Modeling time series information into option prices: An empirical evaluation of statistical projection and GARCH option pricing model [An article from: Journal of Banking and Finance] Buy on Amazon

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Modeling time series information into option prices: An empirical evaluation of statistical projection and GARCH option pricing model [An article from: Journal of Banking and Finance]

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PublisherElsevier
ISBN / ASINB000RR6MEO
ISBN-13978B000RR6ME4
AvailabilityAvailable for download now
Sales Rank12,239,108
MarketplaceUnited States  🇺🇸

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This digital document is a journal article from Journal of Banking and Finance, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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This paper compares the empirical performances of statistical projection models with those of the Black-Scholes (adapted to account for skew) and the GARCH option pricing models. Empirical analysis on S&P500 index options shows that the out-of-sample pricing and projected trading performances of the semi-parametric and nonparametric projection models are substantially better than more traditional models. Results further indicate that econometric models based on nonlinear projections of observable inputs perform better than models based on OLS projections, consistent with the notion that the true unobservable option pricing model is inherently a nonlinear function of its inputs. The econometric option models presented in this paper should prove useful and complement mainstream mathematical modeling methods in both research and practice.
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