Previous |  Up |  Next

Article

Title: Stability, empirical estimates and scenario generation in stochastic optimization - applications in finance (English)
Author: Kaňková, Vlasta
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 53
Issue: 6
Year: 2017
Pages: 1026-1046
Summary lang: English
.
Category: math
.
Summary: Economic and financial processes are mostly simultaneously influenced by a random factor and a decision parameter. While the random factor can be hardly influenced, the decision parameter can be usually determined by a deterministic optimization problem depending on a corresponding probability measure. However, in applications the "underlying" probability measure is often a little different, replaced by empirical one determined on the base of data or even (for numerical reason) replaced by simpler (mostly discrete) one. Consequently, real one and approximate one correspond to applications. In the paper we try to investigate their relationship. To this end we employ the results on stability based on the Wasserstein metric and ${\cal L}_{1}$ norm, their applications to empirical estimates and scenario generation. Moreover, we apply the achieved new results to simple financial applications. The corresponding model will a problem of stochastic programming. (English)
Keyword: stochastic programming problems
Keyword: probability constraints
Keyword: stochastic dominance
Keyword: stability
Keyword: Wasserstein metric
Keyword: ${\cal L}_{1}$ norm
Keyword: Lipschitz property
Keyword: empirical estimates
Keyword: scenario
Keyword: error approximation
Keyword: financial applications
Keyword: loan
Keyword: debtor
Keyword: installments
Keyword: mortgage
Keyword: bank
MSC: 90C15
idZBL: Zbl 06861639
idMR: MR3758933
DOI: 10.14736/kyb-2017-6-1026
.
Date available: 2018-02-26T11:25:32Z
Last updated: 2018-05-25
Stable URL: http://hdl.handle.net/10338.dmlcz/147083
.
Reference: [1] L.Dai, Chen, C. H., Birge, J. R.: Convergence properties of two-stage stochastic programming..J. Optim. Theory Appl. 106 (2000), 489-509. MR 1797371, 10.1023/a:1004649211111
Reference: [2] Dupačová, J., Wets, R. J.-B.: Asymptotic behaviour of statistical estimates and optimal solutions of stochastic optimization problems..Ann. Statist. 16 (1984), 1517-1549. MR 0964937, 10.1214/aos/1176351052
Reference: [3] Dupačová, J., Hurt, J., Štěpán, J.: Stochastic Modelling in Economics and Finance..Kluwer, Dordrecht 2002. MR 2008457
Reference: [4] Hoeffding, W.: Probability inequalities for sums of bounded random variables..J. Amer. Statist. Assoc. 58 (1963), 301, 13-30. MR 0144363, 10.1080/01621459.1963.10500830
Reference: [5] Houda, M., Kaňková, V.: Empirical estimates in economic and financial optimization problems..Bull. Czech Econometr. Soc. 19 (2012), 29, 50-69.
Reference: [6] Kaniovski, Y. M., King, A. J., Wets, R. J.-B.: Probabilistic bounds (via large deviations) for the solutions of stochastic programming problems..Ann. Oper. Res. 56 (1995), 189-208. Zbl 0835.90055, MR 1339792, 10.1007/bf02031707
Reference: [7] Kaňková, V.: Optimum solution of a stochastic optimization problem with unknown parameters..In: Trans. 7th. Prague Conf. 1974, Academia, Prague 1977, pp. 239-244. MR 0519478
Reference: [8] Kaňková, V.: An approximative solution of stochastic optimization problem..In: Trans. 8th. Prague Conference, Academia, Prague 1978, pp. 349-353. MR 0536792, 10.1007/978-94-009-9857-5_33
Reference: [9] Kaňková, V.: Uncertainty in stochastic programming..In: Proc. Inter. Conf. on Stoch. Optim., Kiev 1984 (V. I Arkin and R. J.-B. Wets, eds.), Lecture Notes in Control and Information Sciences 81, Springer, Berlin 1986, pp. 393-401. MR 0891003, 10.1007/bfb0007116
Reference: [10] Kaňková, V.: On the stability in stochastic programming: the case of individual probability constraints..Kybernetika 33 (1997), 5, 525-546. Zbl 0908.90198, MR 1603961
Reference: [11] Kaňková, V., Houda, M.: Empirical estimates in stochastic programming..In: Proc. Prague Stochastics 2006 (M. Hušková and M. Janžura, eds.), MATFYZPRESS, Prague 2006, pp. 426-436. Zbl 1162.90528
Reference: [12] Kaňková, V.: Multistage stochastic programs via autoregressive sequences and individual probability constraints..Kybernetika 44 (2008), 2, 151-170. MR 2428217
Reference: [13] Kaňková, V.: Empirical estimates in optimization problems; survey with special regard to heavy tails and dependent samples..Bull.Czech Econometric. soc. 19 (2012), 30, 92-111.
Reference: [14] Kaňková, V., Houda, M.: Thin and heavy tails in stochastic programming..Kybernetika 51 (2015), 3, 433-456. MR 3391678, 10.14736/kyb-2015-3-0433
Reference: [15] Kaňková, V.: Scenario generation via ${\cal L}_{1} $ norm..In: Proc. 33rd Inter. Conf. Mathematical Methods in Economics 2015 (D. Marinčík, J. Ircingová and P. Janeček, eds.), Published by West Bohemia, Plzeň 2015, pp. 331-336.
Reference: [16] Kaňková, V.: A note on optimal value of loans..In: Proc. 34th Inter. Conf. Mathematical methods in economics 2016 (A. Kocourek and M. Vavroušek, eds.), Technical University Liberec, Liberec 2016, pp, 371-376.
Reference: [17] Luderer, B., Nollau, V., Vetters, K.: Mathematical Formulas for Economists. Third edition..Springer Science and Media, 2006. MR 1614635, 10.1007/978-3-662-12431-4
Reference: [18] Pflug, G. Ch.: Scenarion tree generation for multiperiod finncial optimization by optimal discretizatin..Math. Program. Ser. B 89 (2001), 251-271. MR 1816503, 10.1007/pl00011398
Reference: [19] Pflug, G. Ch.: Stochastic Optimization and Statistical Inference..In: Stochastic Programming, Handbooks in Operations Research and Managemennt Science, Vol. 10 (A. Ruszczynski and A. A. Shapiro, eds.), Elsevier, Amsterdam 2003, pp. 427-480. MR 2051793, 10.1016/s0927-0507(03)10007-2
Reference: [20] Rockafellar, R., Wets, R. J. B.: Variational Analysis..Springer, Berlin 1983. Zbl 0888.49001, 10.1007/978-3-642-02431-3
Reference: [21] Römisch, W., Schulz, R.: Stability of solutions for stochastic programs with complete recourse..Math. Oper. Res. 18 (1993), 590-609. MR 1250562, 10.1287/moor.18.3.590
Reference: [22] Römisch, W.: Stability of Stochastic Programming Problems..In: Stochastic Programming, Handbooks in Operations Research and Managemennt Science, Vol. 10 (A. Ruszczynski and A. A. Shapiro, eds.), Elsevier, Amsterdam 2003, pp. 483-554. MR 2051791, 10.1016/s0927-0507(03)10008-4
Reference: [23] Salinetti, G., Wets, R. J. B.: On the convergence of closed-valued measurable multifunctions..Trans. Amer. Math. Society 266 (1981), 1, 275-289. MR 0613796, 10.1090/s0002-9947-1981-0613796-3
Reference: [24] Schulz, R.: Rates of convergence in stochastic programs with complete integer recourse..SIAM J. Optim. 6 (1996), 4, 1138-1152. MR 1416533, 10.1137/s1052623494271655
Reference: [25] Shapiro, A.: Quantitative stability in stochastic programming..Math. Program. 67 (1994), 99-108. Zbl 0828.90099, MR 1300821, 10.1007/bf01582215
Reference: [26] Shapiro, A., Dentcheva, D., Ruszczynski, A.: Lectures on Stochastic Programming (Modeling and Theory)..Published by Society for Industrial and Applied Mathematics and Mathematical Programming Society, Philadelphia 2009. Zbl 1302.90003, MR 2562798, 10.1137/1.9780898718751
Reference: [27] Šmíd, M.: The expected loss in the discretization of multistage stochastic programming problems-estimation and convergence rate..Ann. Oper. Res. 165 (2009), 29-45. MR 2470981, 10.1007/s10479-008-0355-9
Reference: [28] Šmíd, M., Dufek, J.: Multi-period Factor Model of Loan Portfolio (July 10, 2016).. 10.2139/ssrn.2703884
Reference: [29] Shorack, G. R., Wellner, J. A.: Empirical Processes and Applications to Statistics..Wiley, New York 1986. MR 0838963, 10.1137/1.9780898719017
Reference: [30] Wets, R. J. B.: A Statistical Approach to the Solution of Stochastic Programs with (Convex) Simple Recourse..Research Report, University Kentucky 1974. MR 0727454
.

Files

Files Size Format View
Kybernetika_53-2017-6_5.pdf 374.1Kb application/pdf View/Open
Back to standard record
Partner of
EuDML logo