The AURORA Financial Management System: Model and Parallel Implementation Design

Annals of Operations Research

Volumn 99, Issue 1-4, 2000, Pages 189-206

  Pflug, G Ch ^a   Swietanowski A ^a   Dockner, E ^a   Moritsch, H ^a  

^a UNIVERSITY OF VIENNA   (Austria)

Author keywords

Asset liability management; Financial management; Parallel algorithms; Stochastic optimization

Indexed keywords

EID: 0041687739     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1023/a:1019297118383     Document Type: Article

References (40)

1. Ph. Artzner, F. Delbaen, J.-M. Eber and D. Heath, Coherent measures of risk, Mathematical Finance 9 (1999) 203-228.
2. D.P. Bertsekas, Constrained Optimization and Lagrange Multiplier Methods (Academic Press, 1982).
3. J.R. Birge, Decomposition and partitioning methods for multistage stochastic linear programs, Operations Research 33 (1985) 989-1007.
4. J.R. Birge and L. Qi, Computing block-angular Karmarkar projections with applications to stochastic programming, Management Science 34(12) (1990).
5. R.E. Bixby, Progress in linear programming, ORSA J. on Computing 6(1) (1994) 15-22.
6. F. Black, E. Derman and W. Toy, A one-factor model of interest rates and its application to tresury bond options, Financial Analysts Journal 3 (January/February 1990) 33-39.
7. M.J. Brennan, E.S. Schwartz and R. Lagnado, Strategic asset allocation, Journal of Economic Dynamics and Control 21 (1997) 1377-1403.
8. D.R. Cariño, T. Kent, D.H. Myers, C. Stacy, M. Sylvanus, A.L. Turner, K. Watanabe and W.T. Ziemba, The Russell-Yasuda Kasai model: an asset/liability model for a Japanese insurance company using multistage stochastic programming, Interfaces 24 (1994) 29-49.
9. J.C. Cox, J.E. Ingersoll and S.A. Ross, A theory of terms of interest rates, Econometrica 53 (1985) 385-407.
10. G.B. Dantzig and P. Wolfe, Decomposition principle for linear programs, Operations Research 8 (1960) 101-111.
11. M.A.H. Dempster and R.T. Thompson, Parallelization and aggregation of nested Benders decomposition, Working paper WP 01/95, The Judge Institute of Management Studies, Cambridge University (1995).
12. J. Dupacova, Stochastic programming models in banking, Working paper, International Institute for Applied Systems Analysis (1991).
13. A. Gupta, G. Karypis and V. Kumar, Highly scalable parallel algorithms for sparse matrix factorization, IEEE Transactions on Parallel and Distributed Systems 8(5) (1997).
14. P. Hoel, S. Port and Ch. Stone, Introduction to Stochastic Processes (Houghton-Mifflin, Boston, 1972).
15. P. Kall and S.W. Wallace, Stochastic Programming (Wiley, Chichester, 1994).
16. S. Karlin and H. Taylor, A Second Course in Stochastic Processes (Academic Press, Boston, 1993).
17. H. Konno and H. Yamazaki, Mean absolute deviation portfolio optimization model and its applications to Tokyo stock market, Management Science 37 (1991) 519-531.
18. M.I. Kusy and W.T. Ziemba, A bank asset and liability management model, Operations Research 34 (1986) 356-376.
19. H. Markowitz, Portfolio selection, Journal of Finance 7 (1952) 77-91.
20. J.M. Mulvey, Nonlinear network models in finance, in: Advances in Mathematical Programming and Financial Planning (JAI Press, 1987).
21. J.M. Mulvey, An asset-liability investment system, Interfaces 24 (1994) 22-33.
22. J.M. Mulvey, Multi-stage financial planning systems, in: Operations Research Models in Quantitative Finance, eds. R.L. D'Ecclesia and S.A. Zenios (Physica-Verlag, 1994) pp. 18-35.
23. J.M. Mulvey and A. Ruszczyński, A diagonal quadratic approximation method for large-scale linear programs, Operations Research Letters 12 (1992) 205-215.
24. J.M. Mulvey and A. Ruszczyński, A new scenario decomposition method for large-scale stochastic optimization, Operations Research 43 (1995) 477-490.
25. J.M. Mulvey and W.T. Ziemba, Worldwide Asset and Liability Modeling (Cambridge University Press, 1998).
26. J.M. Mulvey and H. Vladimirou, Stochastic network programming for financial planning problems, Management Science 38 (1992) 1642-1664.
27. V. Norkin, G.Ch. Pflug and A. Ruszczyński, A branch and bound method for stochastic global optimization, Mathematical Programming 83 (1998) 425-450.
28. W. Ogryczak and A. Ruszczyński, From stochastic dominance to mean-risk models: Semideviations as risk measures, European Journal of Operations Research 116 (1999) 33-50.
29. G.Ch. Pflug, Risk-reshaping contracts and stochastic optimization, Central European Journal of Operations Research 5(3-4) (1998) 205-230.
30. G.Ch. Pflug, How to Measure Risk? Festschrift to F. Ferschl (Physica-Verlag, 1999).
31. G.Ch. Pflug and A. Świȩtanowski, Dynamic asset allocation under uncertainty for pension fund management, Control and Cybernetics 28(4) (1999).
32. A. Ruszczyński and A. Świȩtanowski, Accelerating the regularized decomposition method for two stage stochastic linear problems, European Journal of Operations Research 101(2) (1997) 328-342.
33. A. Ruszczyński, An augmented Lagrangian decomposition method for block diagonal linear programming problems, Operations Research Letters 8 (1989) 287-294.
34. A. Ruszczyński, Interior point methods in stochastic programming, Technical Report WP-93-8, International Institute for Applied Systems Analysis, Laxenburg, Austria (1993).
35. A. Ruszczyński, Parallel decomposition of multistage stochastic programming problems, Mathematical Programming 58 (1993) 201-228.
36. A. Ruszczyński, On convergence of an augmented Lagrangian decomposition method for sparse convex optimization, Mathematics of Operations Research 20(3) (1995) 634-656.
37. O.A. Vasicek, An equilibrium characterization of the term structure, J. Financial Economics 5 (1977) 177-18.
38. H. Vladimirou and S.A. Zenios, Scalable parallel computations for large-scale stochastic programming, Annals of Operations Research 90 (1999) 87-129.
39. S.A. Zenios, Financial Optimization (Cambridge University Press, 1993).
40. S.A. Zenios and R.L. D'Ecclesia, eds., Operations Research Models in Quantitative Finance (Springer, 1994).