Verstoep, K., Baggio, A., Ballintijn, G., Kuz, I., Pierre, G., van Steen, M., Tanenbaum, A., Doornbos, G., ... van der Steen, A. (2000). The Distributed ASCI supercomputer project. Operating Systems Review, 34(4), 76-96. https://doi.org/10.1145/506106.506115[details]
Claque, D. S., Kandhai, B. D., Zhang, R., & Sloot, P. M. A. (2000). On the Hydraulic Permeability of (Un)Bounded Fibrous Media Using the Lattice-Boltzmann Method. Physical Review E, 61(1), 616-625. https://doi.org/10.1103/PhysRevE.61.616[details]
Kandhai, B. D., Soll, W., Chen, S., Hoekstra, A. G., & Sloot, P. M. A. (2000). Finite-Difference Lattice-BGK Methods on Nested Grids. Computer Physics Communications, 129, 100-109. https://doi.org/10.1016/S0010-4655(00)00097-7[details]
2020
Sourabh, S. (Author), Hofer, M. (Author), & Kandhai, D. (Author). (2020). Quantifying systemic risk using Bayesian networks. Web publication or website, Risk.net. Advance online publication. https://www.risk.net/7462701[details]
Artoli, A. M. M., Kandhai, B. D., Hoefsloot, H. C. J., Hoekstra, A. G., & Sloot, P. M. A. (2003). Lattice Boltzmann: a robust and accurate solver for interactive computational hymodynamics. Lecture Notes in Computer Science, 1034-1043. [details]
2024
Boersma, M. (2024). Complex networks in audit: A data-driven modelling approach. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
Hoencamp, J. H. (2024). Modern advances in computational credit risk modelling: Quantitative approaches to margin value adjustments for interest rate derivatives. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
Anagnostou, I. (2020). Risk management in trading activities through the lens of complex systems theory. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
de Graaf, C. S. L. (2016). Efficient PDE based numerical estimation of credit and liquidity risk measures for realistic derivative portfolios. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
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