DETERMINANTS OF SPREADS OF ROMANIAN SOVEREIGN BONDS - an application on the EMBIG spreads –...

DETERMINANTS OF SPREADS OF ROMANIAN SOVEREIGN BONDS

- an application on the EMBIG spreads –

Student: BERBECARU CLAUDIA-FLORIANA

Supervisor: Professor MOISĂ ALTĂR

The Academy of Economic Studies DOFIN – Doctoral School of Finance and Banking

Bucharest, July 2008


In last years there was a rapid compression in the spreads of sovereign bonds issued by Emerging Economies

The compression in spreads was driven both by domestic fundamentals but also by the developments in the risk appetite of investors on the international markets

For instance, decrease in the EMBIG spreads for Romania came hand in hand with important progresses in the economy as reflected by the improved sovereign ratings from S&P

EMBIG Composite, EMBIG Romania and Credit Rating Outlook for Romania

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EMBIG spreads for Romania

EMBIG spreads - Composite index

Credit rating outlook index (CROI) - Romania (RHS)


Developments in the risk appetite of investors on the international markets were also important for the sovereign spreads

EU accession had also an impact on the spreads for CEE countries

Spreads in June 2007 S&P Rating

1 Bulgaria 18.3 8 BBB+, Stable2 Croatia 21.5 9 BBB, Stable3 Lithuania 21.7 7.7 A, Negative4 Slovakia 22.2 6 A, Stable5 Czech Republic 22.7 6 A-, Pozitive6 Romania 28 10 BBB-, Stable7 Hungary 30.1 8 BBB+, Stable8 Poland 33 7 A-, Stable

Country CROI

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BulgariaCzech RepublicHungaryPolandRomania

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18EMBI spreads for Hungary

Credit rating outlook index

THE MODEL

The spreads of sovereign bonds for Emerging Economies are thought to reflect the default risk of these countries

They should be modeled as a function of the probability of default and of the loss given the default (or the expected recovery)

Most empirical analises use the following reduced-form equation:

tititiiiti ZXs ,,, )log(

where tis , is the spread for country i at t ,

tiX , is a set of domestic fundamentals for country i at t

tZ is a set of external factors reflecting the degree of risk

appetite of international investors

Many times tiX , is based on the sovereign ratings of rating agencies

DATA USED IN ANALYSIS

Number of countries: 11 Emerging Economies

Period of analysis: May 2002 – April 2008

EMBIG spreads They are computed by JP Morgan on daily basis as the difference between the

yields of sovereign bonds issued by Emerging Economies and the yield for a bond issued by a a developed benchmark economy

The spreads of sovereign bonds for Emerging Economies are thought to reflect the default risk of these countries

EMBIG price indexes are used in the last part of the paper to estimate volatility, co-movements and spillover effects


Credit Rating Outlook Index (CROI)

Converts the sovereign ratings of S&P on a numerical (cardinal) scale

The CROI is used as proxy for the domestic fundamentals

We use the CROI computed by Hartelius and others (2008) which takes into account both the ratings and the oulooks for the ratings

The HP filtered series (ʌ=15) is used the estimations

Stable Positive Negative

Investment grade

AAA 1 0 2.7

AA+ 2 1 3.7

AA 3 2 4.7

AA- 4 3 5.7

A+ 5 4 6.7

A 6 5 7.7

A- 7 6 8.7

BBB+ 8 7 9.7

BBB 9 8 10.7

BBB- 10 9 11.7

Sub-investment grade, categoria I

BB+ 11 10.1 12.7

BB 12 11.1 13.7

BB- 13 12.1 14.7

B+ 14 13.1 15.7

B 15 14.1 16.7

B- 16 15.1 17.7

CCC+ 17 16.1 18.7

Sub-investment grade, categoria II

CCC 18 18 18

CCC- 19 19 19

CC 20 20 20

C 21 21 21

SD 22 22 22

Category S&P sovereign ratings

Outlook


Volatility index of S&P 500 (VIX)

The Chicago Board Options Exchange Volatility Index (VIX) is a key measure of market expectations of near-term volatility (30 days) conveyed by S&P 500 stock index option prices

Proxy for risk appetite in the global markets

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VIX index


Other series taken into account, but not used in the final model

3-months futures on the FED funds rate - used volatility of the diference between the 3-months futures on the FED funds rate and the FED funds rate

Unit root tests

Unit root test on the individual series showed that the series are I(1) Panel unit root tests showed also that series are I(1)

EMPIRICAL MODEL

Testing for cointegration

No cointegration was found between the data when using only data for Romania Panel cointegration tests (Pedroni and Kao) showed that there is a cointegration relationship between the log of EMBIG spreads,

the log of CROI index, and the log of VIX

Estimation methods

To estimate the lon-run relationship between the variables, we use two models: A panel model with fixed effects The pool mean group (PMG) estimator of Pesaran, Shin and Smith (1997)

PANEL MODEL WITH FIXED EFFECTS – ESTIMATION RESULTS

We estimate the following equation with pooled data:

tiiititi vixcroiembig ,, log_log_log_

where 11,...,2,1i identifies the countries and 72,...,2,1t identifies the

period of time.

is the same across the countries

varies across the countries

we allow for fixed effects

we take into account that there might be autocorrelation in the

residuals across countries


Variable Coefficient Std. Error t-Statistic Prob.

C -4.150236 0.196415 -21.12989 0.0000

LOG(HP_CROI_?) 2.544679 0.063320 40.18774 0.0000

BG--LOG(VIX) 1.245724 0.102703 12.12937 0.0000

BR--LOG(VIX) 1.561762 0.166648 9.371598 0.0000

CR--LOG(VIX) 0.953539 0.087435 10.90571 0.0000

HU--LOG(VIX) 0.880507 0.056080 15.70092 0.0000

MX--LOG(VIX) 0.823619 0.064358 12.79742 0.0000

PO--LOG(VIX) 1.176625 0.101113 11.63678 0.0000

RO--LOG(VIX) 1.159120 0.134922 8.591051 0.0000

SA--LOG(VIX) 0.785796 0.078891 9.960475 0.0000

SL--LOG(VIX) 0.637691 0.173224 3.681314 0.0002

TU--LOG(VIX) 0.877326 0.097576 8.991228 0.0000

VN--LOG(VIX) 1.318097 0.083019 15.87706 0.0000

Fixed Effects (Cross)

BG--C -0.729494

BR--C -0.995616

CR--C -0.032228

HU--C -0.017427

MX--C 1.080493

PO--C -0.617098

RO--C -0.636171

SA--C 1.101355

SL--C 0.681114

TU--C 0.523515

VN--C -0.358444

Wald Test:

Test Statistic Value df Probability

F-statistic 32.25910 (10, 769) 0.0000 Chi-square 322.5910 10 0.0000

The Wald test rejects the null hypothesis that the coefficient of the VIX is the same across the countries

The tests rejects the null hypotesis that the fixed effects coefficents are thesame across countries

Redundant Fixed Effects Tests Test cross-section fixed effects

Effects Test Statistic d.f. Prob. Cross-section F 45.238281 (10,769) 0.0000


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Bulgaria

Romania

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Croatia

Romania

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Hungary

Romania

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Poland

Romania

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Slovakia

Romania

Given that the variables are I(1) and cointegrated, the residuals can be considered as deviations from the long-run equilibrium


There is a high similarity between Romania and Bulgaria which might be explained by the EU accession process:

Spreads increased above the equilibrium level in 2003 when the EU decided not to include Romania and Bulgaria in the 2004 enlargement wave

Spreads decreased towards the equilibrium level in 2004 when the 2007 accession target was announced

Spreads felt below the equilibrium level in 2007 after the EU accesion

In April 2008 Romanian embig spreads were below the equilibrium level despite the fact they increased starting mid-2007

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Croatia

Romania

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CROI_BG CROI_CR CROI_RO

POOL MEAN GROUP ESTIMATOR OF PESARAN, SHIN AND SMITH (1997)

The following equation in the error correction form is estimated:

itijt

r

jjijti

q

jji

p

jjtijitititiiti

cvixcroihp

embigvixcroihpembigembig

ii

i

log__log_

log_log__log_log_log_

1

0,2,

1

0,1

1

1,,,1,,

where 11,...,2,1i denotes the countries and 72,...,2,1t denotes the time

periods.

In the long-run relationship:

- the coefficient of the CROI is the same across the countries

- the coefficient i of the VIX is different across the countries

speed of adjustment coefficient i is different across the countries

number of lags differ across the variables and across the countries


Schwarz Criteria selected an ARDL (2,0,1) model for Romania

log_log_

log__log_log_log_

tRO,1,21,1,

,1,,

ROtROtRORO

tROtROtROROtRO

cvixembig

vixcroihpembigembig

0.6844-log_0.3451log_0.2479

log_1.4888_log_2.5270log_-0.1185log_

tRO,1,

,1,,

ttRO

ttROtROtRO

vixembig

vixcroihpembigembig

Variable Coefficient Standard error T-statistic

RO -0.1185 0.0327 -3.6262

2.5270 0.2249 11.2336

RO 1.4888 0.3325 4.4782

1,RO 0.2479 0.0949 2.6118

1,2RO 0.3451 0.1063 3.2467

ROc -0.6844 0.2005 -3.4141


Country ARDL Model Phi log_hp_croi log_vix

Bulgaria 2 0 1 Coefficient -0.17 2.53 1.43

Std. Error 0.05 0.22 0.27

t-statistic -3.43 11.23 0.05

Brasilia 1 1 1 Coefficient -0.09 2.53 1.69

Std. Error 0.03 0.22 0.51

t-statistic -2.88 11.23 3.34

Croatia 2 0 0 Coefficient -0.29 2.53 1.08

Std. Error 0.05 0.22 0.15

t-statistic -5.97 11.23 7.05

Hungary 2 0 0 Coefficient -0.38 2.53 0.92

Std. Error 0.07 0.22 0.09

t-statistic -5.70 11.23 9.92

Mexic 1 2 1 Coefficient -0.17 2.53 0.89

Std. Error 0.07 0.22 0.19

t-statistic -2.51 11.23 4.62

Poland 1 1 1 Coefficient 0.04 2.53 1.22

Std. Error 0.04 0.22 0.76

t-statistic 1.00 11.23 1.60

Country ARDL Model Phi log_hp_croi log_vix

Romania 2 0 1 Coefficient -0.12 2.53 1.49

Std. Error 0.03 0.22 0.33

t-statistic -3.63 11.23 4.48

South Africa 1 1 0 Coefficient -0.24 2.53 1.22

Std. Error 0.06 0.22 0.22

t-statistic -3.87 11.23 5.44

Slovakia 1 0 0 Coefficient 0.00 2.53 12.08

Std. Error 0.04 0.22 86.80

t-statistic 0.13 11.23 0.14

Turkey 1 2 1 Coefficient -0.13 2.53 1.67

Std. Error 0.05 0.22 0.51

t-statistic -2.47 11.23 3.29

Venezuela 2 0 0 Coefficient -0.24 2.53 1.41

Std. Error 0.04 0.22 0.16

t-statistic -5.47 11.23 8.81

Coefficients in the long-run relationship for the 11 countries in the pool model


Panel with fixed effects estimation:

Pool mean group estimator results:

5.7755log_4888.1_log_2.5270__log_ ,1, ttROtRO vixcroihpeqembig

6864.4log_1591.1_log_2.5447__log_ ,1, ttROtRO vixcroihpeqembig

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Panel with fixed effects - Deviation fromequilibrium

PMG estimator - Deviation from equilibrium

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EMBI spreads for Romania

Panel w ith f ixed effects - Equilibrium levelPMG estimator - Equilibrium level

MAIN PRACTICAL IMPLICATIONS OF THE MODEL

The spreads for the Romanian sovereign bonds decreased by 225 bp between May 2002 and April 2008. The estimated model, based on the long-run equilibrium relationship, implies only a decrease of 51 bp.

The higher decrease in the effective spreads is due to the fact that the Romanian bonds were undervaluated in 2002 (the spreads were above their equilibrium level) and they were overvaluated in April 2008 (the spreads were below their equilibrium level).

The 51 bp decreased based on the equilibrium level is due exclusively to the fundamentals (as reflected by the decrease in the S&P sovereign rating), while the external factors had no impact during this interval. This is because following the crisis on the international markets the VIX index returned to the same level as in 2002, which means that the investors started to price appropriately the risk.

In the long run, a country cannot bet on the external factors to reduce its borrowing costs. Rather, it should implement appropriate domestic policies in order to improve domestic fundamentals.

CO-MOVEMENTS AND SPILLOVER EFFECTS IN THE DAILY RETURNS OF SOVEREIGN BONDS

We test for the existence of a co-movement in the prices of sovereign bonds and for the existence of spillover effects between the Emerging Countries from Europe

We use daily returns from May 2002 to May 2008 for 6 countries: Poland, Hungary, Slovakia, Romania, Bulgaria, Croatia

To test for co-movements we use the permanent components of the conditional variance obtained from univariate Component GARCH (1,1) models:

,2ttt cr with ),0(~/ 2

1 ttt NI

112

1312

1212

112 )()()( ttttttttt Dqaqaqaq

)()( 21

21211 tttt bqbq

where tr is the daily return, 2

t is the conditional variance and tq is the permanent component of the conditional variance


Estimation results:

Sample period: May 2002 – May 2008

Romania Bulgaria Croatia Poland Hungary

ARCH in Mean c 70.198*** 27.64*** 86.1432*** 36.4175*** 29.3184***

ARCH Term a1 0.1938*** 0.101*** 0.1548** 0.0709** 0.0625***

GARCH Term a2 0.4147*** 0.6193*** -0.0285 0.0671 0.2391*

Asymetric Term a3 -0.076* n.a. -0.1443** -0.1098*** -0.0357

Trend Intercept ω 0.000002*** 0.000004*** 0.000002*** 0.000005*** 0.000005***

Trend AR Term b1 0.9982*** 0.9963*** 0.9969*** 0.8987*** 0.9861***

Forecast error b2 0.0195*** 0.0091** 0.0171*** 0.0231*** 0.0354*** LM Obs*R-squared 0.1035 1.6387 0.0329 0.2591 0.8766

a1 + a2 0.6085 0.7203 0.1263 0.138 0.3016 *, ** and *** indicate significance at the 1%, 5% and 10% confidence level, respectively


Permanent components of the conditional standard deviations

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

2-May-02 17-Oct-02 3-Apr-03 18-Sep-03 4-Mar-04 19-Aug-04 3-Feb-05 21-Jul-05 5-Jan-06 22-Jun-06 7-Dec-06 24-May-07 8-Nov-07 24-Apr-08

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VIX (RHS) Bulgaria Croatia Hungaria Poland Romania

Correlation coefficients

There is a high similarity especially between the permanent components for conditional volatility for Romania, Bulgaria, and Croatia

Bulgaria Croatia Hungary Poland

Romania 0.91 0.81 0.48 0.27

Bulgaria 0.77 0.56 0.14

Croatia 0.64 0.47

Hungary 0.45

Bulgaria Croatia Hungary Poland

Romania 0.53 0.16 0.2 -0.11

Bulgaria 0.07 0.16 0*

Croatia 0.31 0.22Hungary 0.24

Permanent components

Transitory components

Note: All coefficients are statistically significant

The coefficient for Poland and Bulgaria is not statisticalsignificant


Principal components analysis for the permanent components of conditional volatility

A. All five countries are included

Cumulative CumulativeNumber Value Difference Proportion Value Proportion

1 3.29 2.30 0.66 3.29 0.662 1.00 0.52 0.20 4.29 0.863 0.47 0.30 0.09 4.76 0.954 0.17 0.10 0.03 4.93 0.995 0.07 --- 0.01 5.00 1.00

B. Only Romania, Bulgaria and Croatia are included


1 2.66 2.41 0.89 2.66 0.892 0.25 0.16 0.08 2.91 0.973 0.09 --- 0.03 3.00 1.00

C. Only Romania and Bulgaria are included


1 1.91 1.81 0.95 1.91 0.952 0.09 --- 0.05 2.00 1.00

Eigenvalues: (Sum = 5, Average = 1)




In order to test for spillover effects we reestimate the CGARCH model using in the equation for the permanent component of the volatility for a country the lagged estimated permanent components for the other countries

,,2

,, tROtROtRO cr with ),0(~/ 2;1, tROttRO NI

1,1;2

1,31,2

1,21,2

1,12

, )()()( tROtROtROtROtROtROtROttRO Dqaqaqaq

1,32

1,2

1,21,1, )()( tjtROtROtROtRO qbbqbq

From country i

to Romania

Coefficient 3b Standard error z-statistics Prob.

Bulgaria 0.020721 0.008247 2.512418 0.0120

Croatia 0.018687 0.005076 3.681276 0.0002

Hungary 0.004638 0.001308 3.545817 0.0004

Poland 0.043294 0.00949 4.561988 0.0000

From Romania

to country i

Coefficient 3b Standard error z-statistics Prob.

Bulgaria 0.180597 0.061303 2.945963 0.0032

Croatia 0.107563 0.057154 1.881976 0.0598

Hungary 0.006334 0.003187 1.987443 0.0469

Poland 0.001284 0.00155 0.828561 0.4074

There are spillover-effects especially both to and from Romania

CONCLUSION

The Credit Rating Outlook Index (CROI) and the volatility index VIX explain well the developments in the spreads of sovereign bonds

There is a large similitude between the deviations of spreads from the level implied by the long-run relationship in the case of Bulgaria and Romania, which we explain by the EU accession process of these two countries.

We find also a comovement in the volatility of daily returns of CEE sovereign bonds, with spillover effects especially between Bulgaria and Romania. The co -movement is located at the level of the permanent component of the conditional volatility, which mean s that it is related to fundamental factors.

In the long run, a country cannot bet on the external factors to reduce its borrowing costs. Rather, it should implement appropriate domestic policies in order to improve domestic fundamentals.

Additional research is welcomed. For instance, modeling the impact of EU accession on the spreads of CEE sovereign bonds is challenging from an econometric point of view given that this is an unobservable variable. Also, alternative estimation methods might be used in order to check the robustness of the empirical results.

REFERENCES

Alexander, C. (2001), “Market Models: A Guide to Financial Data Analysis”, John Wiley

& Sons Ltd

Chicago Board Options Exchange (2003), VIX CBOE Volatility Index, www.cboe.com

Edwards, S. (1983), “LCD’s Foreign Borrowing and Default Risk: An Empirical

Investigation 1976 – 1980”, NBER Working Paper Series No. 1172

Ferrucci, G. (2003), “Empirical Determinants of Emerging Market Economies’ Sovereign

Bond Spreads”, Bank of England, Working Paper No. 205

Fiess, N (2003), “Capital Flows, Country Risk and Contagion”, World Bank Policy

Research Working Paper 2943

Gonzalez Hermosillo, B. (2008), “Investors’ Risk Appetite and Global Financial Market

Conditions”, IMF Working Paper 08/85

Hartelius, K., K. Kashiwase and L.E. Kodres (2008), “Emerging Market Spread

Compression: Is it Real or is it Liquidity”, IMF Working Paper 08/10

Hauner, D., J. Jonas, and M.S. Kumar (2007), “Policy Credibility and Sovereign Credit:

The Case of New EU Member States”, IMF Working Paper 07/1

REFERENCES

J.P. Morgan (1999), “Introducing the J.P. Morgan Emerging Market Bond Index Global

(EMBI Global), www.morganmarkets.com

Luengnaruemitchai, P. and S. Schadler (2007), “Do Economists’ and Financial Markets’

Perspectives on the New Members of the EU Differ?” , IMF Working Paper 07/65

Maier, Philipp (2008), “Sound Policies or Good Fortune: What Drives the Compression in

Emerging Market Spreads?”, Paper presented at the Canadian Economics Assosiation

42nd Annual Meetings at University of British Columbia, Vancouver

McGuire, P. and M.A. Schrijvers (2003), “Common Factors in Emerging Market

Spreads”, BIS Quarterly Review

Ozatay, F. E. Ozmen and G. Sahinbeyoglu (2007), “Emerging Markets Sovereign

Spreads, Global Financial Conditions and US Macroeconomic News”, Economic

Research Center Working Papers in Economics 07/07

Pesaran, M.H., Y. Shin and R.P. Smith (1997), “Pool estimation of Long Run

Relationship in Dynamic Heterogeneous Panels”, Birkbeck College London

Pramor, M. and N.T. Tamirisa (2006), “Common Volatility Trends in the Central and

Eastern European Currencies and the Euro”, IMF Working Paper 06/206

DETERMINANTS OF SPREADS OF ROMANIAN SOVEREIGN BONDS - an application on the EMBIG spreads –...

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