Calibration of Jump-Diffusion Option Pricing Models: A Robust Non-Parametric Approach

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A Finite Difference Scheme for Option Pricing in Jump Diffusion and Exponential Lévy Models (2005, methodology): “However empirical studies on performance of risk neutral jump-diffusion models [11] seem to indicate that this feature is redundant with jumps and leads to highly ill-posed calibration problems”
Nonparametric state price density estimation using constrained least squares and the bootstrap (2006, unknown): “…Ghysels et al. (1997), Aït-Sahalia and Lo (1998, 2000), Aït-Sahalia and Duarte (2000) , Broadie et al (2000a,b), Garcia and Gencay (2000), Aït-Sahalia, Bickel and Stoker (2001), Cont (2001), Cont and Fonseca (2002), Cont and Tankov (2002), Daglish (2002) and Härdle, Kleinow and Stahl (2002).”
Option Pricing Under a Double Exponential Jump Diffusion Model (2004, background): “Since e(x,t )= zg(x,t), it is not difficult to see that ( 15 )-(16) reduce to −rz e+Le =0 , ∀ x>x 0(t);”
Pricing discretely monitored Asian options under Levy processes (2008, methodology): “The calibration problem for the Merton model is ill-posed, as many different combinations of the mean jump size and its volatility reproduce option prices with about the same overall least square error, see He et al. (2006) and Cont and Tankov (2004b) where some regularization techniques based on ”