Arbitrage-free discretization of lognormal forward Libor and swap rate models
Author(s) -
Paul Glasserman,
Xiaoliang Zhao
Publication year - 2000
Publication title -
finance and stochastics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 50
eISSN - 1432-1122
pISSN - 0949-2984
DOI - 10.1007/s007800050002
Subject(s) - interest rate swap , libor , discretization , numéraire , arbitrage , econometrics , libor market model , swap (finance) , variance swap , mathematical finance , interest rate derivative , mathematics , interest rate , economics , volatility smile , financial economics , sabr volatility model , finance , volatility (finance) , mathematical analysis
. An important recent development in the pricing of interest rate derivatives is the emergence of models that incorporate lognormal volatilities for forward Libor or forward swap rates while keeping interest rates stable. These market models\/ have three attractive features: they preclude arbitrage among bonds, they keep rates positive, and, most distinctively, they price caps or swaptions according to Black's formula, thus allowing automatic calibration to market data. But these features of continuous-time formulations are easily lost when the models are discretized for simulation. We introduce methods for discretizing these models giving particular attention to precluding arbitrage among bonds and to keeping interest rates positive even after discretization. These methods transform the Libor or swap rates to positive martingales, discretize the martingales, and then recover the Libor and swap rates from these discretized variables, rather than discretizing the rates themselves. Choosing the martingales proportional to differences of ratios of bond prices to numeraire prices turns out to be particularly convenient and effective. We can choose the discretization to price one caplet of arbitrary maturity without discretization error. We numerically investigate the accuracy of other caplet and swaption prices as a gauge of how closely a model calibrated to implied volatilities reproduces market prices. Numerical results indicate that several of the methods proposed here often outperform more standard discretizations.
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