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Alan Greenspan, the quants and stochastic optimal control

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  • Stein, Jerome L.

Abstract

Alan Greenspan's paper (March 2010) presents his retrospective view of the crisis. His theme has several parts. First, the housing price bubble, its subsequent collapse and the financial crisis were not predicted either by the market, the FED, the IMF or the regulators in the years leading to the current crisis. Second, financial intermediation tried to function on too thin layer of capital - high leverage - owing to a misreading of the degree of risk embodied in ever more complex financial products and markets. Third, the breakdown was unpredictable and inevitable, given the 'excessive' leverage - or low capital - of the financial intermediaries. The proposed legislation for the 'reform' of the financial system requires that the FED "identify, measure, manage and mitigate risks to the financial stability of the United States". The focus is upon capital requirements or debt ratios. The 'Quants' ignored systemic risk and just focused upon risk transfer in very liquid markets. The FED, IMF, Treasury and the 'Quants'/market lacked the appropriate tools of analysis to answer the following questions: what is an optimal leverage or capital requirement that balances the expected growth against risk? What are theoretically founded early warning signals of a crisis? The author explains why the application of stochastic optimal control (SOC)/dynamic risk management is an effective approach to determine the optimal degree of leverage, the optimum and excessive risk and the probability of a debt crisis. The theoretically derived early warning signal of a crisis is the excess debt ratio, equal to the difference between the actual and optimal ratio. The excess debt starting from 2004-05 indicated that a crisis was most likely. This SOC analysis should be used by those charged with surveillance of financial markets.

Suggested Citation

  • Stein, Jerome L., 2010. "Alan Greenspan, the quants and stochastic optimal control," Economics Discussion Papers 2010-17, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwedp:201017
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    References listed on IDEAS

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    1. Stein, Jerome L., 2006. "Stochastic Optimal Control, International Finance, and Debt Crises," OUP Catalogue, Oxford University Press, number 9780199280575.
    2. Fleming, Wendell H. & Stein, Jerome L., 2004. "Stochastic optimal control, international finance and debt," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 979-996, May.
    3. Kristopher Gerardi & Andreas Lehnert & Shane M. Sherlund & Paul Willen, 2008. "Making Sense of the Subprime Crisis," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 39(2 (Fall)), pages 69-159.
    4. Eckhard Platen & Rolando Rebolledo, 1996. "Principles for modelling financial markets," Published Paper Series 1996-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Stein, Jerome L., 2010. "A tale of two debt crises: a stochastic optimal control analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-24.
    6. Shojai, Shahin & Feiger, George, 2010. "Economists’ hubris – the case of risk management," Journal of Financial Transformation, Capco Institute, vol. 28, pages 27-35.
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    More about this item

    Keywords

    Stochastic optimal control; warning signals of crisis; optimal leverage and debt ratios;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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