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Recovering the Probability Density Function of Asset Prices Using GARCH as Diffusion Approximations Author info | Abstract | Publisher info | Download info | Related research | Statistics Fabio Fornari (Banca d'Italia)
Antonio Mele () (Universite' de Paris X - Thema)
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This paper uses Garch models to estimate the objective and risk-neutral density functions of financial asset prices and, by comparing their shapes, recover detailed information on economic agents' attitudes toward risk. It differs from recent papers investigating analogous issues because it uses Nelson's (1990) result that Garch schemes are approximations of the kind of differential equations typically employed in finance to describe the evolution of asset prices. This feature of Garch schemes usually has been overshadowed by their well-known role as simple econometric tools providing reliable estimates of unobserved conditional variances. We show instead that the diffusion approximation property of Garch gives good results and can be extended to situations with i) non-standard distributions for the innovations of a conditional mean equation of asset price changes and ii) volatility concepts different from the variance. The objective PDF of the asset price is recovered from the estimation of a nonlinear Garch fitted to the historical path of the asset price. The risk-neutral PDF is extracted from crosssections of bond option prices, after introducing a volatility risk premium function. The direct comparison of the shapes of the two PDFS reveals the price attached by economic agents to the different states of nature. Applications are carried out with regard to the futures written on the Italian 10-year bond.
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Paper provided by Bank of Italy, Economic Research Department in its series Temi di discussione (Economic working papers) with number
396.
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Date of creation: Feb 2001Date of revision:
Handle: RePEc:bdi:wptemi:td_396_01Contact details of provider: Postal: Via Nazionale, 91 - 00184 Roma Web page: http://www.bancaditalia.it More information through EDIRC
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Keywords: option pricing ; stochastic volatility ; ARCH ; volatility risk premium ; Other versions of this item:
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions G12 - Financial Economics - - General Financial Markets - - - Asset Pricing G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
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