The Information in the Joint Term Structures of Bond Yields

2018 ◽  
Author(s):  
Andrew Meldrum ◽  
Marek Andrzej Raczko ◽  
Peter Spencer
Keyword(s):  
Bond Yields ◽  
Term Structures

Term Structures of Corporate Bond Yields as a Function of Risk of Default: Discussion

1967 ◽  
Vol 22 (2) ◽  
pp. 346
Author(s):  
John M. Culbertson ◽  
David Durand
Keyword(s):  
Corporate Bond ◽  
Bond Yields ◽  
Term Structures

A GENERALIZATION OF PRINCIPAL COMPONENT ANALYSIS FOR NON-OBSERVABLE TERM STRUCTURES IN EMERGING MARKETS

2003 ◽  
Vol 06 (08) ◽  
pp. 885-903 ◽  
Author(s):  
CAIO IBSEN RODRIGUES DE ALMEIDA ◽  
ANTONIO MARCOS DUARTE ◽  
CRISTIANO AUGUSTO COELHO FERNANDES
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Emerging Markets ◽  
Interest Rates ◽  
Term Structure ◽  
Principal Component ◽  
Component Analysis ◽  
Bond Yields ◽  
Term Structures ◽  
Time Term

Principal Component Analysis (PCA) has been traditionally used for identifying the most important factors driving term structures of interest rates movements. Once one maps the term structure dynamics, it can be used in many applications. For instance, portfolio allocation, Asset/Liability models, and risk management, are some of its possible uses. This approach presents very simple implementation algorithm, whenever a time series of the term structure is disposable. Nevertheless, in markets where there is no database for discount bond yields available, this approach cannot be applied. In this article, we exploit properties of an orthogonal decomposition of the term structure to sequentially estimate along time, term structures of interest rates in emerging markets. The methodology, named Legendre Dynamic Model (LDM), consists in building the dynamics of the term structure by using Legendre Polynomials to drive its movements. We propose applying LDM to obtain time series for term structures of interest rates and to study their behavior through the behavior of the Legendre Coefficients levels and first differences properly normalized (Legendre factors). Under the hypothesis of stationarity and serial independence of the Legendre factors, we show that there is asymptotic equivalence between LDM and PCA, concluding that LDM captures PCA as a particular case. As a numerical example, we apply our technique to Brazilian Brady and Global Bond Markets, briefly study the time series characteristics of their term structures, and identify the intensity of the most important basic movements of these term structures.

Extensions

2013 ◽  
Author(s):  
Francis X. Diebold ◽  
Glenn D. Rudebusch
Keyword(s):  
Bayesian Analysis ◽  
Stochastic Volatility ◽  
Research Program ◽  
Functional Form ◽  
Credit Spreads ◽  
Bond Yields ◽  
Ongoing Research ◽  
Factor Loadings ◽  
Term Structures ◽  
Macroeconomic Fundamentals

This chapter highlights aspects of the vibrant ongoing research program associated with the ideas developed in earlier chapters. It begins with a collage-style sketch of work involving Bayesian analysis, functional form for factor loadings, term structures of credit spreads, and nonlinearities. It then discusses in greater detail the incorporation of more than three yield factors. Next, it treats stochastic volatility in both dynamic Nelson–Siegel model (DNS) and arbitrage-free DNS (AFNS) environments, with some attention to the issue of unspanned stochastic volatility. Finally, it discusses the incorporation of macroeconomic fundamentals in their relation to bond yields. It also introduces aspects of modeling real versus nominal yields in DNS/AFNS environments, a theme treated in detail in Chapter 5.

Earnings Predictability, Bond Ratings, and Bond Yields

CFA Digest ◽  
2006 ◽  
Vol 36 (2) ◽  
pp. 34-35
Author(s):  
Christopher J. Sullivan
Keyword(s):  
Bond Yields ◽  
Bond Ratings ◽  
Earnings Predictability
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