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Estimating the Term Structure of Volatility in Futures Yield - A Maximum Likelihood Approach

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The volatility structure of 90-day bill futures traded on the the Sydney Futures Exchange is analysed within the framework of the Heath-Jarrow-Morton model. The method involves characterisation of the transition probability density function for the forward rate process represented by the stochastic differential equation in the arbitrage-free economy. Maximisation of the likelihood function then results in the estimates of the parameters of the volatility function. The volatility function is also used in a simulation of the preference-free stochastic differential equation for bill prices.

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  • Ram Bhar & Carl Chiarella, 1995. "Estimating the Term Structure of Volatility in Futures Yield - A Maximum Likelihood Approach," Working Paper Series 56, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  • Handle: RePEc:uts:wpaper:56
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    File URL: http://www.finance.uts.edu.au/research/wpapers/wp56.pdf
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    1. Lo, Andrew W., 1988. "Maximum Likelihood Estimation of Generalized Itô Processes with Discretely Sampled Data," Econometric Theory, Cambridge University Press, vol. 4(2), pages 231-247, August.
    2. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    3. Marc Chesney & Robert J. Elliott & Dilip Madan & Hailiang Yang, 1993. "Diffusion Coefficient Estimation and Asset Pricing When Risk Premia and Sensitivities Are Time Varying1," Mathematical Finance, Wiley Blackwell, vol. 3(2), pages 85-99, April.
    4. David Heath & Robert Jarrow & Andrew Morton, 2008. "Bond Pricing And The Term Structure Of Interest Rates: A New Methodology For Contingent Claims Valuation," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 13, pages 277-305, World Scientific Publishing Co. Pte. Ltd..
    5. Marc Chesney & Robert J. Elliott & Dilip Madan & Hailiang Yang, 1993. "Diffusion coefficient estimation and asset pricing when risk premia and sensitivities are time varying," Working Papers hal-00610777, HAL.
    6. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    7. Robert A. Jarrow & Arkadev Chatterjea, 2019. "Interest Rates," World Scientific Book Chapters, in: An Introduction to Derivative Securities, Financial Markets, and Risk Management, chapter 2, pages 22-52, World Scientific Publishing Co. Pte. Ltd..
    8. Schwartz, Eduardo S & Torous, Walter N, 1989. " Prepayment and the Valuation of Mortgage-Backed Securities," Journal of Finance, American Finance Association, vol. 44(2), pages 375-392, June.
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    1. Ram Bhar & Carl Chiarella, 1996. "Construction of Zero-Coupon Yield Curve From Coupon Bond Yield Using Australian Data," Working Paper Series 70, Finance Discipline Group, UTS Business School, University of Technology, Sydney.

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