Yield Curve Modeling and Forecasting

Yield Curve Modeling and Forecasting

Author: Francis X. Diebold

Publisher: Princeton University Press

Published: 2013-01-15

Total Pages: 225

ISBN-13: 1400845416

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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.


Yield Curve Modeling and Forecasting

Yield Curve Modeling and Forecasting

Author: Francis X. Diebold

Publisher: Princeton University Press

Published: 2013-01-15

Total Pages: 223

ISBN-13: 0691146802

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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.


Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds

Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds

Author: A. Berkelaar

Publisher: Springer

Published: 2009-11-30

Total Pages: 401

ISBN-13: 0230251293

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This edited volume contains essential readings for financial analysts and market practitioners working at Central Banks and Sovereign Wealth Funds. It presents the reader with state-of-the-art methods that are directly implementable, and industry 'best-practices' as followed by leading institutions in their field.


Bond Pricing and Yield Curve Modeling

Bond Pricing and Yield Curve Modeling

Author: Riccardo Rebonato

Publisher:

Published: 2018-06-07

Total Pages: 781

ISBN-13: 1107165857

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Rebonato provides an authoritative, clear, and up-to-date explanation of the cutting-edge innovations in affine modeling for government bonds, and provides readers with the precise tools to develop their own models. This book combines precise theory with up-to-date empirical evidence to build, with the minimum mathematical sophistication required for the task, a critical understanding of what drives the government bond market.


A Practitioner's Guide to Discrete-Time Yield Curve Modelling

A Practitioner's Guide to Discrete-Time Yield Curve Modelling

Author: Ken Nyholm

Publisher: Cambridge University Press

Published: 2021-01-07

Total Pages: 152

ISBN-13: 1108982301

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This Element is intended for students and practitioners as a gentle and intuitive introduction to the field of discrete-time yield curve modelling. I strive to be as comprehensive as possible, while still adhering to the overall premise of putting a strong focus on practical applications. In addition to a thorough description of the Nelson-Siegel family of model, the Element contains a section on the intuitive relationship between P and Q measures, one on how the structure of a Nelson-Siegel model can be retained in the arbitrage-free framework, and a dedicated section that provides a detailed explanation for the Joslin, Singleton, and Zhu (2011) model.


Developments in Macro-Finance Yield Curve Modelling

Developments in Macro-Finance Yield Curve Modelling

Author: Jagjit S. Chadha

Publisher: Cambridge University Press

Published: 2014-02-06

Total Pages: 571

ISBN-13: 1107662559

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Changes in the shape of the yield curve have traditionally been one of the key macroeconomic indicators of a likely change in economic outlook. However, the recent financial crises have created a challenge to the management of monetary policy, demanding a revision in the way that policymakers model expected changes in the economy. This volume brings together central bank economists and leading academic monetary economists to propose new methods for modelling the behaviour of interest rates. Topics covered include: the analysis and extraction of expectations of future monetary policy and inflation; the analysis of the short-term dynamics of money market interest rates; the reliability of existing models in periods of extreme market volatility and how to adjust them accordingly; and the role of government debt and deficits in affecting sovereign bond yields and spreads. This book will interest financial researchers and practitioners as well as academic and central bank economists.


Handbook of Financial Time Series

Handbook of Financial Time Series

Author: Torben Gustav Andersen

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 1045

ISBN-13: 3540712976

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The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.


The Frailty Model

The Frailty Model

Author: Luc Duchateau

Publisher: Springer Science & Business Media

Published: 2007-10-23

Total Pages: 329

ISBN-13: 038772835X

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Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.


Dynamic Factor Models

Dynamic Factor Models

Author: Siem Jan Koopman

Publisher: Emerald Group Publishing

Published: 2016-01-08

Total Pages: 685

ISBN-13: 1785603523

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This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.