RT Journal Article SR Electronic T1 A Comparison of Markov–Functional and Market Models JF The Journal of Derivatives FD Institutional Investor Journals SP 22 OP 43 DO 10.3905/jod.2005.605351 VO 13 IS 2 A1 Michael N. Bennett A1 Joanne E. Kennedy YR 2005 UL https://pm-research.com/content/13/2/22.abstract AB The LIBOR Markov–functional model is an efficient arbitrage–free pricing model suitable for callable interest rate derivatives. We demonstrate that the one–dimensional LIBOR Markov–functional model and the separable one–factor LIBOR market model are very similar. Consequently, the intuition behind the familiar SDE formulation of the LIBOR market model may be applied to the LIBOR Markov–functional model. The application of a drift approximation to a separable one–factor LIBOR market model results in an approximating model driven by a one–dimensional Markov process, permitting efficient implementation. For a given parameterization of the driving process, the distributional structures of this model and the corresponding Markov–functional model are found to be numerically virtually indistinguishable for short–maturity tenor structures over a wide variety of market conditions, and both are very similar to the market model. A theoretical uniqueness result shows that any accurate approximation to a separable market model that reduces to a function of the driving process is effectively an approximation to the analogous Markov–functional model. Therefore, the conclusions reached in this article are not restricted to the particular choice of driving process. Minor differences are observed for longer maturities; nevertheless the models remain qualitatively similar. These differences do not have a large impact on Bermudan swaption prices. Under stress testing, the LIBOR Markov–functional and separable LIBOR market models continue to exhibit similar behavior, and Bermudan prices under these models remain comparable. However, the drift approximation model now appears to admit arbitrage that is practically significant. In this situation, the authors argue the Markov–functional model is a more appropriate choice for pricing.