2002
DOI: 10.2139/ssrn.302280
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The Relation Between Implied and Realised Probability Density Functions

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Cited by 26 publications
(25 citation statements)
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“…Among the nonparametric approaches, and following Bondarenko [9], we can point out: implied trees methods [23], kernel methods [2], maximum-entropy methods [12,26], methods applied to the volatility smile [3,11,13,25], methods applied to the risk-neutral probability [19,21]. Other methods share both parametric and nonparametric features [1,9].…”
Section: Theoremmentioning
confidence: 99%
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“…Among the nonparametric approaches, and following Bondarenko [9], we can point out: implied trees methods [23], kernel methods [2], maximum-entropy methods [12,26], methods applied to the volatility smile [3,11,13,25], methods applied to the risk-neutral probability [19,21]. Other methods share both parametric and nonparametric features [1,9].…”
Section: Theoremmentioning
confidence: 99%
“…Other authors have also used spline fitting techniques in the context of risk-neutral density estimation, see [3,13]. In contrast to existing techniques, we allow the displacement of spline knots in a superset of the set of points corresponding to option strikes.…”
Section: Introductionmentioning
confidence: 99%
“…As a result many density specifications have been estimated from options prices. Parametric specifications include a mixture of lognormals [Ritchey (1990), Melick and Thomas (1997)], polynomials multiplied by a lognormal [Madan and Milne (1994)], a generalized beta [Anagnou, Bedendo, Hodges and Tompkins (2002)] and the densities of continuous-time price processes when volatility is stochastic [Bates (2000), Jondeau and Rockinger (2000)]. Other approaches include maximum entropy densities [Buchen and Kelly (1996)], non-parametric estimates [Ait-Sahalia and Lo (1998)], multi-parameter discrete distributions [Jackwerth and Rubinstein (1996)] and densities implied by smile functions, defined by either polynomials [Shimko (1993), Malz (1997)] or spline functions [Bliss and Panigirtzoglou (2002a)].…”
Section: Introductionmentioning
confidence: 99%
“…One strand of literature investigates methods that transform RNDs into real-world densities [Anagnou et al (2002), Bakshi, Kapadia and Madan (2003), Bliss and Panigirtzoglou (2002b)]. These methods are important for central bankers and other decision takers who wish to infer market beliefs about future distributions from market prices.…”
Section: Introductionmentioning
confidence: 99%
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