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Parameter Estimation for Stock Models with Non-Constant Volatility Using Markov Chain Monte Carlo Methods

In: Operations Research Proceedings 2006

Author

Listed:
  • Markus Hahn

    (Austrian Academy of Sciences)

  • Wolfgang Putschögl

    (Austrian Academy of Sciences)

  • Jörn Sass

    (Austrian Academy of Sciences)

Abstract

We consider a model for a financial market where the asset prices satisfy a stochastic differential equation. For the volatility no new source of randomness is introduced, but the volatility at each time depends deterministically on all previous price fluctuations. Such non-constant volatility models preserve the completeness of the market while they allow for many attractive features.

Suggested Citation

  • Markus Hahn & Wolfgang Putschögl & Jörn Sass, 2007. "Parameter Estimation for Stock Models with Non-Constant Volatility Using Markov Chain Monte Carlo Methods," Operations Research Proceedings, in: Karl-Heinz Waldmann & Ulrike M. Stocker (ed.), Operations Research Proceedings 2006, pages 227-232, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-69995-8_38
    DOI: 10.1007/978-3-540-69995-8_38
    as

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