Book contents
- Frontmatter
- Dedication
- Contents
- Acknowledgements
- Symbols and Abbreviations
- Part I The Foundations
- 1 What This Book Is About
- 2 Definitions, Notation and a Few Mathematical Results
- 3 Links among Models, Monetary Policy and the Macroeconomy
- 4 Bonds: Their Risks and Their Compensations
- 5 The Risk Factors in Action
- 6 Principal Components: Theory
- 7 Principal Components: Empirical Results
- Part II The Building Blocks: A First Look
- Part III The Conditions of No-Arbitrage
- Part IV Solving the Models
- Part V The Value of Convexity
- Part VI Excess Returns
- Part VII What the Models Tell Us
- References
- Index
3 - Links among Models, Monetary Policy and the Macroeconomy
from Part I - The Foundations
Published online by Cambridge University Press: 25 May 2018
- Frontmatter
- Dedication
- Contents
- Acknowledgements
- Symbols and Abbreviations
- Part I The Foundations
- 1 What This Book Is About
- 2 Definitions, Notation and a Few Mathematical Results
- 3 Links among Models, Monetary Policy and the Macroeconomy
- 4 Bonds: Their Risks and Their Compensations
- 5 The Risk Factors in Action
- 6 Principal Components: Theory
- 7 Principal Components: Empirical Results
- Part II The Building Blocks: A First Look
- Part III The Conditions of No-Arbitrage
- Part IV Solving the Models
- Part V The Value of Convexity
- Part VI Excess Returns
- Part VII What the Models Tell Us
- References
- Index
Summary
THE PURPOSE OF THIS CHAPTER
In our treatment we do not provide a macroeconomic or monetary-economics foundation of yield curve modelling. In this sense, our approach is therefore ‘reduced-form’: we acknowledge that deeper drivers (say, expected inflation, or the output gap) than the variables we use (say, the short rate, or the slope of the yield curve) affect the yield curve; but, for a variety of reasons, in our modelling we choose to make use of the latter, less fundamental, variables instead of the fundamental ones.
Why would we want to do so? Perhaps because they are more easily observable (estimating the slope of the yield curve requires a Bloomberg terminal; assessing the output gap is a tad more difficult). Perhaps because they synthetically embed a lot of information about the more fundamental variables (much as the temperature of a gas ‘contains’ information about the velocities of its molecules). Perhaps because they give rise to a simpler analytical treatment (we will show, for instance, that bond prices are given by expectations of a function of the path of the short rate). More generally, whenever one uses a reduced-form approach, one has a rough idea of the link between the fundamental variables and the phenomenon at hand, but one despairs of one's ability to connect all the modelling dots from the former to the latter. One therefore takes a number of judicious shortcuts through the toughest hairpin turns, hoping that one will still land in the right direction.
Even if we embrace a high-level, reduced-form approach it is still very useful to have at least an approximate picture of the links between the reduced-form variables that we use and the more fundamental variables that drive the yield curve. Providing this link is the task undertaken in this chapter. As we do so, we also present the first extension of the simple Vasicek model that we will encounter in Chapter 10.
- Type
- Chapter
- Information
- Bond Pricing and Yield Curve ModelingA Structural Approach, pp. 49 - 62Publisher: Cambridge University PressPrint publication year: 2018