The 2nd edition of this successful book has several new features. The calibration discussion of the basic LIBOR market model has been enriched considerably, with an analysis of the impact of the swaptions interpolation technique and of the exogenous instantaneous correlation on the calibration outputs. A discussion of historical estimation of the instantaneous correlation matrix and of rank reduction has been added, and a LIBOR-model consistent swaption-volatility interpolation technique has been introduced. The old sections devoted to the smile issue in the LIBOR market model have been enlarged into a new chapter. New sections on local-volatility dynamics, and on stochastic volatility models have been added, with a thorough treatment of the recently developed uncertain-volatility approach. Examples of calibrations to real market data are now considered. The fast-growing interest for hybrid products has led to a new chapter. A special focus here is devoted to the pricing of inflation-linked derivatives. The three final new chapters of this second edition are devoted to credit. Since Credit Derivatives are increasingly fundamental, and since in the reduced-form modeling framework much of the technique involved is analogous to interest-rate modeling, Credit Derivatives -- mostly Credit Default Swaps (CDS), CDS Options and Constant Maturity CDS - are discussed, building on the basic short rate-models and market models introduced earlier for the default-free market. Counterparty risk in interest rate payoff valuation is also considered, motivated by the recent Basel II framework developments.

"Papers presented at the Leuven Conference on Exchange Rates in Multicountry Econometric Models (November 1981)"--P. vii.

The standard reference for fixed income portfolio managers—fully updated with new analytical frameworks Fixed Income Mathematics is known around the world as the leading guide to understanding the concepts, valuation models for bonds with embedded option, mortgage-backed securities, asset-backed securities, and other fixed income instruments, and portfolio analytics. Fixed Income Mathematics begins with basic concepts of the mathematics of finance, then systematically builds on them to reveal state-of-the-art methodologies for evaluating them and managing fixed-income portfolios. Concepts are illustrated with numerical examples and graphs, and you need only a basic knowledge of elementary algebra to understand them. This new edition includes several entirely new chapters―Risk-Adjusted Returns, Empirical Duration, Analysis of Floating-Rate Securities, Holdings-Based Return Attribution Analysis, Returns-Based Style Attribution Analysis, Measuring Bond Liquidity, and Machine Learning―and provides substantially revised chapters on: Interest rate modeling Probability theory Optimization models and applications to bond portfolio management Historical return measures Measuring historical return volatility The concepts and methodologies for managing fixed income portfolios has improved dramatically over the past 15 years. This edition explains these changes and provides the knowledge you need to value fixed-income securities and measure the various types of risks associated with individual securities and portfolios.

Exchange rate forecasts are generated using some popular monetary models of exchange rates in conjunction with several estimation techniques. We propose an alternative set of criteria for evaluating forecast rationality which entails the following requirements: the forecast and the actual series i) have the same order of integration, ii) are cointegrated, and iii) have a cointegrating vector consistent with long run unitary elasticity of expectations. When these conditions hold, we consider the forecasts to be consistent.' We find that it is fairly easy for the generated forecasts to pass the first requirement. However, according to the Johansen procedure, cointegration fails to hold the farther out the forecasts extend. At the one year ahead horizon, most series and their respective forecasts do not appear cointegrated. Of the cointegrated pairs, the restriction of unitary elasticity of forecasts with respect to actual appears not to be rejected in general. The exception to this pattern is in the case of the error correction models in the longer subsample. Using the Horvath-Watson procedure, which imposes a unitary coefficient restriction, we find fewer instances of consistency, but a relatively higher proportion of the identified cases of consistency are found at the longer horizons.