Effects of European Sovereign Debt Crisis on Global Financial Markets

Prof. Dr. Irena VodenskaBoston University, USA

Effects of European Sovereign Debt Crisis on Global Financial Markets

Greening Financial Sector | Global Sustainable Finance Conference 4th to 5th of July 2013, Karlsruhe ‐ Germany

Outline

Motivation Europe and the Euro European sovereign debt crisis What is systemic risk and why does it matter? Connectivity of financial systems Dynamics in network of financial institutions Distress propagation model Multiplex Financial Networks Discussion and Conclusion

Vodenska et al., GSFC, July 4th ‐ 5th, 2013 Karlsruhe, GermanyThursday, July 4th, 2013 2

Motivation

Economic systems are globally interconnected Exogenous or endogenous shocks can provoke cascading

failures Financial systems are susceptible to to sharp transitions from

seemingly stable to irreversibly unstable states Sound policies are necessary to halt cascading failures or

soften their impact


Creation of the European economic and monetary union – long and carefully planned process

Intended to embrace the historically fragmented European countries and increase their international productivity and trade competitiveness

The creation of the euro has brought some positive and some challenging developments

ECE countries have emerged as market economies from former Eastern European communist regimes

Thursday, July 4th, 2013 4

European Union and the Euro

Vodenska et al., GSFC, July 4th ‐ 5th, 2013 Karlsruhe, Germany

The challenges to joining the EU for the former communist countries are at least two‐fold:Changes in the economic environments and conversions of property rights from centralized or Government‐owned to privateImportant cultural and societal transformation

Mortgages and other household loans have been the fastest growing products in the lending market, with the highest growth rates achieved in Lithuania, Latvia, Bulgaria, and Romania (Szapary & Darvas, 2008).


Challenges – Property, Culture


Increased trade among the countries that use common currency has been prominently studied (Frankel & Rose, 2002; Micco, et al., 2003; Bun & Klaasen, 2007)

Imports and exports significantly enhance the overall economic performance of a country

Trade is an important determinant of growth in GDP as well as real income

Price stabilization ‐ desirable after turbulent periods of structural price changes during the transitional pre‐EU accession period (Frankel, 2004; Wdowinski, 2005).

Thursday, July 4th, 2013 Vodenska et al., GSFC, July 4th ‐ 5th, 2013 Karlsruhe, Germany 6

Common Currency pros

Having local currency, the Government can reduce the real interest rate when needed to encourage investments in domestic businesses or depreciate its currency to boost the exports towards the countries with stronger currencies (Frankel, 2004)

Given the possibility of future economic shocks, economic convergence increases the probability of crisis contagion. Examples include:Western Europe during 1992‐93East Asia in 1997‐98, and the Russian default crisis of 1998 Latin America in 1982, 1994‐95 and 1998‐99 (Frankel, 2004)


Common Currency cons

Treaty of Rome of 1957 The Maastricht Treaty of 1992 The Stability and Growth Pact of 1997 Needed:Well‐defined criteria and process for exiting the Eurozone. Maintaining fiscal discipline and required economic criteria after becoming an EU member

Under current circumstances:The EMU and the euro may encounter more and larger crisis

New members may advocate for use of their local currencies.


EU accession plan missing link(s)

Distribution of Structural and Cohesion Funds, 1989‐2006


Total funds (annual average) (millions of ECUs)

Funds as a percent of GDPa

Group or countryCohesion countriesSpain 111,564.0 (6,198.5) 1.1Portugal 46,283.4 (2,571.3) 2.5Ireland 16,000.8 (895.1) 1.6Greece 50,922.0 (2,829.3) 3.1Other EU countriesAustria 3,096.0 (258.1) 0.11Belgium 4,753.8 (264.1) 0.10Denmark 1,818.0 (101.0) 0.06Finland 3,459.6 (288.3) 0.26France 36,275.0 (2,015.3) 0.13Germany 58,181.0 (3,232.3) 0.14Italy 61,905.6 (3,439.2) 0.30Luxembourg 255.0 (14.2) 0.08Netherlands 6,035.4 (335.3) 0.09Sweden 3,153.6 (262.8) 0.12United Kingdom 33,827.4 (1,879.3) 0.16

ECU = European currency unit.a. GDP for 1996.Sources: The European Union and its “cohesion” policies (Institute for International Economics, http://www.iie.com), European Commission, First Report on Economic and Social Cohesion (Brussels, 1996); European Union, http://www.europa.eu.int/comm/regional_policy/; and Simon Hix, The Political System of the European Union (NY: St. Martin’s Press, 1999) (Pastor, 2001)

Temporal dynamics of selected macroeconomic indicators


Market Capitalization

EU ECE members

Romania 2 20

Bulgaria 5 15

EU Candidates

Croatia 11 41

Macedonia 0.2 29

Indicators/ Groups/Countries 1999

2000

2010‐

‐2011


2000

2010‐

‐2011

GDP per capita growth

EU ECE members

Lithuania ‐0.4 3

Romania ‐1 1.1

EU candidates

Montenegro ‐9 2.2

Serbia ‐11 1.4

Turkey ‐4.8 1.4

Temporal dynamics of selected macroeconomic indicators



2000

2010‐

‐2011

Sovereign Debt (% of GDP)

EU ECE countries

Bulgaria 74 15

Hungary 60 80

EU candidates

Macedonia 47 28

Iceland 43 99

Inflation

EU ECE countries

Poland 7.3 2.7

Romania 45 6

EU Candidates

Serbia 42 6

Croatia 4 1

Turkey 65 8.5


2000

2010‐

‐2011


Market Capitalization of exchange‐listed companies – EU candidates

0

50

100

150

200

250

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Market cap

. of listed Co

's (%

of G

DP)

Euro Zone

Croatia

Iceland

Macedonia

Montenegro

Serbia

Turkey


What happened to Iceland? In 2001 banks were deregulated By 2007, three major banks in Iceland held foreign debt of over € 50

billion compared to Iceland’s GDP of € 8.5 billion The crisis contributed to the collapse of all three of the country's

major banks following difficulties in debt refinancing and a run on foreign deposits

In 2007, The Economist ranked the Icelandic krona as the most overvalued currency in the world

The 2008–2012 financial crisis is characterized as a major economic and political crisis in Iceland

Relative to the size of its economy, Iceland’s banking collapse is the largest suffered by any country in economic history

Sources: Central Bank of Iceland: External Debt, Oct. 21, 2008,The Economist: Cracks in the crust, Dec. 11, 2008,The Financial Times: The big chill, Nov. 15, 2008


0

20

40

60

80

100

120

140

160

1990 1995 2000 2005 2010

Governm

ent D

ebt (as % of G

DP)

Government Debt for the PIIGS countries, Germany, France and the United States

Greece

Italy

Portugal

United States

France

Germany

Ireland

Spain


The case of Greecefrom Boomerang by Michael Lewis

Greece – nation of about 11 million peopleHad roughly $400 billion outstanding debtAnd owed another $800 billion in pensions So, $145 billion bailout was … a gestureGreek railroad annual revenues are €100 million with annual wages of €400 million and €300 million in other expenses

Average railroad employee earns €65,000/y


Greek Tragedy (or Mystery) from Boomerang by Michael Lewis

In October 2009, estimated budget deficit was 3.7% (George Papaconstantinou – new minister of finance had just took office)

Couple of weeks later, the budget deficit was revised to 12.5% and eventually turned out to be 14%

In 2009, the tax collection collapsed because it was an election year (usual election year practice)

Approx. 30‐40% of taxes are typically not paid It takes about 15 years to resolve tax cases, so people prefer

to go to court rather than pay taxes


On the Ground in Irelandfrom Boomerang – by M. Lewis

• In 2008 Irish politicians made a decision to guarantee the debts of the largest Irish banks

• In 2010 Anglo Irish Bank declared €34 billion in losses – on total loan amount of €72 billion

• 2006 unemployment rate was 4%, 2010 – 11%• 2007 Ireland had budget surplus and by 2010 its deficit was 32%

of the country’s GDP• Since 2000, lending to construction and real estate has increased

from 8 % to 28% ‐ roughly all Irish deposits have been handed over to the commercial property developers


Systemic Risk

Global financial crisis of 2007‐2012 Considered to be the worst crisis since the Great Depression

of the 1930s Propagated value deterioration of most financial markets

around the world Contributed to potential complete collapse of major financial

institutions Involved national governments in bailing out too‐big‐to‐fail

banks


Systemic Risk (cont.)

Adversely affected the housing market and real estate prices globally

Contributed to increased unemployment rates and prolonged workforce unemployment

Significantly reduced consumer wealth and quenched appetite for spending

Contributed to the European sovereign‐debt crisis


In light of the sovereign debt challenges faced by the Eurozone countries: In December 2011, the European Central Bank committed to

provide €1 trillion of funds for the European banks for up to three years in attempt to stem the effects of the most recent financial crisis

This injection of liquidity intends to give the European governments three years to make necessary fiscal adjustments

Only time could tell whether this added liquidity into the European banking system will end the European sovereign debt crisis


European Bank Crisis


Selected Eurozone countries considerably increased their borrowing to unsustainable central government debt to GDP ratios: The Greek and the Irish debt crisis only a wake‐up call for the EUGreek GDP ‐ $300 billionIrish GDP ‐ $200 billion Combined, smaller that the GDP of Pennsylvania.

Italy and Spain – much larger economies ‐> bigger problemsItaly has close to €2 trillion debt outstanding with 50 percent financed externally Spain has over €700 billion of public debt outstanding and unemployment rate of 22 percent (Federal Reserve Bank of St. Louis, 2011).

European Sovereign Debt Crisis


Economic and Financial Networks as Complex Interconnected Systems

Network A – Global Banking SystemNetwork B – Sovereign (Government) Debt Network C – World Financial MarketsNetwork D – Currency dynamics

Correlations across different networks (layers)Causality relationships within the networks


Banks and Sovereign Debt Network Dynamics

Equity

Banks

Assets


Assets

Asset value=area

Liabilities

A CB D

X ZY

Banks and Sovereign Debt Network DynamicsOne bank is distressed sells some assets at reduced prices

Equity

Banks

Assets


Assets

Asset value=area

Liabilities

A B C D

X Y Z

Banks and Sovereign Debt Network DynamicsSales affect asset values of other banks

Banks’ equity shrinks

Equity

Banks

Assets


Assets

Asset value=area

Liabilities

A B C D

X Y Z

Banks and Sovereign Debt Network DynamicsBanks get distressed sell more assets

Equity

Banks

Assets


Assets

Asset value=area

Liabilities

A CB D

ZYX

Banks and Sovereign Debt Network DynamicsEquity of Bank D goes to zero Bank D defaults

Equity

Banks

Assets


Assets

Asset value=area

Liabilities

A B C D

X Y Z

Banks’ Adjacency Matrix without the Sovereign Debt Holdings weight


Red – 1 (holdings)

Blue – 0 (no holdings)

Matrix Density is 60%

Average #assets=3

Greece Italy Portugal Spain Ireland

Financial Institutions


Sovereign Debt Holdings of Financial Institutions (log)


Financial Institutions

Greece Italy Portugal Spain Ireland


GIIPS Sovereign Debt Holdings in 2011


GIIPS Sovereign Debt Holdings by Individual Banks


Breakdown of GIIPS Debt holdings in Individual Banks’ portfolios


Banks’ equity level distribution


Distribution of Banks’ holdings in GIIPS Sovereign Debt


Measuring Fin. Institution Distress Propagation

Banco Bilbao

Societe Generale

Banco Espirito Santo

110100

100010000

1000001000000

10000000100000000

1E+091E+101E+111E+121E+131E+141E+151E+16

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Santande

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ABM

PSBN

PGen

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Cred

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Aviva

EFG

Barclays UBI

Zurich FS

Mun

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ECa

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Alph

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Franklin

Ageas

UBI Pramerica

BES

BPI

HSBC

Union

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Mitsub

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RBS

BankInter

UBS

Aegon

Helvetia

Inbe

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ING

DPB

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WLV

Deka

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LH

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Lloyds

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Sumito

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Tokio Mar

State st

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Nom

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TT elta

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SVo

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JP M

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Mellon

MacKe

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In m

illion eu

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by prop

agation of distress Financial Inst. Rankings by influence on the overall system

Rank @ b=‐400,a=‐100 Rank @ b=‐400,a=10 Rank @ b=‐400,a=200 Rank @ b=10,a=‐100Rank @ b=10,a=10 Rank @ b=10,a=200 Rank @ b=150,a=‐100 Rank @ b=150,a=10Rank @ b=150,a=200 Rank @ b=400,a=‐100 Rank @ b=400,a=10 Rank @ b=400,a=200Total Holdings Rank @ b=‐100 Rank @ b=10 Rank @ b=500


Different regimes of network behavior


Multiplex two‐layer network of stock markets and foreign exchange

Multiplex networks have been shown to be more fragile to shocks compared to single networks, which is especially critical in financial networks.

We study dependencies of a stock market index network on one hand and foreign exchange rate network on the other.

Create two networks where nodes represented countries and connectivity links were defined as probabilities of contagion derived from correlations between the nodes weighted by the countries’ Gross Domestic Products

We developed a model for systemic risk propagation through the global stock market and foreign exchange coupled networks


Stock market and foreign exchange Pearson and Partial correlations


PearsonSTKyearlycol

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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3500-1

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1PartialSTKyearlycol

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PearsonFXyearlycol

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PartialFXyearlycol

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PearsonSTKmonthlycol

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PearsonFXmonthlycol

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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Stock Markets

Foreign Exchange

Yearly and monthly correlations between stock markets and foreign exchange


PearsonTWOyearlycol

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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1PearsonTWOmonthlycol

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PearsonSELFyearlycol

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

ARGAUSASTBELBRACANCHI

CHNCOLCYPCZEDENFIN

FRAGERGREHUNICEINDIDOIREISRITA

JAPKAZKORKWTLUX

MALMLTMAUMEXNETNZL

NORPAKPERPOLPORRUSSAUSIN

SLKSLVSAFSPASRI

SWDSWSTHATUNUAE

UKUSABAHOMAQATPHI

VENHK -1

-0.8

-0.6

-0.4

-0.2

0

0.2

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0.6

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1

PearsonSELFmonthlycol

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

ARGAUSASTBELBRACANCHI

CHNCOLCYPCZEDENFIN

FRAGERGREHUNICEINDIDOIREISRITA

JAPKAZKORKWTLUX

MALMLTMAUMEXNETNZL

NORPAKPERPOLPORRUSSAUSIN

SLKSLVSAFSPASRI

SWDSWSTHATUNUAE

UKUSABAHOMAQATPHI

VENHK -1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1. Yearly and 2. Monthly

correlations for all possible pairs

1. Yearly and 2. Monthly

correlations for only corresponding countries

Pearson correlation dendrogram for global stock markets


Pearson correlation dendrogram for foreign exchange


Observations within the coupled network structure and dynamics

For Stock markets, correlations experience sudden increases during crisis

For currency, though not obvious, correlations become weaker during crisis.

The correlations between the stock markets and foreign exchange are mainly negative

This is consistent with the hypothesis that strength in the foreign exchange corresponds to strength in financial markets


Distress propagation from stock market to foreign exchange when crisis starts with specific country’s stock market


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stocknetfxnet

USA, Japan, Germany

Malta, Mauritius, Iceland

Distress propagation from foreign exchange to stock market when crisis starts with specific country’s currency


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fxnetstocknetMalta,

Mauritius, Iceland

Partial correlation network effect of distress propagation when crisis starts with the US or the Greek stock markets


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USA Greece

Sovereign debt effect on global financial markets


PearsonSTKyearly_col

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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1PearsonCDSyearly_col

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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PearsonSTKandCDSyearly_col

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

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Stock Market CorrelationsCDS Market Correlations

Global crisis spreading model results

Some major economies, like USA, Japan, Germany, spread spillover crises faster through the global economy.

For selected smaller countries, like Malta, Mauritius, and Iceland, the speed to spread crises to other countries is slower.

However, some small countries, like Greece, have faster crisis spreading power compared to other small countries.

Pearson and Partial correlations render similar results However for Partial correlation case, if the crisis starts in the stock

market layer the contagion speed differences between big and small countries are

reduced. due to negative partial correlation of USA with other countries, USA

experience the lowest infection rate (due to our method of assigning the contagion probability)


How to circumvent detrimental market swings

To avoid collapses in interconnected systems of sovereign debt and banks we need:Contrarian banks and regular market (+α and –β)Or contrarian market and regular banks (‐α and +β)Avoiding the herding effectDiverting and/or avoiding bubble creationProtecting the system from a crashWe introduce behavioral finance in the analyses


Findings and suggestions

Certain countries are more efficient in spreading financial crisis across both network layers compared to others

The EU countries are strongly related and crisis propagates through the EU very efficiently

PROPOSED: Limiting the additions of new member countries to the

European Monetary Union for the time being Optimizing the timing for the replacement of the local

currencies of the new member candidates with the euro


DiscussionWe study systemic risk propagation through

interdependent financial networks Focus on the challenges of financial and economic

system dynamics as strongly related networks

How to transform global economic networks into more resilient systems to shocks?

Do crisis have common ingredients? Can we apply proposed methods and models universally?


Conclusion

Financial and economic systems are highly interdependent and fragile

Bank networks are affected by the banks’ sovereign debt holdings

Sovereign debt values affects banks’ worth Financial markets (banks and national debt are traded on

securities markets) => financial markets can be affected by crises contagion


Collaborators: Nima Dehmami Boston Univ., U.S.A. Di Zhou Boston Univ., U.S.A. Stefano Battiston ETH, Zurich, Switzerland Shlomo Havlin Bar‐Ilan Univ., Israel Lou Chitkushev Boston Univ., USA H. Eugene Stanley Boston Univ., U.S.A.

Acknowledgments

Greening Financial Sector | Global Sustainable Finance Conference 4th to 5th of July 2013, Karlsruhe ‐ Germany

Research supported by the European Commission FET OpenProject ‘‘FOC’’ 255987 and ‘‘FOC‐INCO’’ 297149Project Coordinator: Guido Caldarelli, IMT Lucca, Italy

Thank You!

Questions?

[email protected]


Effects of European Sovereign Debt Crisis on Global Financial Markets

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