Yield Curve Modeling and Forecasting :The Dynamic Nelson-Siegel Approach ( The Econometric and Tinbergen Institutes Lectures )

Publication subTitle :The Dynamic Nelson-Siegel Approach

Publication series :The Econometric and Tinbergen Institutes Lectures

Author: Diebold Francis X.;Rudebusch Glenn D.;;  

Publisher: Princeton University Press‎

Publication year: 2013

E-ISBN: 9781400845415

P-ISBN(Paperback): 9780691146805

Subject: F830.91 Securities Market

Keyword: 经济学,经济计划与管理,财政、金融

Language: ENG

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Description

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.

Chapter

1.6 Onward

2 Dynamic Nelson-Siegel

2.1 Curve Fitting

2.2 Introducing Dynamics

2.3 State-Space Representation

2.4 Estimation

2.5 Multicountry Modeling

2.6 Risk Management

2.7 DNS Fit and Forecasting

3 Arbitrage-Free Nelson-Siegel

3.1 A Two-Factor Warm-Up

3.2 The Duffie-Kan Framework

3.3 Making DNS Arbitrage-Free

3.4 Workhorse Models

3.5 AFNS Restrictions on A0(3)

3.6 Estimation

3.7 AFNS Fit and Forecasting

4 Extensions

4.1 Variations on the Basic Theme

4.2 Additional Yield Factors

4.3 Stochastic Volatility

4.4 Macroeconomic Fundamentals

5 Macro-Finance

5.1 Macro-Finance Yield Curve Modeling

5.2 Macro-Finance and AFNS

5.3 Evolving Research Directions

6 Epilogue

6.1 Is Imposition of No-Arbitrage Helpful?

6.2 Is AFNS the Only Tractable A0(3) Model?

6.3 Is AFNS Special?

Appendixes

Appendix A Two-Factor AFNS Calculations

A.1 Risk-Neutral Probability

A.2 Euler Equation

Appendix B Details of AFNS Restrictions

B.1 Independent-Factor AFNS

B.2 Correlated-Factor AFNS

Appendix C The AFGNS Yield-Adjustment Term

Bibliography

Index

2.1 DNS Factor Loadings

2.2 Out-of-Sample Forecasting Performance: DNS vs. Random Walk

4.1 DNSS Factor Loadings

4.2 DGNS Factor Loadings

5.1 Nominal and Real Yields and BEI Rates

5.2 BEI Rates and Expected Inflation

5.3 Probabilities of Nonpositive Net Inflation

5.4 LIBOR Spreads

3.1 AFNS Parameter Restrictions on the Canonical A0(3) Model

3.2 Out-of-Sample Forecasting Performance: Four DNS and AFNS Models

3.3 Out-of-Sample Forecasting Performance: Random Walk, A0(3), and AFNSindep

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