A Pure Test for the Elasticity of Yield Spreads



Table 5

Regressions of Changes in Nominal Yield Spreads of SCM Long-Term Corporate Bond Indices on
Changes in Selected Nominal Determinants -

AR-GARCH Estimation

Table 5 reports the results of the AR-GARCH estimation of regression model (4) in which the dependent
variable is the monthly change in the nominal yield spread. This regression model is of the following
form:

δS = βj + ^'\YLT + β2 (δYLT) + fakSlope + β4I + ε,
where S is the monthly change in the nominal yield spread, Ylt is the monthly change in the nominal
yield on the constant maturity long-term Government of Canada index, (
Ylt)2 is a convexity term,
Slope is the monthly change in the nominal spread between the constant maturity long-term Government
of Canada index and the three-month Treasury bill yield, and
I is the monthly nominal return on the
Toronto Stock Exchange 300 index.
t-values are in parentheses, m gives the degree of the autoregressive
process as determined by the stepwise autoregression method,
p and q are the GARCH(p,q) parameters,
Norm. Test gives the
p-value for the normality test for detecting misspecification of the GARCH model,
and finally LM gives the
p -value for the Lagrange multiplier test. Panel A reports the estimates for the
entire sample, covering the 08:1976-07:2001 25-year period. Data during this sample period are
dominated by corporate bonds carrying a standard call provision. Panel B outlines the results for the
01:1995-07:2001 sub-period, in which bonds carrying the doomsday call are expected to dominate all
indices.

_____________________Panel A

: 09:1976-07:2001_____________________________________

Regression Coefficients

AR and GARCH Parameters

Index

β 0

β1

β 2

β 3

β 4

m

p

q

Norm. Test

R2

LM

AAA

-0.0101

(-1.51)

-0.1547

(-11.06)

0.0614
(3.80)

-0.0887 ■

(-7.40)

-0.0055

(-3.61)

1, 2, 4

1

1

<0.0001

0.22

0.0004

AA

-0.0063

(-1.47)

-0.1196

(-9.67)

0.0429
(4.40)

-0.0679

(-6.90)

-0.0050

(-4.68)

1, 2, 4

1

1

0.0018

0.23

0.0067

A

-0.0067

(-1.07)

-0.1208

(-8.86)

0.0600
(5.59)

-0.0541

(-5.06)

-0.0058

(-4.66)

1, 2

1

1

0.0021

0.20

<0.0001

BBB

0.0029
(0.21)

-0.1467

(-3.82)

0.0447
(1.58)

-0.0701

(-2.67)

-0.0109

(-3.30)

-

1

1

<0.0001

0.15

-

Panel B

: 01:1995-07:2001

Regression Coefficients

AR and GARCH Parameters

Goodness of Fit

Index

β 0

β1

β 2

β 3

β 4

m

p

q

Norm. Test

R2

LM

AAA

N/A

AA

-0.0154

(-0.85)

-0.1676

(-2.02)

0.2605
(1.31)

-0.0041

(-0.08)

-0.0070

(-2.31)

-

-

-

-

0.16

-

A

-0.0001

(-0.00)

-0.1817

(-2.29)

0.0541
(0.29)

-0.0041

(-0.08)

-0.0063

(-2.17)

-

-

-

-

0.13

-

BBB

0.0047
(0.14)

0.0510
(0.43)

-0.0081

(-0.03)

0.0141

(0.18)

-0.0132

(-3.03)

-

-

-

-

0.16

-

39



More intriguing information

1. The Effects of Attendance on Academic Performance: Panel Data Evidence for Introductory Microeconomics
2. The name is absent
3. A Multimodal Framework for Computer Mediated Learning: The Reshaping of Curriculum Knowledge and Learning
4. Design and investigation of scalable multicast recursive protocols for wired and wireless ad hoc networks
5. ALTERNATIVE TRADE POLICIES
6. 5th and 8th grade pupils’ and teachers’ perceptions of the relationships between teaching methods, classroom ethos, and positive affective attitudes towards learning mathematics in Japan
7. The name is absent
8. Studying How E-Markets Evaluation Can Enhance Trust in Virtual Business Communities
9. Ein pragmatisierter Kalkul des naturlichen Schlieβens nebst Metatheorie
10. Firm Closure, Financial Losses and the Consequences for an Entrepreneurial Restart