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The Contributions of Professors Fischer Black, Robert Merton, and Myron Scholes to the Financial Services Industry

Author

Listed:
  • Terry Marsh

    (Walter A. Haas School of Business, U. C. Berkeley)

  • Takao Kobayashi

    (Faculty of Economics, University of Tokyo)

Abstract

This paper is written as a tribute to Professors Robert Merton and Myron Scholes, winners of the 1997 Nobel Prize in economics, as well as to their collaborator, the late Professor Fischer Black. We first provide a brief and very selective review of their seminal work in contingent claims pricing. We then provide an overview of some of the recent research on stock price dynamics as it relates to contingent claim pricing. The continuing intensity of this research, some 25 years after the publication of the original Black-Scholes paper, must surely be regarded as the ultimate tribute to their work. We discuss jump-diffusion and stochastic volatility models, subordinated models, fractal models, and generalized binomial tree models, for stock price dynamics and option pricing. We also address questions as to whether derivatives trading poses a systemic risk in the context of models in which stock price movements are endogenized, and give our views on the "LTCM crisis" and liquidity risk.

Suggested Citation

  • Terry Marsh & Takao Kobayashi, 2001. "The Contributions of Professors Fischer Black, Robert Merton, and Myron Scholes to the Financial Services Industry," CIRJE F-Series CIRJE-F-120, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2001cf120
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    References listed on IDEAS

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    1. Jackwerth, Jens Carsten, 1996. "Generalized Binomial Trees," MPRA Paper 11635, University Library of Munich, Germany, revised 12 May 1997.
    2. Andersen, Torben G & Bollerslev, Tim, 1997. "Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    3. Marsh, Terry A. & Takao Kobayashi, 1998. ""The Work of Fischer Black, Robert Merton, and Myron Scholes, and its Continuing Legacy"," CIRJE F-Series 98-F-4, CIRJE, Faculty of Economics, University of Tokyo.
    4. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
    5. Geske, Robert & Shastri, Kuldeep, 1985. "Valuation by Approximation: A Comparison of Alternative Option Valuation Techniques," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 20(1), pages 45-71, March.
    6. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    7. Hirato Kuwahara & Terry A. Marsh, 2000. "Why Doesn't the Black‐‐Scholes Model Fit Japanese Warrants and Convertible Bonds?," International Review of Finance, International Review of Finance Ltd., vol. 1(3), pages 195-227, September.
    8. Ho, Thomas S Y & Lee, Sang-bin, 1986. "Term Structure Movements and Pricing Interest Rate Contingent Claims," Journal of Finance, American Finance Association, vol. 41(5), pages 1011-1029, December.
    9. Ding, Zhuanxin & Granger, Clive W. J., 1996. "Modeling volatility persistence of speculative returns: A new approach," Journal of Econometrics, Elsevier, vol. 73(1), pages 185-215, July.
    10. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    11. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    12. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    13. Grossman, Sanford J, 1988. "An Analysis of the Implications for Stock and Futures Price Volatility of Program Trading and Dynamic Hedging Strategies," The Journal of Business, University of Chicago Press, vol. 61(3), pages 275-298, July.
    14. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    15. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    16. Rüdiger Frey & Alexander Stremme, 1997. "Market Volatility and Feedback Effects from Dynamic Hedging," Mathematical Finance, Wiley Blackwell, vol. 7(4), pages 351-374, October.
    17. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-1261, December.
    18. Sanjiv Ranjan Das & Rangarajan K. Sundaram, 1997. "Taming the Skew: Higher-Order Moments in Modeling Asset Price Processes in Finance," NBER Working Papers 5976, National Bureau of Economic Research, Inc.
    19. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
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