Skip to main content

Computational Database Technology Applied to Option Pricing Via Finite Differences

  • Conference paper
Advances in Databases and Information Systems (ADBIS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4152))

  • 522 Accesses

Abstract

Computational database technology spans the two research fields data-base technology and scientific computing. It involves development of database capabilities that support computational-intensive applications found in science and engineering. This includes support for representing and processing of mathematical models within the database environment without any significant performance loss compared to conventional implementations.

This paper describes how an existing database management system, AMOS II, is extended with capabilities to solve the Black–Scholes equation commonly used in option pricing. The numerical method used is finite differences, and a flexible database framework that can deal with complex mathematical objects and numerical methods is created. We describe how computational data representations and operations are adapted to the database management system and the approach is evaluated with respect to performance, extensibility, and ease of use.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. The Earth Simulator web site (June 2006), http://www.es.jamstec.go.jp/esc/eng/

  2. Abiteboul, S., et al.: The Lowell database research self-assessment. Commun. ACM 48(5), 111–118 (2005)

    Article  Google Scholar 

  3. Åhlander, K.: An Object-Oriented Framework for PDE Solvers, PhD Thesis, Thesis No. 423, Uppsala University, Uppsala (1999)

    Google Scholar 

  4. Åkerlund, J.: A Computational Database for Black-Scholes Equation, MSc Thesis, Department of Information Technology, Uppsala University, Uppsala (June 2005)

    Google Scholar 

  5. The Amos II web site: (March 2006), http://user.it.uu.se/~udbl/amos/

  6. Bernstein, P., et al.: The Asilomar report on database research. SIGMOD Record 27(4), 74–80 (1998)

    Article  Google Scholar 

  7. Björk, T.: Arbitrage Theory in Continuous Time. Oxford University Press, Oxford (1998)

    Book  Google Scholar 

  8. The Linpack web site at NetLib (June 2006), http://www.netlib.org/linpack/

  9. The Lapack web site at NetLib (June 2006), http://www.netlib.org/lapack/

  10. Brown, D., et al.: Overture: An object-oriented framework for solving partial differential equations on overlapping grids. In: Henderson, M.E., Anderson, C.R., Lyons, S.L. (eds.) Object-oriented Methods for Interoperable Scientific and Engineering Computing, SIAM, Philadelphia (1999)

    Google Scholar 

  11. Bruaset, A.M., Langtangen, H.P.: Object-oriented design of preconditioned iterative methods in Diffpack. ACM Transactions on Mathematical Software 23, 50–80 (1997)

    Article  MATH  Google Scholar 

  12. Carey, M., Haas, L.: Extensible Database Management Systems. SIGMOD Record 19(4), 54–60 (1990)

    Article  Google Scholar 

  13. Conolly, T., Begg, C.: Database Systems - A Practical Approach to Design, Implementation and Management, 3rd edn. Addison-Wesley, Reading (2002)

    Google Scholar 

  14. Eijkhout, V.: LAPACK working note 50 - distributed sparse data structures for linear algebra operations (1992) (February 10, 2005), Available from: http://www.cs.utk.edu/~library/TechReports/1992/ut-cs-92-169.ps.Z

  15. Eggermont, R.: Sparse Matrix Compression Formats (February 10, 2005), Available from: http://ce.et.tudelft.nl/~robbert/sparse_matrix_compression.html

  16. Garcia-Molina, H., Salem, K.: Main memory database systems: an overview. IEEE Transactions on Knowledge and Data Engineering 4(6), 509–516 (1992)

    Article  Google Scholar 

  17. Gray, J., Compton, M.: A call to arms. Queue 3(3), 30–38 (2005)

    Article  Google Scholar 

  18. Gray, J., et al.: Scientific data management in the coming decade. SIGMOD Record 34(4), 34–41 (2005)

    Article  Google Scholar 

  19. Gustafsson, B., et al.: Time Dependent Problems and Difference Methods. John Wiley & Sons, Inc., Chichester (1995)

    MATH  Google Scholar 

  20. Heath, M.T.: Scientific Computing - An Introductory Survey, 2nd edn. McGraw-Hill, New York (2002)

    Google Scholar 

  21. Hull, J.C.: Options, Futures and other Derivatives, 4th edn. Prentice-Hall International, Inc., Englewood Cliffs (2000)

    Google Scholar 

  22. Löf, H.: Parallelizing the method of conjugate gradients for shared memory architectures, Uppsala University, Department of Information Technology, Uppsala (2004)

    Google Scholar 

  23. Nyström, M., Orsborn, K.: Computational Database Technology for Component Mode Synthesis. Advances in Engineering Software 35(10-11), 735–745 (2003)

    Article  Google Scholar 

  24. Orsborn, K.: On Extensible and Object-Relational Database Technology for Finite Element Analysis Applications. PhD Thesis, Thesis No. 452, Linköping University, Linköping (1996)

    Google Scholar 

  25. Orsborn, K., et al.: Representing matrices using multi-directional foreign functions. In: Gray, P.M.D., Kerschberg, L., King, P.J.H., Poulovassilis, A. (eds.) The Functional Approach to Data Management: Modeling, Analyzing and Integrating Heterogeneous Data, Springer, Heidelberg (2004)

    Google Scholar 

  26. Pantazopoulos, K.N., Houstos, E.N.: Modern software techniques in computational finance. In: Arge, E., Bruaset, A.M., Langtangen, H.P. (eds.) Modern Software Tools for Scientific Computing, Birkhäuser, pp. 227–246 (1997)

    Google Scholar 

  27. Risch, T., et al.: Functional data Integration in a distributed mediator system. In: Gray, P.M.D., Kerschberg, L., King, P.J.H., Poulovassilis, A. (eds.) The Functional Approach to Data Management: Modeling, Analyzing and Integrating Heterogeneous Data. Springer, Heidelberg (2004)

    Google Scholar 

  28. Saad, Y.: Iterative Methods for Sparse Linear Systems, 2nd edn. (2000), Available from: ftp://ftp.cd.umn.edu/dept/users/saad/ITBOOK.tar.gz

  29. Seltzer, M.: Beyond relational databases. Queue 3(3), 50–58 (2005)

    Article  Google Scholar 

  30. Silberschatz, A., Zdonik, S.: Strategic directions in database systems – breaking out of the box. ACM Computing Surveys 28(4), 764–778 (1996)

    Article  Google Scholar 

  31. Stonebraker, M., Brown, P.: Object-Relational DBMSs: Tracking the Next Great Wave. Morgan Kaufmann Publishers, Inc., San Francisco (1999)

    Google Scholar 

  32. Skavhaug, O.: Numerical Methods and Software with Applications in Computational Finance. PhD Thesis, Thesis No. 338, University of Oslo, Oslo (2004)

    Google Scholar 

  33. Saad, Y.: SPARSKIT: a basic tool kit for sparse matrix computations, version 2 (1994) (February 10, 2005), Available from: http://www-users.cs.umn.edu/~saad/software/SPARSKIT/paper.ps

  34. Tavella, D., Randall, C.: Pricing Financial Instruments - The Finite Difference Method. John Wiley & Sons, Inc., Chichester (2000)

    Google Scholar 

  35. Thuné, M., et al.: Object-oriented modeling of parallel PDE solvers. In: Boisvert, R.F., Tang, P.T.P. (eds.) The Architecture of Scientific Software, pp. 159–174. Kluwer Academic Publishers, Boston (2001)

    Google Scholar 

  36. Thuné, M., et al.: Object-oriented construction of parallel PDE solvers. In: Arge, E., Bruaset, A.M., Langtangen, H.P. (eds.) Modern Software Tools for Scientific Computing, Birkhäuser, pp. 203–226 (1997)

    Google Scholar 

  37. Wiederhold, G.: Information systems that really support decision-making. Journal of Intelligent Information Systems 14, 85–94 (2000)

    Article  Google Scholar 

  38. Willmott, P., Dewynne, J., Howison, S.: Option pricing - mathematical models and computation. Oxford Financial Press (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Åkerlund, J., Åhlander, K., Orsborn, K. (2006). Computational Database Technology Applied to Option Pricing Via Finite Differences. In: Manolopoulos, Y., Pokorný, J., Sellis, T.K. (eds) Advances in Databases and Information Systems. ADBIS 2006. Lecture Notes in Computer Science, vol 4152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827252_28

Download citation

  • DOI: https://doi.org/10.1007/11827252_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37899-0

  • Online ISBN: 978-3-540-37900-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics