Abstract
In the paper a stochastic asset model can be used for long term financial planning and observations in insurance. The scenario model is developed for the case when the large number of scenarios is generated and represents the uncertainty of stochastic parameters. The paper presents the construction the multistage scenario tree using the clustering-based approach. It is implemented on sampled data of nominal interest rate according to accepted stochastic model.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Brigo, D., Mercurio, F.: Interest Rate Model-Theory and Practice: With Smile. Inflation and Credit, Springer Finance (2001)
Cox, J.C., Ingersoll, J.E., Ross, S.A.: A theory of the term structure of interest rates. Econometrica 53, 385–407 (1985). doi:10.2307/1911242
Hibbert, J., Mowbray, P., Turnbull, C.: A stochastic asset model and calibration for long-term financial planning purposes. Technical Report, Barrie & Hibbert Limited, pp. 1–76 (2001)
Vasicek, O.: An equilibrium characterization of the term structure. J. Financ. Econ. 5, 177–188 (1977)
Dupacova, J., Consigli, G., Wallace, S.W.: Scenarios for multistage stochastic programs. Ann. Oper. Res. 100, 25–53 (2000)
Domenica, N., Birbilis, G., Mitra, G., Valente, P.: Stochastic programming and scenario generation within a simulation framework: an information system perspective, pp. 1–41. Carisma Center, Brunel University, Uxbridge, Middlesex (2003)
Dupacova, J., Hurt, J., Stepan, J.: Stochastic Modeling in Economics and Finance. Kluwer Academic Publishers (2002)
Kaut, M.: Scenario Generation for Stochastic Programming Introduction and Selected Methods, pp. 1–61. SINTEF Technology and Society (2011)
Mitra, S.: Scenario generation for stochastic programming. OptiRisk Syst. 1–33 (2008)
Mitra, S., Di Domenica, N.: A review of scenario generation methods. Int. J. Comput. Sci. Math. 3(3), 226–244 (2015). ISSN: 1752-5055
Pflug, G., Romisch, W.: Modeling, Measuring and Managing Risk. World Scientific Publishing Co. Pte. Ltd. (2007)
Jain, A., Murty, M.N., Flynn, P.J.: Data clustering: a review. ACM Comput. Surv. 31, 3 (1999)
Kaufmann, L., Rousseeuw, P.: Finding Groups in Data: An Introduction to Cluster Analysis. Wiley-Interscience, Canada (1990)
Kovacheva, Ts.: Cluster analysis. Inf. Technol. Control. Sofia. 3, 24–29 (2004)
Kovacheva, Ts.: Risk factors analysis affecting the insurance company’s activities. “Applied Mathematics and Mechanics”, Proceeding, Ulyanovsk State Technical University, Ulyanovsk, pp. 252–258 (2011). ISBN: 978-5-9795-0904-4
Neftci, S.: An Introduction to the Mathematics of Financial Derivatives. Elsevier (2000)
Statistical Analysis with SAS/STAT\(^{\textregistered }\) Software. http://www.sas.com/technologies/analytics/statistics/stat/index.html
Heitsch, H., Römisch, W.: Scenario tree modelling for multistage stochastic programs. DFG Research Center Matheon “Mathematics for key technologies” (2005)
Pranevicius, H., Sutiene, K.: Scenario generation for multistage stochastic programs, pp. 1–6. KTU, Kaunas (2008)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Kovacheva, T. (2017). Construction of Multistage Scenario Tree for Insurance Activity. In: Georgiev, K., Todorov, M., Georgiev, I. (eds) Advanced Computing in Industrial Mathematics. Studies in Computational Intelligence, vol 681. Springer, Cham. https://doi.org/10.1007/978-3-319-49544-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-49544-6_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-49543-9
Online ISBN: 978-3-319-49544-6
eBook Packages: EngineeringEngineering (R0)