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Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures, Yield Curve Modeling and Forecasting contains essential tools with enhanced utility for academics, central banks, governments, and industry.
State-of-the-art research from academics and policymakers on the role of and challenges to monetary policy during the ongoing financial crisis.
State-of-the-art research from academics and policy-makers on the role of and challenges to monetary policy during the ongoing financial crisis.
We estimate the latent factors that underlie the dynamics of the sovereign bond yield curve in Morocco during 2004–14 based on the Dynamic Nelson-Siegel model. On this basis, we explore the interaction between macroeconomic variables and the yield curve, which is of direct relevance to macroeconomic policy-making. In Morocco’s context, we find that tighter monetary policy increases short-end maturities, and that the impact is small and short-lived. Economic activity is also briefly but significantly impacted, suggesting that even under a pegged exchange rate, monetary policy autonomy and effectiveness can be increased through greater central bank independence. Fiscal improvements significantly lower yield levels. Policy conclusions are that improvement in the fiscal and monetary policy frameworks, as well as greater financial sector development and inclusion, could benefit Morocco and strengthen the transmission mechanisms and effectiveness of macroeconomic policies.
In recent years, term premia have been very low and sometimes even negative. Now, with the United States economy growing above potential, inflationary pressures are on the rise. Term premia are very sensitive to the expected future path of growth, inflation, and monetary policy, and an inflation surprise could require monetary policy to tighten faster than anticipated, inducing to a sudden decompression of term and other risk premia, thus tightening financial conditions. This paper proposes a semi-structural dynamic term structure model augmented with macroeconomic factors to include cyclical dynamics with a focus on medium- to long-run forecasts. Our results clearly show that a macroeconomic approach is warranted: While term premium estimates are in line with those from other studies, we provide (i) plausible, stable estimates of expected long-term interest rates and (ii) forecasts of short- and long-term interest rates as well as cyclical macroeconomic variables that are stunningly close to those generated from large-scale macroeconomic models.
Back Cover ( this section should include endorsements also) As interest rate markets continue to innovate and expand it is becoming increasingly important to remain up-to-date with the latest practical and theoretical developments. This book covers the latest developments in full, with descriptions and implementation techniques for all the major classes of interest rate models - both those actively used in practice as well as theoretical models still 'waiting in the wings'. Interest rate models, implementation methods and estimation issues are discussed at length by the authors as are important new developments such as kernel estimation techniques, economic based models, implied pricing methods and models on manifolds. Providing balanced coverage of both the practical use of models and the theory that underlies them, Interest Rate Modelling adopts an implementation orientation throughout making it an ideal resource for both practitioners and researchers. Back Flap Jessica James Jessica James is Head of Research for Bank One's Strategic Risk Management group, based in the UK. Jessica started life as a physicist at Manchester University and completed her D Phil in Theoretical Atomic and Nuclear Physics at Christ Church, Oxford, under Professor Sandars. After a year as a college lecturer at Trinity, Oxford, she began work at the First National Bank of Chicago, now Bank One, where she still works. She is well known as a speaker on the conference circuit, lecturing on a variety of topics such as VaR, capital allocation, credit derivatives and interest rate modelling, and has published articles on various aspects of financial modelling. Nick Webber Nick Webber is a lecturer in Finance at Warwick Business School. Prior to his academic career, Nick had extensive experience in the industrial and commercial world in operational research and computing. After obtaining a PhD in Theoretical Physics from Imperial College he began research into financial options. His main area of research centres on interest rate modelling and computational finance. He has taught practitioner and academic courses for many years, chiefly on options and interest rates. Front Flap Interest Rate Modelling provides a comprehensive resource on all the main aspects of valuing and hedging interest rate products. A series of introductory chapters reviews the theoretical background, pointing out the problems in using naïve valuation and implementation techniques. There follows a full analysis of interest rate models including major categories, such as Affine, HJM and Market models, and in addition, lesser well known types that include Consol, Random field and Jump-augmented Models. Implementation methods are discussed in depth including the latest developments in the use of finite difference, Lattice and Monte Carlo methods and their particular application to the valuation of interest rate derivatives. Containing previously unpublished material, Interest Rate Modelling is a key reference work both for practitioners developing and implementing models for real and for academics teaching and researching in the field.
In this volume, specialists from traditionally separate areas in economics and finance investigate issues at the conjunction of their fields. They argue that financial decisions of the firm can affect real economic activity—and this is true for enough firms and consumers to have significant aggregate economic effects. They demonstrate that important differences—asymmetries—in access to information between "borrowers" and "lenders" ("insiders" and "outsiders") in financial transactions affect investment decisions of firms and the organization of financial markets. The original research emphasizes the role of information problems in explaining empirically important links between internal finance and investment, as well as their role in accounting for observed variations in mechanisms for corporate control.
1. Introduction 1 2. Identification Analysis and F.I.M.L. Estimation for the K-Mode1 10 3. Identification Analysis and F.I.ML. Estimation for the C-Model 23 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model 32 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling 44 5 .a Impulse Response Analysis 44 5.b Variance Decomposition (by Antonio Lanzarotti) 51 6. Long-run A-priori Information. Deterministic Components. Cointegration 58 6.a Long-run A-priori Information 58 6.b Deterministic Components 62 6.c Cointegration 65 7. The Working of an AB-Model 71 Annex 1: The Notions ofReduced Form and Structure in Structural VAR Modeling 83 Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models 87 Appendix A 93 Appendix B 96 Appendix C (by Antonio Lanzarotti and Mario Seghelini) 99 Appendix D (by Antonio Lanzarotti and Mario Seghelini) 109 References 128 Foreword In recent years a growing interest in the structural VAR approach (SVAR) has followed the path-breaking works by Blanchard and Watson (1986), Bemanke (1986) and Sims (1986), especially in U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping directions: the interpretation ofbusiness cycle fluctuations of a small number of significantmacroeconomic variables and the identification of the effects of different policies.