Interpreting Recent Changes in theCredit Spreads of Japanese Banks
Jun Pan and Kenneth J. Singleton

This paper examines the recent period of relatively low credit spreads inJapan, with particular emphasis on the market’s assessments of the credit risksof large Japanese banks implicit in the prices of credit derivatives. We extract
the market-price implied likelihood of a credit event in the future, andexplore the nature of the default risk premiums underlying recent changes inbank bond and credit derivatives prices. We document substantial increases
in the “jump-at-default” default risk premiums for the large Japanese banks
examined during the early part of 2006. These patterns in risk premiums
are related to the recent patterns in market indicators of global event risk,
local equity market volatility, and an estimate of the duration of the Bankof Japan’s zero interest rate policy.
Keywords: Default risk premium; Credit default swap; Japanese banks;
Zero interest rate policy; Event risk
JEL Classification: G13, G21, G32

Jun Pan: Sloan School of Management, Massachusetts Institute of Technology (E-mail: junpan@mit.edu)
Kenneth J. Singleton: Graduate School of Business, Stanford University (E-mail: ken@future.
stanford.edu)
We benefited from discussions with Naohiko Baba, Yuko Kawai, and Yoichi Ueno, and the commentsof our discussants, Hung Tran and Kazuo Ueda. Scott Joslin, Baozhong Yang, and Zhipeng Zhang
provided excellent research assistance. We are grateful for financial support from the Gifford Fong
Associates Fund, at the Graduate School of Business, Stanford University, and financial support from
the Massachusetts Institute of Technology Laboratory for Financial Engineering.
MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006
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129

I. Introduction
This paper examines the recent period of relatively low credit spreads in Japan, withparticular emphasis on the market’s assessments of the credit risks of large Japanesebanks implicit in the prices of credit derivatives. We extract the market-price implied
likelihood of a credit event in the future, and explore the nature of the default risk
premiums underlying recent changes in bank bond and credit derivatives prices. Of
particular interest is the market’s risk premium associated with a possible jump inbond prices due to a restructuring or other major credit event involving one of thelarge banks in Japan.
These questions about Japanese banks seem particularly interesting now owing
to the confluence of several macroeconomic developments. The Japanese economy isshowing signs of recovery after many years of weakness and, concurrently, there has
been a substantial increase in the equity prices of Japanese companies, including
those of large Japanese banks. Moreover, with the improving economy—and thebenefit of hindsight—the Bank of Japan (BOJ) ended its quantitative monetary easing
policy (QMEP) toward the end of our sample period, and exited its zero interest
rate policy (ZIRP) shortly after our sample period ended. We are interested in
how market default-event risk premiums changed over the past few years as market
participants reassessed the strength of the Japanese economy, the impacts of thestrengthening economy on the policies of the BOJ, and the likely impacts of both ofthese factors on the financial strengths of the Japanese banking system.1 Have default
risk premiums fallen as a consequence of these economic developments, or have they
increased? In either case, how should we interpret the patterns in risk premiums wedocument subsequently?
The remainder of this paper is organized as follows. Section II describes the credit
default swap (CDS) market and provides an overview of the data used in our analysis.
Section III examines the properties of Japanese sovereign credit risk through the lens of
the prices of CDS contracts on Japanese government debt. This analysis serves to relatechanges in the market’s assessment of the credit quality of Japan as a whole to local andglobal risks. Then, in Section IV we turn to the properties of the CDS spreads for fourlarge Japanese banks: Mizuho Bank, Sumitomo Mitsui Banking Corporation (SMBC),Bank of Tokyo-Mitsubishi (BTM), and UFJ Bank. Particular attention is given to the
co-movements among these spreads and their relation to both Japanese sovereign risk
and equity market risk factors. Finally, Section V examines the properties of the credit
event risk premiums of two of these banks.

II. CDS Spreads for Japanese Banks
To extract market information about the credit quality of Japanese banks, we rely on
the CDS market. A CDS is essentially an insurance contract between the insurer andthe insured in which the latter pays an insurance premium at some regular interval,
1. See Ito and Harada (2006) for a complementary study of bank fragility that uses data on credit default spreads
from an earlier sample period. They do not examine default risk premiums explicitly.

130 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

usually every six months, in return for being “made whole” in the face of an insured
credit event. That is, the purchaser of insurance pays the CDS spread (multiplied by
the notional amount of underlying bonds insured) as the premium, and if an insured
event occurs, then the insurer pays the insured the difference between the post-event
market value of the bonds covered by the CDS contract and their face value.
To price CDS contracts, we follow Duffie and Singleton (1999)—see also the review
of CDS contracts in Duffie and Singleton (2003)—and adopt a “reduced-form”
pricing model. We let  denote the risk-neutral mean arrival rate of a credit event.
One can think of  as approximately the probability of a (covered) credit event overthe next, short interval of time under the pricing measure. Additionally, we let R 
denote the expected fractional recovery of face value that bondholders receive immediately following a credit event, under the pricing measure. The associated loss rate as aproportion of the face value is L ≡ (1 − R ). Finally, CDSt (M ) denotes the spreadon a CDS contract with time to maturity of M years.
Using this notation, the CDS spread satisfies
2M1  −∫––CDSt (M )Et e

j =1
2

t +0.5jt = (1 − R ) t +MEt u e −∫ (r + )ds du.
∫t




(rs +s )ds

u

t

s



s

(1)

The left-hand side of (1) is the expected present value of the insurance premium paidby the insured, CDSt (M )/2, semiannually. These payments are made only so long as
an insured credit event has not occurred, and this accounts for the presence of  inthe discount factor. Premiums are made only if the underlying bank survives until thepremium payment date. The right-hand side is the present value of the recovery
received by the insured if an insured credit event occurs. Since a credit event canoccur at any time over the life of the CDS contract, and the underlying bank must
survive until date u for the bank to then default at this time, the pricing formula
involves the terms u e −∫  ds . For a given u, this term captures the probability of thebank surviving until date u and then defaulting immediately thereafter. All of the
expectations in (1) are taken with respect to the risk-neutral pricing measure.
To interpret the spread CDSt (M ) in terms of developments in credit markets, it
is instructive to step back and first review the interpretation of credit spreads on
corporate bonds. To a first approximation, the credit spread on an M-year floating ratebond, say, Ct (M ), is approximately equal to L + l tC, where L is the mean loss rate
associated with holding a corporate bond and l C captures compensation for liquidity.
Heuristically, when holding a corporate bond, the investor is compensated for the timevalue of money, the mean rate of loss expected to be incurred due to default—
the probability of loss ( ) times the loss given default (L ), and a convenience yieldassociated with the provision of liquidity.
Absent arbitrage opportunities and large transactions costs, CDSt (M ) is also
approximately equal to L.2 Thus, a systematic decline in CDS (or corporate) spreads
u 
s

t

2. We could, as well, include a liquidity adjustment to CDSt (M ). For many issuers the CDS contract is more liquidthan their associated bonds, and so many researchers have assumed that liquidity premiums are larger in the bondmarket than in the CDS market (see, e.g., Longstaff, Mithal, and Neis [2005]). For our analysis, what is importantis that the CDSt (M ) spreads for the large Japanese banks are considered to be largely due to credit risk.

131

typically means one or more of the following occurred: the probabilities of a credit
event declined, the risk premiums associated with credit events declined (more on thislater), or expected loss rates declined.
Figure 1 displays the U.S. dollar five-year CDS spreads for four large Japanesebanks—SMBC, BTM, Mizuho Bank, and UFJ Bank—over the period 1998 throughthe middle of 2006.3 For comparison, we have also included the yield on a portfolioof a corporate spread. Clearly, CDS spreads fluctuated substantially over the sample
period, with notable spikes upward in the fourth quarter of 1998 and during
the banking crisis in Japan in 2002. Most of our attention will be focused on thelater part of this period, starting in mid-2003 and running through mid-2006.
This was a relatively quiet sub-period in credit markets, but one that witnessed astrengthening of the Japanese economy and, finally, the end of the BOJ’s policy ofquantitative easing.
One cannot always translate our findings about CDS spreads immediately into
implications for bank debenture spreads, because we often see a nonzero basis(CDSt (M ) − Ct (M ) ≠ 0). In particular, it is often quite expensive to “sell short” corporate bonds, and they are often the bonds that are expensive relative to the CDS spread.
This is illustrated in Figure 2, where the five-year CDS spread for BTM is plottedagainst the yield spread on its five-year bonds. For most of this period, the CDS spread
was above the corporate bond spread, and this partly reflects the shorting costs in thecorporate market. The CDS-bond basis was particularly large during the banking
Figure 1 U.S. Dollar Five-Year CDS Spreads on Japanese Banks

500

Basis points
SMBC
BTM
MizuhoUFJ
A corporate spread

450
400
350
300
250
200
150
100
50
0
Jan. 7,
1997

Nov. 19,
1998

Sep. 30,
2000

Aug. 12,2002

June 23,
2004

3. BTM and UFJ merged on January 1, 2006 to form Bank of Tokyo-Mitsubishi UFJ (BTMU).

132 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

May 5,
2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

Figure 2 Five-Year CDS and Corporate Bond Yield Spreads for BTM

180

Basis points
CDS spread
Corporate bond yield spread

160
140
120
100
80
60
40
20
0
–20
Oct.
1999

Feb.
2001

May
02

Aug.
03

Dec.
04

Mar.
06

crisis in 2002, when there was a notable increase in bond yield spreads. However, giventhat our focus is on the post-2003 period, most of our findings can be interpreted asapplying as well to the yields on bonds issued by Japanese banks.

III. Japanese Sovereign Credit Risk
Before exploring the properties of bank CDS spreads in depth, it will be informative to
examine the relation between sovereign risk for Japan and various factors related to
global and local event risks. For our analysis, sovereign risk is measured by the spreads
on the U.S. dollar five-year CDS contract for Japanese government bonds (JGBs).
Additionally, we examine three risk factors that might be related to variation in thesovereign CDS spread. The first is the VIX option implied volatility index for U.S.
equities. This index is often interpreted as a measure of global event risk, an interpretation that is consistent with the very high correlations between emerging market
CDS spreads and VIX documented in Pan and Singleton (2005). A second risk factor
is the bond market’s expected duration of the ZIRP, as computed from JGB yields by
the BOJ.4 A larger value of ZIRP means a longer duration of the policy of zero shortterm interest rates. Finally, for our third risk factor we use the implied volatility on the
Nikkei index option (Nikkei IV) as an index of local market volatility and risk.
4. We are grateful to the BOJ for providing these data for our analysis. ZIRP is constructed by the Financial Markets
Department for monitoring purposes. For more details, see Baba (2006).

133

Table 1 Regression of U.S. Dollar Japanese Sovereign CDS Spread on VIX, ZIRP,
and Nikkei IV
Constant–6.672(0.601)3.429(0.145)0.259(0.396)–6.438(0.529)VIX
0.960(0.045)ZIRP

Nikkei IV

3.855(0.143)0.646(0.059)2.413(0.169)Adjusted R2
0.55
0.36

0.381
(0.024)0.096(0.022)0.21
0.65

Note: Sample period is June 3, 2003 through June 2, 2006. Standard errors are given in parentheses.

Table 1 displays the results from regressing the sovereign CDS spreads for Japan on
VIX, ZIRP, and Nikkei IV. All of the coefficients are positive; sovereign CDS spreads
widened as either global or local event risk increased (as measured by equity option
volatility) or the market believed that it was likely the BOJ would maintain the ZIRP
for a longer period. When all three risk factors are included simultaneously, theadjusted coefficient of determination (R2) is 0.65, indicating that about 35 percent of
the variation in the sovereign spread for Japan was due to risk factors not captured by
VIX, ZIRP, or Nikkei IV. We will want to keep the high correlation between these risk
factors and the Japan CDS spread in mind in interpreting subsequent regressions that
include all four of these variables as right-hand-side risk factors.

IV. Bank CDS Spreads
There is, not surprisingly, substantial co-movement among the CDS spreads on large
Japanese banks. Accordingly, we begin our exploration of the credit risk implicit inJapanese CDS spreads by computing the first principal component (PC) from thecovariance matrix of spreads for Mizuho, BTM, SMBC, and UFJ over the sample
period of June 3, 2003 through June 2, 2006. The first PC is then regressed on the risk
factors VIX, ZIRP, Nikkei IV, and JapanSov, where the latter is the U.S. dollar CDS
spread for Japan (our measure of sovereign risk). The results are displayed in Table 2.
From the first four rows of regression coefficients in Table 2 it is seen that, among
VIX, ZIRP, and Nikkei IV, variation in VIX contributes the most to explaining variation in the first PC of bank spreads. At the same time, from the fifth row of results it
follows that the first PC of bank spreads behaves very much like Japan risk—the R2 in
the projection of the first PC of bank spreads onto JapanSov is 0.95 percent. When
all of the risk factors are included in the same projection (the sixth row of coefficientsin Table 2), JapanSov largely drives out ZIRP and the coefficients on VIX and Nikkei
IV fall substantially from their values when these variables are the sole regressor.
This is in part a manifestation of the high degree of correlation between JapanSovand the other risk factors noted above. It also suggests that investors (in U.S. dollar
CDS contracts) interpreted the common “level” factor underlying bank CDS spreads
as largely being equivalent to Japanese sovereign risk.

134 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

Table 2 Regression of First Principal Component of U.S. Dollar CDS Spreadon Risk Factors
Constant–83.92(5.345)20.84(1.444)–21.19(3.407)83.87(4.701)–11.67(0.739)–30.17(1.324)–28.07(1.338)VIX
9.610(0.399)ZIRP

Nikkei IV

JapanSov

35.26(1.461)6.290(0.554)0.898(0.165)1.570(0.126)21.07(1.503)0.922(0.683)Adjusted R2
0.61
0.33

4.170
(0.210)1.390(0.214)0.590(0.086)

0.28
0.69
9.29
(0.109)8.36(0.171)8.39(0.136)

0.95
0.96
0.96

Note: Sample period is June 3, 2003 through June 2, 2006. Standard errors are given in parentheses.

Table 3 Regression of the Difference between the First Principal Componentsof U.S. Dollar and Yen CDS Spreads on Risk Factors
Constant–3.580(0.715)3.475(0.176)0.285(0.586)–1.267(0.434)–3.915(0.555)VIX
0.779(0.056)ZIRP

Nikkei IV

JapanSov

3.912(0.237)0.30
0.386(0.036)–0.128(0.052)2.249(0.363)Adjusted R2
0.25

0.328
(0.034)0.22
1.368(0.079)0.771(0.108)0.53
0.62

Note: Sample period is June 3, 2003 through June 2, 2006. Standard errors are given in parentheses.

An interesting question is whether investors in yen CDS contracts (more likely
domestic than foreign entities) view the risks of banks differently than those who
invest in U.S. dollar CDS contracts. To examine this question, we computed the corresponding first PC of yen CDS spreads on the same four banks and then projected
the difference between the dollar and yen PCs onto our risk factors (Table 3). All
three of the risk factors VIX, ZIRP, and Nikkei IV are positively correlated with thisdifference in PCs, suggesting that as credit event risk increases CDS spreads denominated in dollars widen more than they do in yen. One potential interpretation of thisfinding is that foreign investors in Japanese bank CDS contracts either assign ahigher likelihood to an adverse credit event for Japanese banks following an increasein global event risk (as measured by VIX) or domestic economic risk (as measured byincreases in either ZIRP or Nikkei IV), or the risk premiums demanded by theseinvestors increase with increases in the risk factors.

135

Once JapanSov is included as a regressor, VIX is largely driven out of the projectionof differences in PCs onto the risk factors, while the coefficients on ZIRP and Nikkei
IV remain large relative to their standard errors. Thus, variation in the difference in(the first PCs of ) U.S. dollar and yen CDS spreads is not entirely due to differencesin the assessments of how sovereign risk will affect the credit risks of banks. Overand above sovereign risk, increases in the local equity market volatility or the risk of adeterioration in the Japanese macroeconomy (as measured by an increase in ZIRP)
are both associated with wider dollar-yen CDS spreads.

V. Default Risk Premiums for Japanese Banks
We turn next to the nature of default risk premiums for large Japanese banks. We suppose the probability of a credit event is state-dependent (varies with macroeconomic
and industry conditions), while the loss in value due to a credit event is constant.5 We
set the (risk-neutrally) expected percentage loss in face value owing to a credit event to0.60, following industry practice in the pricing of CDS contracts on Japanese banks.6
There are two distinct types of credit risk that are reflected in CDS spreads and in
expected excess returns on bond positions. The first is compensation for the usual
risk factors associated with business and macro conditions: movements in interest
rates; movements in balance sheets that affect likelihoods of default; movements inregulation or monetary policy by central banks; and so on. The other is compensation for “jump-at-default risk.” More concretely, the instantaneous expected excess
return on a defaultable zero-coupon bond with price B(t, T ) can be expressed as
eBt = Comp(risk factors) + Comp(jump-at-default)=...

wt − B(t, T –) (1 − RP (t )).
+ –––––––––t
B(t, T )(2)

The first term in (2) captures the compensation investors receive for bearing therisks associated with unpredictable variation in the state variables underlying yield
curve movements. These include both the state variables determining the default-freeterm structure and those that govern variation over time in .7 Thus, at least a
portion of this component of excess returns is capturing risk related to credit.
Separate from the risk related to unpredictable variation in  is the risk of a jumpin the price of the underlying bonds in the event that a bank does restructure. It is
this jump-at-default risk that we are particularly interested in, and it is the premium
associated with this risk that is most often referred to as the default risk premium.
5. This assumption is now standard in studies of credit default risk premiums; see, for example, Driessen (2005) and
Berndt et al. (2005). It is surely not literally true, but rather is made for convenience to focus on the timing risks
associated with credit events.
6. See Ueno and Baba (2006) for a discussion of industry practice in Japan for the pricing of bank CDS contracts.
7. There is no presumption that the state variables driving the risk-free yield curve and those determining  are
distinct. In general they will not be; the short-term risk-free rate and  are generally correlated over time. See Duffee(1999) for some evidence of negative correlation among these variables in U.S. corporate bond markets.

136 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

The compensation for this risk, as reflected in excess returns, is captured in thesecond term of (2), (wt − B(t, T ))/(B(t, T ))t (1 − RP (t )). The term wt is the recovery
value of the bond; (wt − B(t, T ))/(B(t, T )) is the percentage loss of value due todefault; and RPt is the market price of default risk. If the risk premium is one, thenthis last term is zero and does not affect excess returns; there is no concern about
jumps at the time of credit events. On the other hand, if the risk premium is greaterthan one, then (1 − RPt ) is negative. Since the term (wt − B(t, T ))/(B(t, T )) is negative
if prices jump down when there is a credit event, the overall contribution of this term
to excess returns is positive.
Now it turns out theoretically that the risk premium associated with jump-at-default
risk is the ratio between the risk-neutral and historical arrival rate of credit events:

–t ,
RPt = ––
t(3)

where  is the historical mean arrival rate of credit events (see Yu [2002] for a heuristic
discussion of this relation). Typically, this ratio is larger than one since, assuming
investors are averse to jump-at-default risk, to obtain the correct market prices usingrisk-neutral valuation,  must be set larger than P. Effectively, the investment environment must, risk-neutrally, be much riskier (default must be more likely) than what
has been experienced historically.
Our objective is to compute the risk premiums RPt and investigate how thesepremiums have changed recently with the strengthening of the Japanese economy
and the changing expectations of market participants about the exit from the BOJ’s
ZIRP and QMEP. As an approximation to , we use the five-year CDS spread, which
we noted is approximately L, divided by 0.60 (by convention, the market’s
estimate of L ).
To compute , we rely on the estimate of the market’s expected probability ofdefault over the next year calculated by Moody’s KMV using a Merton-style balancesheet model of credit events.8 Letting EDF (t ) denote the estimated probability ofdefault over the next year, 1 − EDF (t ) is the estimated probability of survival. If (t )is the mean arrival rate of default under the historical distribution, then
1 − EDF (t ) = Et e −∫  (s)ds .
t +1



t

(4)

Therefore, approximately,(t ) ≈ − log[1 − EDF (t )].

(5)

The ratio of our estimated  to the estimated  gives our estimate of RP.

8. We are grateful to Moody’s KMV for providing us with its default estimates for the two Japanese banks examinedin this analysis.

137

Figure 3 Risk Premium for Mizuho Bank
Basis points

2450

RP (left scale) (right scale) (right scale)

400
350
300
250

1

200
150
100
50
0
Jan.
2003

0
Jan.
04

Jan.
05

Jan.
06

Figure 3 displays RP, as well as its components  and , for Mizuho Bank. Noticefirst of all that, aside from the early part of our sample in 2003, Q and  track eachother remarkably closely. The ratio of these variables, RP, fluctuates above and below
one over the sample period. Toward the end of the sample, during late 2005 andearly 2006, there is a substantial run-up in the risk premium in the market. Thus, itappears that as the price of Mizuho Bank’s equity was increasing, and as the likelihoodthat the BOJ would end the QMEP was increasing with the strengthening of themacroeconomy, the risk premium related to jump-at-default risk was increasing.
The corresponding results for SMBC in Figure 4 are even more striking.
Throughout the period from mid-2003 through mid-2005, RP for SMBC stayed
roughly constant at a level notably below one. Then there was a steep increase in RP
that continued through the end of our sample in early 2006.
Two features of these results warrant further discussion: (1) why did we see
prolonged periods during which RP was substantially below unity and (2) why did
the risk premiums increase substantially over the latter part of our sample period
when, by most accounts, the Japanese economy was improving, as were the balance
sheets of the large banks in Japan?
With regard to the risk premiums being below unity, this may partially reflectmismeasurement of Q or , or both. Focusing first on , recall that  is extracted
from the CDS spread by scaling by L set at 0.60. If we have set L too high, thenthis will tend to understate both  and RP. An interesting question then is: whatlevel of L would ensure that RPt is greater than or equal to unity throughout our

138 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

Figure 4 Risk Premium for SMBC
Basis points3

RP (left scale) (right scale) (right scale)

250

200
2

150

100

1

50

0
Jan.
2003

0
Jan.
04

Jan.
05

Jan.
06

sample period? We computed these Lmin values for Mizuho Bank and SMBC andobtained 0.23 and 0.16, respectively. These values, although substantially smaller
than market convention, are perhaps not wholly implausible. There have been very
few defaults or episodes of restructuring by major financial institutions in Japan.
Moreover, if there were a restructuring, then one might argue that regulators would
manage such events in a manner which ensured that investors in the bonds of thesebanks would lose at most a small percentage of the face value of their bonds. Of
course, relying on such implicit guarantees makes the run-up in RP at the end of oursample, especially for SMBC, even more puzzling unless one also argues that the
implicit financial guarantees within the Japanese banking system were weakening
with increased liberalization and the recent strengthening of the Japanese economy.
At a mechanical level, the substantial increase in risk premiums toward the endof our sample is simply a reflection of the fact that, in our data,  fell more rapidly
than  in early 2006. Some insight into the economic forces that were in playduring this period comes from inspection of the projections of the risk premiums
for SMBC and Mizuho Bank (RP ) onto the risk factors (Table 4). Most notably,
the largest correlation is between RP and ZIRP during this sample period. Thatis, as optimism about the end of the BOJ’s ZIRP increased (ZIRP declined),
RP increased.
This pattern is consistent with the presence of clientele effects—essentially, different
classes of investors were determining  and . More precisely,  is determined largely
by expected returns and volatility in the Japanese equity market. On the other hand,139

Table 4 Projections of Risk Premiums onto Risk Factors[1] SMBC
Constant
8.604(0.4267)5.687(0.239)8.066(0.408)4.926(0.220)9.025(0.428)VIX–0.375(0.026)–0.213(0.033)ZIRP–2.475(0.235)–2.011(0.235)

Nikkei IV

JapanSov

Adjusted R2
0.22
0.38

0.015
(0.019)0.43–0.309(0.036)–2.371(0.250)0.0006(0.020)–0.250(0.025)0.149(0.022)VIX–0.079(0.011)ZIRP

Nikkei IV

JapanSov

0.16

Adjusted R2
0.08

0.45

[2] Mizuho Bank
Constant
3.677(0.173)3.340(0.046)3.275(0.140)3.299(0.057)2.678(0.161)–0.107(0.013)–0.047(0.014)–0.778(0.036)–0.563(0.045)–0.338(0.042)0.30
0.074(0.007)0.083(0.007)0.38–0.105(0.005)–0.093(0.008)0.23
0.44

Note: Sample period is June 3, 2003 through June 2, 2006. Standard errors are given in parentheses.

 was computed from U.S. dollar CDS spreads. Although overseas hedge funds
were active investors in both markets (Japanese equities and the CDS markets),
our impression is that those focusing on bank equities were funds following macro or
directional strategies, while those focusing on the bank CDS market were pursuing
arbitrage strategies.9 From this perspective, the large runups in RP through the earlypart of 2006 could reflect a relatively more optimistic view on Japanese banks bymacro/directional investors. That is, the directional investors’ perception of the“distances to default” of these banks improved more through early 2006 than thecorresponding perceptions of arbitrage traders. Consistent with this interpretation,in the projection of our estimated  for SMBC onto the risk factors VIX, ZIRP,
Nikkei IV, and JapanSov (Table 5), there is high correlation between  and VIX, ourmeasure of global event risk.
Of course, there is the possibility that the recent run-up in RP for Japanese banks
was also due in part to mismeasurement of the one-year default probability by Moody’s
KMV. Reliable estimation of expected default frequencies is difficult under the best of
circumstances. In the case of large Japanese banks, there were several mergers during
our sample period that led to substantial changes in the balance sheets of these banks.10
Moreover, the high leverage ratios maintained by banks present challenges for the
9. We are grateful to Naohiko Baba for pointing out the different investment focus of these different classes of investors.
10. Because of the merger between BTM and UFJ, we omitted these banks from the analysis of RP in this section.

140 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

Table 5 Projections of  for SMBC onto Risk Factors
Constant–171.30(9.941)
29.94(5.200)–80.58(7.231)–9.068(5.924)–142.90(9.843)VIX
18.06(0.731)ZIRP

Nikkei IV

JapanSov

62.10(5.078)0.25
9.248(0.421)

5.071(0.959)27.31(6.477)

Adjusted R2
0.53

4.753
(0.526)0.34
13.96(0.897)5.813(1.186)0.53
0.65

Note: Sample period is June 3, 2003 through June 2, 2006. Standard errors are given in parentheses.

application of balance-sheet models of default. Particularly challenging is measurementof the appropriate default boundary.
A more extensive exploration of recent patterns of jump-at-default risk premiumsfor Japanese banks is an interesting topic for future research.

References

Baba, N., “Financial Market Functioning and Monetary Policy: Japan’s Experience,” Monetary andEconomic Studies, 24 (S-1), Institute for Monetary and Economic Studies, Bank of Japan, 2006,
pp. 39–71 (this issue).
Berndt, A., R. Douglas, D. Duffie, M. Ferguson, and D. Schranz, “Measuring Default Risk Premia from
Default Swap Rates and EDFs,” working paper, Stanford University, 2005 (also available as BIS
Working Paper No. 173, Bank for International Settlements, 2005).
Driessen, J., “Is Default Event Risk Priced in Corporate Bonds?”Review of Financial Studies, 18 (1), 2005,
pp. 165–195.
Duffee, G., “Estimating the Price of Default Risk,” Review of Financial Studies, 12 (1), 1999, pp. 197–226.
Duffie, D., and K. Singleton, “Modeling Term Structures of Defaultable Bonds,” Review of Financial
Studies, 12 (4), 1999, pp. 687–720.
———, and ———, Credit Risk, Princeton: Princeton University Press, 2003.
Ito, T., and K. Harada, “Bank Fragility in Japan: 1995 to 2003,” in M. Hutchison and F. Westermann,eds. Japan’s Great Stagnation: Financial and Monetary Policy Lessons for Advanced Economies,
Cambridge, Massachusetts: The MIT Press, 2006.
Longstaff, F., S. Mithal, and E. Neis, “Corporate Yield Spreads: Default Risk or Liquidity? New Evidence
from the Credit-Default Swap Market,” Journal of Finance, 60 (5), 2005, pp. 2213–2253.
Pan, J., and K. Singleton, “Default and Recovery Implicit in the Term Structure of Sovereign CDS
Spreads,” working paper, Stanford University, 2005.
Ueno, Y., and N. Baba, “Default Intensity and Expected Recovery of Japanese Banks and ‘Government’:
New Evidence from the CDS Market,” Bank of Japan Working Paper No. 06-E-04, Bank ofJapan, 2006.
Yu, F., “Modeling Expected Return on Defaultable Bonds,” Journal of Fixed Income, 12 (2), 2002,
pp. 69–81.

141

Comment
HUNG TRAN11International Monetary FundI would like to make a few comments, having more to do with interpretations andsome technical questions, and conclude by raising issues for further research.
Basically, I found the authors’ paper to be very interesting, because it is basically inline with the kind of work that our department at the International Monetary Fund(IMF) has been doing. Instead of looking only at Japanese banks’ credit risk evolution over time, we look at emerging markets and sovereign borrower credit risk, but a
lot of the methodology and issues we encounter and try to resolve are parallel to thekinds of issues confronting the authors.
First, I find that the calculation using the ratio of the risk-neutral mean arrival
rate of a credit event, , to the historical mean arrival rate of credit events, , as ameasure of the risk premium, to be very interesting. I think that it is a more accurate
way to try to measure the risk premium, compared to the way in which many market
participants use just the spread as a risk premium.
However, if we look at the calculated risk premium for the two Japanese banks thatthe authors showed, many questions arise. Despite the explanation, I find it counterintuitive that in the latest period until now the risk premium for both Mizuho Bankand Sumitomo Mitsui Banking Corporation (SMBC) increases rather significantly,
because this is the period when banks in Japan have really cleaned up their balance
sheets, the volume of nonperforming loans has declined, and profitability has increased.
So it is difficult intuitively to reconcile that with the increase in the risk premium.
Certainly, if you look at the regression that the authors used to calculate the risk
premium for the two banks, it is also difficult to understand what actually is goingon. For Mizuho Bank, the coefficient for VIX is positive and the coefficient for ZIRP
is positive, if they are run alone. In the last equation, VIX has a negative coefficient,but a positive coefficient for ZIRP. Now the same factors, VIX and ZIRP, are negative
throughout for SMBC.12 For me, it is difficult to see why a global factor like VIXshows up with a positive coefficient for one bank, and then a negative coefficient foranother bank. The same with ZIRP; so that is a question I would like to raise and ask
the authors to clarify in their paper.
The second point I would like to raise is as follows. In the authors’ Figure 1, it isinteresting to see that the basis risk, which is the difference between the credit default
swap (CDS) spread and the corporate bond spread for banks, appears to be fluctuating
within a very narrow range. That seems reassuring, because market participants tend
to use CDSs as a hedge or risk management tool when they invest in the actual
underlying bonds or notes from the banks or from the corporate borrowers.
However, having said that, I think that the usage of CDSs as a hedge might encounter
11. My comments are my own and do not necessarily reflect the views of the International Monetary Fund.
12. Please note that the comment refers here to material provided by Kenneth J. Singleton during the presentationof the paper at the conference.

142 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Comment

some development problem in the future, precisely because of the fact that theissuance of CDSs based on the underlying volume of actual bonds seems to be
diverging. In other words, for many companies, the amount of CDSs outstanding ismuch bigger compared to the volume of bonds outstanding. To the extent that thecurrent documentation of the CDS contract calls for physical delivery of the actual
bonds by the buyers of CDSs, when a credit event occurs, to the seller of the CDS
contract in exchange for protection, the fact that there is a small number of bonds
when the bond of that borrower gets into difficulty—as in the case of Delphi
Corporation in the United States in late 2005 and other companies there in recent
months—means there is a scramble to get hold of the physical bonds by the buyers of
CDSs to deliver to the seller of CDSs. This tends to boost the value of the defaulted
bonds well above the recovery value of the bonds, therefore impacting the CDS
spread as well.
At an extreme, if you have a company moving to reduce its outstanding bonds,
like one European company is planning to do, to zero, that means the company nolonger has any outstanding bonds. Then the volume of CDS contracts written on
those bonds will face a very uncertain and, up to this moment, difficult to understandfuture. Because again, the documentation of the CDS contracts calls for a credit
event meaning failure to service the outstanding bonds, if there are no bonds there isno such event to be triggered, and therefore whether the CDS will become worthlessor not is an issue under debate.
Taking that into consideration, there is a question as to how much the CDS
spread and the actual credit spread of the bond will continue to track each other as
nicely and with a stable basis risk, as we have seen.
The last point I would like to raise again concerns something that the IMF verymuch shares with the authors, stemming from our belief in the need for the importance of a measure of volatility in financial markets worldwide. That is the ubiquityof the VIX index. It shows up everywhere in the pricing of all kinds of risk premiums
or risky assets, and in all kinds of financial practices, the most important of which is
the use of the value at risk (VaR) measure for risk management purposes, and also thepricing of all kinds of financial contracts and products, with embedded optionality,
which seem to be very widespread at the moment. So in recent years, if you run acorrelation between the VIX index with practically every risky asset, from Japanesebanks to high-yield bond spreads, to high-yield corporate bond spreads, to emerging
market government bond spreads, such as those for Turkey, Mexico, Russia, orIndonesia, you have a very nice correlation. But that means what is nice on the way
down also presents a problem if volatility, again as measured by the VIX index, seems to
be on the rise. One can think of many reasons why volatility might be on the rise;
namely, more uncertainty in terms of future data on economic growth; more uncertainty in terms of monetary policy response to the data; then the question is, what
will happen to the entire range of asset prices, the entire range of financial practices
including the application of VaR as a means for risk management and other risk pricing?
To me, this is far more a concern as an outcome of the recent market volatility
and corrections than the actual decline in price levels themselves. Price levels havedeclined in many asset markets, but from a very high, multiyear-high level. More of a143

question is what will happen when volatility, having risen noticeably in recent weeks,
continues to rise, and what the secondary effect of that higher volatility will be interms of the rest of the asset markets.

Comment
KAZUO UEDA
University of Tokyo
This is a very timely analysis. Needless to say, the credit default swap (CDS) market
has recently been growing very rapidly in Japan. It is also timely to analyze questions
such as what effect the quantitative monetary easing policy (QMEP) or the zerointerest rate policy (ZIRP) has had on various risk premiums, given the fact that the
Bank of Japan (BOJ) exited from the QMEP back in March.
The authors estimate bank risk premiums, or default-related risk premiums, bycomparing the estimate of the risk-neutral mean arrival rate of a credit event, ,derived from the data on CDSs, with the historical mean arrival rate of credit events
, estimated from stock market data and balance-sheet data. But the results are
somewhat counterintuitive. The estimates of risk premiums in many cases are below
one, and also they are rising fairly sharply toward the end of the sample.
There are other studies of a similar issue. For example, a paper by Ueno and Baba
(2006) estimates bank risk premiums by comparing the survival probability under
the risk-neutral measure with the survival probability under the so-called pseudoactual measure.13 It uses data on the term structure of CDS spreads, not just five-year
rates. The results are fairly intuitive; the black bars in Figure 1 show something likerisk premiums estimated in this way, and they decline, as more or less expected,
toward the end of the sample.
So the results Jun Pan and Kenneth J. Singleton obtain must be driven by the factthat they use the stock market data, or they compare the estimate of the intensities
between the stock market and the CDS market. Thus, possible factors driving theirresults are that there may have been significant undershooting of stock prices in, say,years such as 2002–03, or perhaps overshooting in 2005. Another possibility alreadystated by the authors is that investors in the CDS market and the stock market differ.
On the CDS market, I would just like to touch on one thing that has alreadybeen discussed by the authors. This concerns the Japanese government’s policy ofprotecting all bank debts between sometime in late 1997 to 2004–05. In the case of
Ashikaga Bank that arose in late 2003, even all subordinated debt was protected. So
one wonders whether the bond market sought to price in risk premiums related todefault or default events. At least, it is fair to say that the pricing in these markets
ought to be sensitive to changes in perceptions about the degree to which the government is willing to protect bond holders. Essentially, this issue of sensitivity contests
the assumption of constancy of the loss rates or the recovery rates.
13. The survival probability under the pseudo-actual measure is based on the risk-neutral default intensity, but
evaluated under the actual measure.

144 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

Comment

Figure 1 Risk Premiums as the Difference between Risk-Neutral and Pseudo-Actual
Measures of Survival Probabilities[1] BTM[2] SMBC

1.00

0.05

1.00

0.95

0.03

0.95

0.05
0.04
0.03
0.02

0.90

0.01

0.90

0.01
0.00

0.85
–0.01
Sep. Sep. Sep. Sep. Sep. Sep. Sep. Sep.
1998 99 2000 01 02 03 04 05[3] UFJ
1.00

0.85
–0.01
Sep. Sep. Sep. Sep. Sep. Sep. Sep. Sep.
1998 99 2000 01 02 03 04 05[4] Mizuho
0.05

1.00

0.05

0.04
0.95

0.03

0.04
0.95

0.03

0.02
0.90

0.01

0.02
0.90

0.01

0.00
0.85
–0.01
Sep. Sep. Sep. Sep. Sep. Sep. Sep. Sep.
1998 99 2000 01 02 03 04 05

0.00
0.85
Sep. Sep. Sep. Sep. Sep. Sep. Sep.
1998 99 2000 01 02 03 04–0.01[5] Japan
1.00

0.005

0.99

0.004

0.98

Difference (right scale)
Under  (left scale)
Under  (left scale)

0.003
0.002

0.97
0.96

0.001
0.000

–0.001
0.95
Sep. Sep. Sep. Sep. Sep. Sep. Sep. Sep.
1998 99 2000 01 02 03 04 05

Source: Ueno and Baba (2006).

Now I would like to turn to something with which I am more familiar, which isthe effect of the BOJ’s actions on various market prices, especially risk premiums.
It is widely believed that quantitative easing has had fairly significant effects on risk
premiums in a wide range of markets. For example, interest rates on negotiablecertificates of deposit (NCDs). The standard deviation across banks of interest rates
rose sharply during the period of financial instability in 1997–98, while it went down
during the ZIRP period in 1999–2000 and declined further under the QMEP. (SeeFigure 2; for further details, see Baba et al. [2006].)

145

Ap
r.
N 5,
ov 1
M . 1 993
ay , 1
D 30 993
ec ,. 19
Ju 26, 94
ly 1
Fe 24 994b. , 1
Se 19 995
p. , 1
Ap 16, 996
r. 1
N 14 996
ov , 1.
9Ju 10, 97
ne 19
Ja 8, 97
n. 19
Au 4, 98
g 1
Fe . 2 999
b. , 1
Se 28 999
p. , 20
Ap 25, 00
r. 20
N 23 00
ov ,2
Ju . 19 00
ne , 2 1
Ja 17 001
n. , 2
Au 13 002
g. , 2
1 0
M 1, 03ar 20.
0
O 8, 2 3ct. 4 00
M , 4
ay 20
2, 04
20
05

Ap
r.
N 5,
ov 1
M . 1 993
ay , 1
D 30 993
ec ,. 19
Ju 26, 94
ly 1
Fe 24 994b. , 1
Se 19 995
p. , 1
Ap 16, 996
r. 1
N 14 996
ov , 1.
9Ju 10, 97
ne 19
Ja 8, 97
n. 19
Au 4, 98
g 1
Fe . 2 999
b. , 1
Se 28 999
p. , 20
Ap 25, 00
r. 20
N 23 00
ov ,2
Ju . 19 00
ne , 2 1
Ja 17 001
n. , 2
Au 13 002
g. , 2
1 0
M 1, 03ar 20.
0
O 8, 2 3ct. 4 00
M , 4
ay 20
2, 04
20
05

Ap
r.
N 5,
ov 1
M . 1 993
ay , 1
D 30 993
ec ,. 19
Ju 26, 94
ly 1
Fe 24 994b. , 1
Se 19 995
p. , 1
Ap 16, 996
r. 1
N 14 996
ov , 1.
9Ju 10, 97
ne 19
Ja 8, 97
n. 19
Au 4, 98
g 1
Fe . 2 999
b. , 1
Se 28 999
p. , 20
Ap 25, 00
r. 20
N 23 00
ov ,2
Ju . 19 00
ne , 2 1
Ja 17 001
n. , 2
Au 13 002
g. , 2
1 0
M 1, 03ar 20.
0
O 8, 2 3ct. 4 00
M , 4
ay 20
2, 04
20
05

Figure 2 Standard Deviation of Interest Rates on Newly Issued NCDs among Banks[1] Maturity of Less than 30 Days

0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00

0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00

0.70

0.50

0.40

0.30
Percent

Standard deviation

0.60

Standard deviation
Period offinancial
instability

Standard deviation
Period offinancial
instability

Period offinancial
instability

ZIRP

ZIRP

ZIRP

Source: Baba et al. (2006).

146 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006
QMEP

Average ofstandard deviation[2] Maturity of Less than 60 Days

Percent

QMEP

Average ofstandard deviation[3] Maturity of Less than 90 Days

Percent

QMEP

Average ofstandard deviation

0.20

0.10

0.00

Comment

Looking at the credit curves for NCD rates discussed in Baba et al. (2006), we findthat as the years progressed the credit curves became flatter and flatter, indicating
roughly that risk premiums declined with the QMEP (Figure 3). It is the same forbond spreads or CP.
Next, there are questions such as what aspects of quantitative easing have affectedrisk premiums in various markets. There are two or three candidates. First, the BOJ
increased the supply of reserves, so the amount of the current account balances at theBOJ may have affected risk premiums. Second, there may have been some direct
effects of the BOJ’s operations on the prices of assets it was buying. Third, the ZIRP
was in place, which was the commitment to maintain interest rates at zero for longer
than the market would have expected in the absence of such a policy.
Baba et al. (2006) tested for the effects of these aspects of quantitative easing using
the data on NCDs. We ran regressions of NCD interest rates on monetary policy
variables including dummies for the ZIRP and QMEP periods, the amount of current
account balances, and the maturity or durability of fund-supplying operations as aproxy for other kinds of non-traditional operations the BOJ was undertaking. The
result was that the current account balance variable was insignificant, while the others
were significant with the right sign.
Pan and Singleton find that their ZIRP variable reduced the risk premium for
Sumitomo Mitsui Banking Corporation (SMBC) and Bank of Tokyo-Mitsubishi, butraised it for Mizuho Bank.14 Even for SMBC, the ZIRP variable raised the default
intensity variable. I must say some of these results are counterintuitive. The variable theyused, ZIRP, is the bond market’s expected duration of the BOJ’s ZIRP, as computed fromJapanese government bond yields. This variable fluctuates in response to essentially twoforces. First, it moves in response to changing market views of near-term inflation
or growth, and second, it may respond to explicit policy changes or policy statements
by the BOJ. But the only time the BOJ said something explicit about the durationof the ZIRP during the period in question (June 3, 2003 to June 2, 2006) was
October 2003.
Looking at the movements of the ZIRP variable used, we notice that there are peaksin the fall of 2002 and the spring of 2003, when investors were most pessimistic about
the state of the financial system. So I would say the fluctuations in this variable were
mostly due to changing perceptions about the economy, which means that there is apotential simultaneous equation bias in the regression the authors carry out. That is tosay, shocks that affect the risk premiums may also have affected the ZIRP variable.
Negative shocks to the economy or, in particular, to the financial system made ZIRP
larger, which should lead to a positive bias for the coefficient. This bias probably isstrongest for Mizuho Bank.
So in conclusion, the questions and issues analyzed in the paper are very interesting, but at this point it would be somewhat hasty to take the result at face value. But
again, the authors have given us a lot of interesting things to consider.

14. Please note that the comment refers here to material provided by Kenneth J. Singleton during the presentationof the paper at the conference.

147

Figure 3 Credit Curves of NCD Spreads[1] Maturity of Less than 30 Days
0.14

Percent
1997
1999
2002
2004
2005

0.12
0.10
0.08
0.06
0.04
0.02
0.00
Aa2

Aa3

A1

A2

A3

Baa1

Baa2

Baa3

A2

A3

Baa1

Baa2

Baa3

A2

A3

Baa1

Baa2

Baa3

[2] Maturity of Less than 60 Days
0.16

Percent
1997
1999
2002
2004
2005

0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
Aa2

Aa3

A1

[3] Maturity of Less than 90 Days
0.16

Percent

0.14

1997
1999
2002

0.12
0.10

2004
2005

0.08
0.06
0.04
0.02
0.00
–0.02
Aa2

Aa3

A1

Source: Baba et al. (2006).

148 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006

General Discussion
References

Baba, Naohiko, Motoharu Nakashima, Yousuke Shigemi, and Kazuo Ueda, “The Bank of Japan’s
Monetary Policy and Bank Risk Premiums in the Money Market,” International Journal ofCentral Banking, 2, 2006, pp. 105–135.
Ueno, Yoichi, and Naohiko Baba, “Default Intensity and Expected Recovery of Japanese Banks and‘Government’: New Evidence from the CDS Market,” Bank of Japan Working Paper No. 06-E-04,
Bank of Japan, 2006.

General Discussion
In his response to the discussants, Kenneth J. Singleton stressed first that the default
risk premium he defined was not a measure of the single market’s assessment of thelikelihood of a credit event. He suggested that the default risk premium could rise if
the equity market’s assessment or the historical estimate of the probability of default
fell more rapidly than that implicit in the credit default swap (CDS) market. He also
insisted that there were multiple types of risk premiums.
Regarding Hung Tran’s remarks about hedging and the institutional features of
the CDS markets and his concerns about global volatility being on the rise, Singleton
agreed with Tran and said that some large management firms in the United States
were actually designing funds for pension funds and other institutional clients, toenable them to sell off the volatility risk.
In the general discussion, Kenneth N. Kuttner (Oberlin College) questioned theassumption of the constant loss rate over time. He proposed estimating the risk
premium as a latent common factor from all the bank credit spreads and then imposing
it to those banks, which enables an estimation of the implied time-varying loss rates
for each bank. Singleton responded that presuming the risk premiums have the same
pattern across all the banks given the historical probability of default, he could estimate
the time-varying loss rates.
Ulrich Kohli (Swiss National Bank), the chairperson of the session, questioned theassumption that the loss rate (recovery rate) is 60 percent (40 percent). He said that hewould expect recovery rates to be higher for banks. Since banks were regulated morestrictly than other firms, the probability was higher that a bank would be liquidated or
shut down before it became insolvent. Singleton agreed with Kohli and responded thatto get the default risk premiums up around one in the paper, one would use a loss rate
closer to about 20 percent, not 60 percent, which corresponds to a very high recovery
rate for banks.
Regarding the comments on his work by Kazuo Ueda, Naohiko Baba (Bank ofJapan) first clarified the difference in definitions of default risk premiums between Pan
and Singleton’s work and his own. Then he pointed out the possible perception gap
between credit and stock markets about capital injections by the government andrepayment by banks, which was likely to cause the recent rise in the jump-at-default risk
premium. Singleton agreed with Baba’s interpretation and responded that participants
had two main concerns. One is a lack of understanding of how the critical factors that
affected the likelihood of a bank going into financial distress were going to move over149

time, and the other is the fear about what would happen if they went into financial
distress. He stressed that the paper focused on the second main concern.
Shen Bingxi (The People’s Bank of China) asked how the credit markets in Japan,
including the corporate bond and CDS markets, developed and would develop in the
future. Singleton responded that in Japan, similar to the United States, most corporate
bonds are bought and kept in the portfolios of large financial institutions and held tomaturity, so that the CDS spreads give a clearer window into the market’s perceptionsof credit quality than corporate bond spreads.

150 MONETARY AND ECONOMIC STUDIES (SPECIAL EDITION)/DECEMBER 2006