Volatility skews and extensions of the Libor market model

By Leif Andersen, J. Andreasen. 2000

265 citations recorded by the source corpus.

Subfields: Finance

View Paper: https://www.semanticscholar.org/paper/96e27338140109dc9a8e471c332bea0bda09bf14

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Citations in the corpus

Primal-Dual Simulation Algorithm for Pricing Multidimensional American Options (2004, unknown): “Equation (2) states that Qt is the maximum of the current exercise value and the expected present value of continuing (and following an optimal exercise policy).”
LIBOR market model with stochastic volatility (2006, methodology): “Using the martingale property of X(t), we can show that φT (1) = 1 and u = 0 is a removable singularity of ηT (u).”
Self Exciting Threshold Interest Rates Models (2006, methodology): “We give expressions for the price of caplet and we adapt the approximation of Andersen and Andreasen (2000) for swaption price when adding stochastic trading time.”
On the martingale property of stochastic exponentials (2004, methodology): “This process has also been used in interest-rate modelling, notably in the extended LIBOR models considered by Andersen and Andreasen (2000).”
A Libor Market Model with Default Risk (2000, unknown): “13The approximation argument in this subsection is based upon Z ühlsdorff (1999) and also Andersen and Andreasen (1998).”
Pricing Swaptions Within an Affine Framework (2002, methodology): “18 Further, this approach should generalize to jumps within the affine structure (Duffie, Pan, and Singleton [2000]), quadratic models (Longstaff [1989], Beaglehole and Tenney [1991], and Constantinides [1992]), or to Heath, Jarrow, and Morton [1992] models or even random field models with a general”
Pricing and Hedging Path-Dependent Options Under the CEV Process (2001, methodology): “ification is termed limited CEV (LCEV) process by Andersen and Andreasen (1998) .”
Fast strong approximation Monte Carlo schemes for stochastic volatility models (2006, background): “…the underlying financial variable to remain on the real axis, we specifically focus on a process for variance of the form (Cox 1975, Cox and Ross 1976, Beckers 1980, Chan et al. 1992, Andersen and Andreasen 2000) dVt ¼ ð VtÞdtþ VqtdZt, Vt0 ¼ V0: ð2Þ with , , , q > 0, and p ¼ 1=2 in equation (1).”
A LOW-BIAS SIMULATION SCHEME FOR THE SABR STOCHASTIC VOLATILITY MODEL (2012, methodology): “The results have been proved in Appendix A of [2] based on the theory presented in [5].”
The Term Structure of Simple Forward Rates with Jump Risk (2000, unknown): “These include adding a stochastic volatility, changing from a lognormal to constant elasticity of variance (CEV) form of volatility (as in Andersen and Andreasen 2000), or allowing for jumps.”
The dynamics of stochastic volatility: evidence from underlying and options markets (2003, methodology): “The use of high-frequency realized volatilities (often calculated at 5-min intervals) is increasingly popular, pursued by Andersen and Bollerslev (1997) and Andersen et al. (2001) among many others.”
A Jump-Diffusion Model for Option Pricing (2002, unknown): “The “Volatility Smile” To illustrate that the model can produce “implied volatility smile,” I consider a real data set used first in Andersen and Andreasen (2000) for two-year and nine-year caplets in the Japanese LIBOR market as of late May 1998. Figure 3 shows both observed implied volatility curv”