Encyclopedia of Operations Research and Management Science

2001 Edition
| Editors: Saul I. Gass, Carl M. Harris

Financial markets

  • John Board
  • Charles Sutcliffe
  • William Ziemba
Reference work entry
First Online:
DOI: https://doi.org/10.1007/1-4020-0611-X_341
How to cite

Over the last half-century, a strong relationship be-tween operations research (OR) and finance has developed, resulting in a large and rapidly growing literature. Although most applications have been of OR techniques to finance, finance problems have also stimulated the development and refinement of OR techniques.

Finance problems, and especially those relating to financial markets, are particularly well suited to analysis using OR techniques. These problems are generally separable and well defined, have a clear objective (often to maximize profit or minimize risk), and have variables which are quantified in monetary terms. The relationships between the variables in finance models are usually stable and well defined, so that the resulting OR model is a good representation of the problem. As there are few concerns about human behavior ruling out the implementation of some solutions, the solutions produced by the analysis can usually be implemented. In addition, large amounts of data,...

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

References

  1. [1]
    Ahmadi, H. (1993). “Testability of the Arbitrage Pricing Theory by Neural Networks.” In Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance, edited by R.R. Trippi and E. Turban, Probus Publishing, Chicago, 421–432. Google Scholar
  2. [2]
    Alexander, G.J. and Resnick, B.G. (1985). “Using Linear and Goal Programming to Immunize Bond Portfolios,” Jl. Banking and Finance, 9(1), 35–54.Google Scholar
  3. [3]
    Ashford, R.W., Berry, R.H., and Dyson, R.G. (1988). “Operational Research and Financial Management,” European Jl. Operations Research, 36(2), 143–152.Google Scholar
  4. [4]
    Barr, R.S., Seiford, L.M., and Siems, T.F. (1993). “An Envelopment Analysis Approach to Measuring the Managerial Efficiency of Banks,” Annals Operations Research, 45(1–4), 1–19.Google Scholar
  5. [5]
    Bauer, P.W., Berger, A.N., Ferrier, G.D., and Humphrey, D.B. (1998). “Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods,” Jl. Economics and Business, 50(2), 85–114.Google Scholar
  6. [6]
    Ben-Dov, Y., Hayre, L., and Pica, V. (1992). “Mortgage Valuation Models at Prudential Securities,” Interfaces, 22(1), 55–71.Google Scholar
  7. [7]
    Ben-Horim, M. and Silber, W.L. (1977). “Financial Innovation: A Linear Programming Approach, Jl. Banking and Finance, 1(3), 277–296.Google Scholar
  8. [7]
    Bertsimas, D. and Lo, A.W. (1998). “Optimal Control of Execution Costs,” Jl. Financial Markets, 1(1), 1–50.Google Scholar
  9. [8]
    Bierman, H. (1966). “The Bond Size Decision,” Jl. Financial and Quantitative Analysis, 1(4), 1–14.Google Scholar
  10. [9]
    Board, J.L.G. and Sutcliffe, C.M.S. (1994). “Estimation Methods in Portfolio Selection and the Effectiveness of Short Sales Restrictions: UK Evidence,” Management Science, 40, 516–534.Google Scholar
  11. [10]
    Board, J.L.G., Sutcliffe, C.M.S., and Ziemba, W.T. (2000). “Portfolio Theory: Mean-Variance.” In Encyclopedia of Operations Research and Management Science, S.I. Gass and C.M. Harris, eds., Kluwer Academic Publishing, Boston-Dordrecht-London.Google Scholar
  12. [11]
    Boyle, P.P. (1977). “Options: A Monte Carlo Approach,” Jl. Financial Economics, 4(3), 323–338.Google Scholar
  13. [12]
    Boyle, P.P. (1989). “Valuing Canadian Mortgage Backed Securities,” Financial Analysts Jl., 45(3), 55–60.Google Scholar
  14. [13]
    Boyle, P.P., Broadie, M., and Glasserman, P. (1997). “Monte Carlo Methods for Security Pricing,” Jl. Economic Dynamics and Control, 21, 1267–1321.Google Scholar
  15. [14]
    Bradley, S.P. and Crane, D.B. (1972). “A Dynamic Model for Bond Portfolio Management,” Management Science, 19, 139–151.Google Scholar
  16. [15]
    Brick, I.E., Mellon, W.G., Surkis, J., and Mohl, M. (1983). “Optimal Capital Structure: A Multi Period Programming Model for Use in Financial Planning,” Jl. Banking and Finance, 7(1), 45–67.Google Scholar
  17. [16]
    Broadie, M. and Glasserman, P. (1996). “Estimating Security Price Derivatives Using Simulation,” Management Science, 42, 269–285.Google Scholar
  18. [17]
    Broadie, M. and Glasserman, P. (1997). “Pricing American Style Securities Using Simulation,” Jl. Economic Dynamics and Control, 21, 1323–1352.Google Scholar
  19. [18]
    Cariño, D.R., Kent, T., Myers, D.H., Stacy, C., Sylvanus, M., Turner, A.L., Watanabe, K., and Ziemba, W.T. (1994). The Russell-Yasuda Kasai Model: An Asset-Liability Model for a Japanese Insurance Company Using Multistage Stochastic Programming, Interfaces, 24(1), 29–49. Reprinted in Ziemba and Mulvey (1998).Google Scholar
  20. [19]
    Cariño, D.R. and Ziemba, W.T. (1998a). “Formulation of the Russell Yasuda Kasai Financial Planning Model,” Operations Research, 46, 433–449.Google Scholar
  21. [20]
    Cariño, D.R., Myers, D., and Ziemba, W.T. (1998b). “Concepts, Technical Issues and Uses of the Russell Yasuda Kasai Model,” Operations Research, 46, 450–462.Google Scholar
  22. [21]
    Christofides, N., Hewins, R.D., and Salkin, G.R. (1979). “Graph Theoretic Approaches to Foreign Exchange,” Jl. Financial and Quantitative Analysis, 14, 481–500. Google Scholar
  23. [22]
    Consiglio, A. and Zenios, S.A. (1997a). “A Model for Designing Callable Bonds and its Solution Using Tabu Search,” Jl. Economic Dynamics and Control, 21, 1445–1470.Google Scholar
  24. [23]
    Consiglio, A. and Zenios, S.A. (1997b). “High Performance Computing for the Computer Aided Design of Financial Products.” In Advances in High Performance Computing edited by L. Grandinetti, J. Kowalik and M. Vajtersic, NATO Advanced Science Institute Series, vol 30, Kluwer Academic Publishers, 273–302. Google Scholar
  25. [24]
    Dahl, H., Meeraus, A., and Zenios, S.A. (1993). “Some Financial Optimization Models: II Financial Engineering.” In Financial Optimization, edited by S.A. Zenios, Cambridge University Press, 37–71. Google Scholar
  26. [25]
    Del Angel, G.F., Márquez, A., and Patiño, E.P. (1998). “A Discrete Markov Chain Model for Valuing Loan Portfolios. The Case of Mexican Loan Sales,” Jl. Banking and Finance, 22, 1457–1480.Google Scholar
  27. [26]
    Dempster, M.A.H. and Hutton, J.P. (1996). “Pricing American Stock Options by Linear Programming, Working Paper,” Department of Mathematics, University of Essex, October, 34 pages. Google Scholar
  28. [27]
    Dempster, M.A.H., Hutton, J.P., and Richards, D.G. (1998). “LP Valuation of Exotic American Options Exploiting Structure,” Working paper, Judge Institute of Management Studies, University of Cambridge, WP 27/98, September. Google Scholar
  29. [28]
    Dixit, A.K. and Pindyck, R.S. (1994). Investment Under Uncertainty, Princeton University Press, New Jersey.Google Scholar
  30. [29]
    Dryden, M.M. (1968). “Short-Term Forecasting of Share Prices: An Information Theory Approach,” Scottish Jl. Political Economy, 15, 227–249.Google Scholar
  31. [30]
    Dryden, M.M. (1969). “Share Price Movements: A Markovian Approach,” Jl. Finance, 24, 49–60.Google Scholar
  32. [31]
    Dutta, P.K. and Madhavan, A. (1997). “Competition and Collusion in Dealer Markets,” Jl. Finance, 52, 245–276.Google Scholar
  33. [32]
    Elimam, A.A., Girgis, M., and Kotob, S. (1996). “The Use of Linear Programming in Disentangling the Bankruptcies of Al-Manakh Stock Market Crash,” Operations Research, 44, 665–676.Google Scholar
  34. [33]
    Elimam, A.A., Girgis, M., and Kotob, S. (1997). “A Solution to Post Crash Debt Entanglements in Kuwait's al-Manakh Stock Market,” Interfaces, 27(1), 89–106.Google Scholar
  35. [34]
    Elton, E.J. and Gruber, M.J. (1971). “Dynamic Programming Applications in Finance,” Jl. Finance, 26, 473–506.Google Scholar
  36. [35]
    Fong, H.G. and Vasicek, O. (1983). “The Tradeoff Between Return and Risk in Immunized Portfolios,” Financial Analysts Jl., 39(5), 73–78.Google Scholar
  37. [36]
    Golub, B., Holmer, M., McKendall, R., Pohlman, L., and Zenios, S.A. (1995). “A Stochastic Programming Model for Money Management,” European Jl. Operational Research, 85, 282–296.Google Scholar
  38. [37]
    Goonatilake, S. and Treleaven, P., eds. (1995). Intelligent Systems for Finance and Business, John Wiley, New York.Google Scholar
  39. [38]
    Grant, D., Vora, G., and Weeks, D. (1997). “Path Dependent Options: Extending the Monte Carlo Simulation Approach,” Management Science, 43, 1589–1602.Google Scholar
  40. [39]
    Heian, B.C. and Gale, J.R. (1988). “Mortgage Selection Using a Decision Tree Approach: An Extension,” Interfaces, 18(4), 72–81.Google Scholar
  41. [40]
    Holmer, M.R., Yang, D., and Zenios, S.A. (1998). “Designing Callable Bonds Using Simulated Annealing.” In Operational Tools in the Management of Financial Risks, edited by C., Zopounidis, Kluwer Academic Publishers, 177–196. Google Scholar
  42. [41]
    Hong, H.K. (1981). “Finance Mix and Capital Structure,” Jl. Business Finance and Accounting, 8, 485–491.Google Scholar
  43. [42]
    Hutchinson, J.M., Lo, A.W., and Poggio, T. (1994). “A Non-Parametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks,” Jl. Finance, 49, 851–889.Google Scholar
  44. [43]
    Klaassen, P. (1998). “Financial Asset-Pricing Theory and Stochastic Programming Models for Asset/Liability Management: A Synthesis,” Management Science, 44, 31–48.Google Scholar
  45. [44]
    Konno, H. and Yamazaki, H. (1991). “Mean Absolute Deviation Portfolio Optimization Model and its Applications to Tokyo Stock Market,” Management Science, 37, 519–531.Google Scholar
  46. [45]
    Konno, H. and Yamazaki, H. (1997). “An Integrated Stock-Bond Portfolio Optimization Model, Jl. Economic Dynamics and Control,” 21, 1427–1444.Google Scholar
  47. [46]
    Kornbluth, J.S.H. and Salkin, G.R. (1987). The Management of Corporate Financial Assets: Applications of Mathematical Programming Models, Academic Press, London.Google Scholar
  48. [47]
    Kraus, A. (1973). “The Bond Refunding Decision in an Efficient Market,” Jl. Financial and Quantitative Analysis, 8, 793–806.Google Scholar
  49. [48]
    Kumar, P.C. and Philippatos, G.C. (1979). “Conflict Resolution in Investment Decisions: Implementation of Goal Programming Methodology for Dual Purpose Funds,” Decision Sciences, 10, 562–576.Google Scholar
  50. [49]
    Kumar, P.C., Philippatos, G.C., and Ezzell, J.R. (1978). “Goal Programming and the Selection of Portfolios by Dual Purpose Funds,” Jl. Finance, 33, 303–310.Google Scholar
  51. [50]
    Lee, S.M. and Eom, H.B. (1989). “A Multi Criteria Approach to Formulating International Project Financing Strategies,” Jl. Operational Research Society, 40, 519–528.Google Scholar
  52. [51]
    Lee, S.M. and Lerro, A.J. (1973). “Optimizing the Portfolio Selection for Mutual Funds, Jl. Finance,” 28, 1087–1101.Google Scholar
  53. [52]
    Litzenberger, R.H. and Rutenberg, D.P. (1972). “Size and Timing of Corporate Bond Flotations,” Jl. Financial and Quantitative Analysis, 7, 1343–1359.Google Scholar
  54. [53]
    Luna, R.E. and Reid, R.A. (1986). “Mortgage Selection Using a Decision Tree Approach, Interfaces,” 16(3), 73–81.Google Scholar
  55. [54]
    Markowitz, H. (1952). “Portfolio Selection,” Jl. Finance, 7, 77–91.Google Scholar
  56. [55]
    Markowitz, H. (1987). Mean-Variance in Portfolio Choice and Capital Markets, Blackwell, London.Google Scholar
  57. [56]
    Meade, N. and Salkin, G.R. (1989). “Index Funds — Construction and Performance Measurement,” Jl. Operational Research Society, 40, 871–879.Google Scholar
  58. [57]
    Meade, N. and Salkin, G.R. (1990). “Developing and Maintaining an Equity Index Fund,” Jl. Operational Research Society, 41, 599–607.Google Scholar
  59. [58]
    Morgan, J.P. and Reuters (1996). RiskMetrics™ — Technical Document, Morgan Guarantee Trust Company of New York. Google Scholar
  60. [59]
    Morgan, J.P. (1997). CreditMetrics™ — Technical Document, Morgan Guarantee Trust Company of New York. Google Scholar
  61. [60]
    Mulvey, J.M. (1987). “Nonlinear Network Models in Finance.” In Advances in Mathematical Programming and Financial Planning, K.D. Lawrence, J.B. Guerard and G.R. Reeves, eds., vol. 1, JAI Press, 253–271. Google Scholar
  62. [61]
    Mulvey, J.M. (1994). “An Asset Liability Investment System,” Interfaces, 24(3), 22–33.Google Scholar
  63. [62]
    Mulvey, J.M. and Vladimirou, H. (1992). “Stochastic Network Programming for Financial Planning Problems,” Management Science, 38, 1642–1664.Google Scholar
  64. [63]
    Murtagh, B.A. (1989). “Optimal Use of Currency Options,” Omega, 17, 189–192.Google Scholar
  65. [64]
    Nawalkha, S.K. and Chambers, D.R. (1996). “An Improved Immunization Strategy: M-Absolute,” Financial Analysts Jl., 52(5), 69–76.Google Scholar
  66. [65]
    O'Hara, M. (1995). Market Microstructure Theory, Blackwell, London.Google Scholar
  67. [66]
    Paskov, S.H. (1997). “New Methodologies for Valuing Derivatives.” In Mathematics of Derivative Securities, Michael A.H. Dempster and S.R. Pliska, eds., Cambridge University Press, 545–582. Google Scholar
  68. [67]
    Perold, A.F. (1984). “Large Scale Portfolio Optimization,” Management Science, 30, 1143–1160.Google Scholar
  69. [68]
    Peterson, P.E. and Leuthold, R.M. (1987). “A Portfolio Approach to Optimal Hedging for a Commercial Cattle Feedlot,” Jl. Futures Markets, 7, 443–457.Google Scholar
  70. [69]
    Powers, I.Y. (1987). “A Game Theoretic Model of Corporate Takeovers by Major Stockholders,” Management Science, 33, 467–483.Google Scholar
  71. [70]
    Premachandra, I., Powell, J.G. and Shi, J. (1998). “Measuring the Relative Efficiency of Fund Management Strategies in New Zealand Using a Spreadsheet-based Stochastic Data Envelopment Analysis Model,” Omega, 26, 319–331.Google Scholar
  72. [71]
    Refenes, A. P., ed. (1995). Neural Networks in the Capital Markets, John Wiley, New York.Google Scholar
  73. [72]
    Rudd, A. (1980). “Optimal Selection of Passive Portfolios,” Financial Management, 9(1), 57–66.Google Scholar
  74. [73]
    Rudd, A. and Schroeder, M. (1982). “The Calculation of Minimum Margin,” Management Science, 28, 1368–1379.Google Scholar
  75. [74]
    Seix, C. and Akhoury, R. (1986). “Bond Indexation: The Optimal Quantitative Approach,” Jl. Portfolio Management, 12(3), 50–53.Google Scholar
  76. [75]
    Shanker, L. (1993). “Optimal Hedging Under Indivisible Choices,” Jl. Futures Markets, 13, 237–259.Google Scholar
  77. [76]
    Sharda, R. (1987). “A Simple Model to Estimate Bounds on Total Market Gains and Losses for a Particular Stock,” Interfaces, 17(5), 43–50.Google Scholar
  78. [77]
    Sharpe, W.F. (1963). “A Simplified Model for Portfolio Analysis,” Management Science, 9, 277–293.Google Scholar
  79. [78]
    Sharpe, W.F. (1967). “A Linear Programming Algorithm for Mutual Fund Portfolio Selection,” Management Science, 13, 499–510.Google Scholar
  80. [79]
    Sharpe, W.F. (1971). “A Linear Programming Approximation for the General Portfolio Analysis Problem,” Jl. Financial and Quantitative Analysis, 6, 1263–1275.Google Scholar
  81. [80]
    Taha, H.A. (1991). “Operations Research Analysis of a Stock Market Problem,” Computers and Operations Research, 18, 597–602.Google Scholar
  82. [81]
    Trippi, R.R. and Turban, E., eds. (1993). Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance, Probus Publishing, Chicago. Google Scholar
  83. [82]
    Vassiadou-Zeniou, C. and Zenios, S.A. (1996). “Robust Optimization Models for Managing Callable Bond Portfolios,” European Jl. Operational Research, 91, 264–273.Google Scholar
  84. [83]
    Weingartner, H.M. (1967). “Optimal Timing of Bond Refunding,” Management Science, 13, 511–524.Google Scholar
  85. [84]
    Wong, K. and Selvi, Y. (1998). “Neural Network Applications in Finance: A Review and Analysis of Literature (1990–1996),” Information and Management, 34(3), 129–139.Google Scholar
  86. [85]
    Worzel, K.J., Vassiadou-Zeniou, C., and Zenios, S.A. (1994). “Integrated Simulation and Optimization Models for Tracking Indices of Fixed Income Securities,” Management Science, 42, 223–233.Google Scholar
  87. [86]
    Yawitz, J.B., Hempel, G.H., and Marshall, W.J. (1976). “A Risk-Return Approach to the Selection of Optimal Government Bond Portfolios,” Financial Management, 5(3), 36–45.Google Scholar
  88. [87]
    Zenios, S.A. (1991). “Massively Parallel Computations for Financial Planning Under Uncertainty.” In Very Large Scale Computation in the 21st Century, J.P. Mesirov, ed., Society for Industrial and Applied Mathematics, Philadelphia, 273–294.Google Scholar
  89. [88]
    Zenios, S.A. (1993a). “Parallel Monte Carlo Simulation of Mortgage Backed Securities.” In Financial Optimization, S.A. Zenios, ed., Cambridge University Press, 325–343. Google Scholar
  90. [89]
    Zenios, S.A. (1993b). “A Model for Portfolio Management with Mortgage Backed Securities,” Annals Operations Research, 43, 337–356.Google Scholar
  91. [90]
    Zenios, S.A., Holmer, M.R., McKendall, R., and Vassiadou-Zeniou, C. (1998). “Dynamic Models for Fixed Income Portfolio Management Under Uncertainty,” Jl. Economic Dynamics and Control, 22, 1517–1541.Google Scholar
  92. [91]
    Zenios, S.A. and Kang, P. (1993). “Mean Absolute Deviation Portfolio Optimization for Mortgage Backed Securities,” Annals Operations Research, 45, 433–450.Google Scholar
  93. [92]
    Ziemba, W.T. and Mulvey, J.M., eds. (1998). Worldwide Asset and Liability Modelling, Cambridge University Press. Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • John Board
    • 1
  • Charles Sutcliffe
    • 2
  • William Ziemba
    • 3
  1. 1.London School of Economics and Political ScienceLondonUK
  2. 2.The University of SouthamptonSouthamptonUK
  3. 3.University of British ColumbiaVancouverCanada