Nordic linkages, European Regional Cluster Report (redacted version)

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NORDIC LINKAGES EUROPEAN REGIONAL CLUSTER REPORT BENJAMIN HUSTON, LUIS BRANDAO-MARQUES, MARCO PINON This presentation and the preliminary results are intended as background for discussions.

Transcript of Nordic linkages, European Regional Cluster Report (redacted version)

NORDIC LINKAGESEUROPEAN REGIONAL CLUSTER REPORTBENJAMIN HUSTON, LUIS BRANDAO-MARQUES, MARCO PINON

This presentation and the preliminary results are intended as background for discussions.

OUTLINE

Motivation

Method

Balance sheet or market data? Example of Nordic interbank exposures

Cross-border spillovers (by recipient country and channel)

Systemic importance of spillover channels

Inward and outward spillovers to and from the Nordics

Banking and insurance connectivity

Sovereign-to-financial and financial-to-nonfinancial

Domestic spillovers

MAIN RESULTS

Among the Nordics, Sweden and Finland are the most connected and Iceland is the least connected.

Strong Nordic connections with North America and Developed Europe.

Nordic sovereign-to-sovereign, financial-to-financial, and financial-to-nonfinancial sector connectivity is highly significant.

Sovereign-to-financial sector connectivity is only moderate: Nordic sovereigns do not play a systemic role.

Nordic financial sectors are the most systemically important segments of the regional Nordic economy, and [REDACTED].

MOTIVATION

MOTIVATION

Recent Norway FSAP and coming Sweden and Finland FSAP.

Nordic regional report (2013).

Unique confidential dataset of bank-to-bank exposures for the Nordic region (Denmark, Finland, Norway, and Sweden).

Denmark, Finland, Norway, and Sweden are all S29 jurisdictions—important to check how connected they are.

METHOD

METHOD

Measure at the firm, sector, and country level: Equity returns; Volatility of equity returns (in logs) but only for robustness.

Spillover Analysis (Diebold and Yilmaz 2014).

Order independent: generalized FEVD; order rotation for robustness.

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METHOD

Spillover from i to j is the percent of j’s total inward spillovers that are coming from i:

Inward and outward spillover indexes calculated using rolling window (3 years).

Centrality measure—eigenvalue centrality (see Annex): Measures the relative importance or influence of a node within a graph.

Node i’s score is the i-th entry of the eigenvector associated with highest eigenvalue in the network’s weighted adjacency matrix (aka spillovers matrix).

Intuition: a node that is connected to another node with many large connections is more important than a node that is connected to another node with few small connections.

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ijijij dds

BALANCE SHEET OR MARKET DATA?

EXAMPLE—NORWAY INTERBANK EXPOSURES

Market data suggests that Swedish banks play the dominant role in transmitting risks in Norway’s banking sector.

Note: See Norway stressing testing technical note for additional information.

[REDACTED]

NORDIC LINKAGES USING MARKET DATA

Nordic to Nordic channels

Nordic financial sectors are the most systemically important segments of the regional Nordic economy

Nordic sovereigns, and Iceland in general, do not appear to play a significant role in transmitting systemic risk to the rest of the region

Market data-based analysis suggests links:• Bank-to-bank lending• Common exposures• Cross-ownership links

Note: The figure displays a centrality plot of the Nordic to Nordic spillover network. Node positions are determined using eigenvector centrality scores and a node’s proximity to the center of the network signifies its importance (i.e., closer nodes are more important). The symbols , , correspond to high, medium, and low levels of systemic risk, respectively, and ring colors are used for solely for visual emphasize. See Diestel (2005) for background information on the graph-theoretic concept of centrality.

= financial sector

= nonfinancial sector

= sovereign

System importance of spillover channels

NORDIC-TO-NORDIC INTERBANK EXPOSURES

[REDACTED]

MAKING SENSE OF THE RESULTS: NORDIC BANK LENDING TO OTHER COUNTRIES

Significant cross-border lending by Nordic financial groups.

Note: See Norway stressing testing technical note for additional information.

MAKING SENSE OF THE RESULTS: NORDIC BANK-TO-BANK OWNERSHIP LINKAGES

60%16%

7%

3%2%

2%2%

8%

Norway

United States

United Kingdom

China

Other Nordic

Saudi Arabia

Canada

Other

DNB Ownership by Country(Percent of total capital as of end of 2014)

31%

24%6%

5%

5%

2%2%

4%

22%Sweden

Finland

United States

Norway

Denmark

Saudi Arabia

United Kingdom

Other

Unknown

Nordea AB Ownership by Country(Percent of total capital as of end of 2014)

48%

13%

6%

5%

4%

2%4%

18%

Denmark

Sweden

UK

Cayman Isl.

United States

Norway

Other

Unknown

Danske Bank Ownership by Country(Percent of total capital as of end of 2014)

26%

15%

3%2%2%2%7%

43%

Finland

United States

Sweden

Norway

Germany

United Kingdom

Other

Unknown

Sampo Plc Ownership by Country(Percent ot total capital as of end of 2014)

Significant cross-ownership links among Nordic financial groups.

CROSS-BORDER SPILLOVERS

DECOMPOSITION OF SPILLOVERS TO THE NORDICS

Equity and commodity prices are the major transmission channels of spillovers to the Nordics

Note: See Klößner and Wagner (2014b) for an assessment of US economic policy uncertainty on cross-border spillovers.

SPILLOVER CHANNEL DYNAMICS

• The largest share of spillovers to the Nordics has historically come from developed economies.

• Recently, spillovers from emerging economies have become more important.

Left: Spillover time-series were calculated using 3-year rolling windows. Right: colors denote low (white), moderate (pink), and high (red) levels of spillover connectivity. Connectivity is a bilateral measure which is defined as the sum of total spillovers shared between two given sectors (Diebold, Yilmaz; 2014).

TOP SPILLOVERS TO THE NORDICS*

Non-Nordic to Nordic

Global Factor to NordicNordic to Nordic

Sweden, Finland, and Denmark are responsible for the largest share of Nordic-to-Nordic spillovers

Norway is the Nordic most affected by global factors, such as commodity prices and the USD FX rate

The largest spillovers to the Nordics originate in Developed Europe, followed by Emerging Europe and North America

* Spillovers were estimated using daily market data which spanned the period of January 2002 to August 2015. In the figures above, arrow size corresponds to a rank ordering of spillover magnitude. The top, middle, and bottom third of spillovers within a given figure are denoted by large, medium, and small-sized arrows, respectively. Numbers displayed next to arrows denote the percentage of given recipient ‘s total spillovers that is attributable to a given spillover originator. For further information on spillovers from a network perspective, see Diebold and Yilmaz (2014).

TOP SPILLOVERS TO THE NORDICS, BY RECIPIENT COUNTRY

FinlandSweden

Sweden, Finland, and Denmark have the greatest exposure to many of the same spillovers: global real estate, hedge funds, Developed Europe, and each other.

Denmark

TOP SPILLOVERS TO THE NORDICS, BY RECIPIENT COUNTRY

IcelandNorway

Norway and Iceland are the least exposed to other Nordics. Both countries share large common exposures to Latin America and global real estate.

MAKING SENSE OF THE RESULTS: NORWAY GOVERNMENT PENSION FUND GLOBAL – COUNTRY/CURRENCY EXPOSURES BY ASSET CLASS

MAKING SENSE OF THE RESULTS: STATOIL COUNTRY EXPOSURES

TOP SPILLOVERS TO THE NORDICS, BY CHANNEL

Energy pricesEmerging market asset prices

Developed market asset prices

Among developed economies, Developed Europe is the source of the largest inward spillovers to the Nordics

Among emerging economies, spillovers from Emerging Europe are the greatest in magnitude

The influence of energy prices on Norway alone is greater than the cumulative influence of energy prices on all other Nordics

TOP SPILLOVERS TO THE NORDICS, BY CHANNEL

USD FX appreciation Global real estate Active asset management

Changes in the USD FX rate have had the greatest effect on Norway

Iceland is the country most affected by global real estate prices, followed by Sweden and Finland

The trading activities of hedge funds have had the largest impact on Norway and Denmark

SUMMARY OF NORDIC EXPOSURE TO INWARD SPILLOVERS

Emerging Economies

Sweden

Finland

Denmark

NorwayIceland

1 2

3

45

2

1

5

4

3

1

2

3

2

1 3

4Global Factors

Advanced Economies

Other Nordics

Among the Nordics, Sweden and Finland are the most exposed to spillovers. Iceland is the least exposed.

Sweden’s greatest exposures are to emerging economies and to other Nordics

Finland’s greatest vulnerabilities are to developed and emerging economies

Note: Greater graph area corresponds to greater inward spillover vulnerability. The numbers 1 through 5 are rank orderings and illustrate a given country’s vulnerability to a given spillover source, where ranks of ‘1’ and ‘5’ denote the highest and lowest levels of vulnerability, respectively. Some rank ordering labels are omitted to enhance figure readability.

Norway has the greatest exposure to global factors and one of the smallest to the Nordic region.

TOP SPILLOVERS FROM THE NORDICS

Nordic to Non-Nordic Nordic to Global Factors

Spillovers originating in the Nordics have the greatest impact on Developed Europe

The Nordics also exert a notable influence on energy and metal commodity prices

SYSTEM IMPORTANCE OF SPILLOVER CHANNELS

Cross-border channels

Sweden and Norway are the most systemically important Nordic countries.

Developed Europe and North America are the most systemically important transmitters of spillovers in the developed world, and Emerging Europe and the Middle East and Africa are the most systemic transmitters among emerging market economies.

The USD FX rate, global real estate, and energy and metal commodities crisis are the most systemically important global factors.

Equities universally dominant bonds in terms of systemic risk transmission.

E = energyM = metalsG = goldF = foodHF = hedge fundsRE = real estateUSD = US FX ratea = Asiae = Europela = Latin Americama = Middle East and Africana = North America

= equities

= bonds

= global factors

= Nordics= developed economy= emerging economy= global factor

BANKING AND INSURANCE CONNECTIVITY

Bank to bank connectivity Insurer to insurer connectivity

Nordic banks are highly connected with each other and with banks in North America and Developed Europe

With the exception of Sweden, the connectivity of Nordic insurers is analogous to that of Nordic banks

Note: colors denote low (white), moderate (pink), and high (red) levels of spillover connectivity. Connectivity is a bilateral measure which is defined as the sum of total spillovers shared between two given sectors (Diebold, Yilmaz; 2014).

Financial to nonfinancial sector connectivitySovereign to financial sector connectivity

NORDIC-TO-NORDIC CONNECTIVITY

Nordic sovereign-to-sovereign and financial-to-financial sector connectivity is significant, but sovereign-to-financial sector connectivity is present only at moderate levels

Levels of Nordic financial-to-nonfinancial connectivity are also highly significant

Left: red lines denote sovereign-to-sovereign connections. Right: green lines denote nonfinancial-to-nonfinancial sector connections. Both: blue line denote financial-to-financial sector connections and black lines denote connections between different types of sectors. Connectivity is a bilateral measure which is defined as the sum of total spillovers shared between two given sectors (Diebold, Yilmaz; 2014).

DOMESTIC CROSS-SECTOR SPILLOVERS

DOMESTIC CONNECTIVITY: SWEDEN AND FINLAND

Note: colors denote low (white), moderate (pink), and high (red) levels of spillover connectivity. Connectivity is a bilateral measure which is defined as the sum of total spillovers shared between two given sectors (Diebold, Yilmaz; 2014).

Sweden exhibits high levels of domestic connectivity between banks, shadow banks, and major nonfinancial sectors, but banking and insurance connectivity is low. Bank-to-sovereign connectivity is low.

Finland shows high connectivity between banks and insurers and moderate bank-to-sovereign connectivity. Finnish nonfinancial sectors are highly connected.

Sweden Finland

DOMESTIC CONNECTIVITY: DENMARK AND NORWAY

Similar to Finland, Denmark exhibits high bank-to-insurer and moderate bank-to-sovereign connectivity. Unlike other Nordics, Denmark insurers are also highly connected to domestic nonfinancial sectors.

Norway also exhibits high bank-to-insurer and moderate bank-to-sovereign connectivity. Norwegian non-financial sectors, in particular those engaged in the export of energy, industrial, and food commodities, are highly connected.

Denmark Norway

TAKEAWAYS

Nordic countries are systemically important as a whole.

For the IMF: Nordic-centric surveillance makes sense.

For authorities: Cross-border surveillance and regional cooperation (including stress testing) is important but not enough.

For the IMF and country authorities: When credit exposure data are not available, market data may be good substitutes.

REFERENCES

Csardi G, and Nepusz T, 2006, “The igraph software package for complex network research.” InterJournal, Complex Systems 1695, http://igraph.org.

Diebold, Francis X., and KamilYılmaz, 2014, "On the network topology of variance decompositions: Measuring the connectedness of financial firms." Journal of Econometrics 182, no. 1: 119-134.

Diestel, Reinhard, 2005, Graph Theory (3rd ed.), Berlin, New York: Springer-Verlag, ISBN 978-3-540-26183-4.

Klößner, S. and Wagner, S., 2014b, “International spillovers of policy uncertainty.” Economics Letters 124, no. 3: 508–512.

Pesaran, H. Hashem, and Yongcheol Shin, 1998, "Generalized impulse response analysis in linear multivariate models." Economics Letters 58, no. 1 (1998): 17-29.

ANNEX

NETWORK METHODOLOGY

1 The value of is not necessarily unique and is numerically estimated using the Power Iteration algorithm. 

Let be a network with associated sets of vertices and edges and . The eigenvector centrality score, , of a given vertex ∊ is defined as

1,

where

is a vertex which shares an edge with , , is the entry in , the adjacency matrix of , which corresponds to the vertices and , and the eigenvalue is a constant which is satisfies the relationship .1

Higher eigenvector centrality scores signify greater network importance. When is a financial network, eigenvector centrality is interpreted as a proxy for systemic risk.

DATA DESCRIPTION: CROSS-BORDER SPILLOVERSAlias Financial Index Name Spillover Group

IS OMX Iceland All Share NordicsSE Datastream Sweden Equities NordicsDK Datastream Denmark Equities NordicsFI Datastream Finland Equities Nordics

NO Datastream Norway Equities NordicsEmerging Europe MSCI Emerging Markets Europe Emerging Economies

Latin America MSCI Emerging Markets Latin America Emerging EconomiesEmerging Asia MSCI Emerging Markets Asia Emerging Economies

MENA Standard and Poor's / IFCI Middle East and Africa Emerging EconomiesDeveloped Europe FTSE Developed Europe Developed Economies

Developed Asia FTSE Developed Asia Pacific Developed EconomiesNorth America FTSE World North America Developed Economies

Emerging Europe JP Morgan GBI-Emerging Markets Europe Emerging EconomiesLatin America JP Morgan GBI-Emerging Markets Latin America Emerging EconomiesEmerging Asia JP Morgan GBI-Emerging Markets Asia Emerging Economies

MENA Citigroup World BIG Overall Africa Middle East Emerging EconomiesDeveloped Europe Citigroup World BIG Overall West Europe Developed Economies

Developed Asia Barclays Asia Pacific Bond Aggregate Developed EconomiesNorth America Citigroup World BIG Overall North America Developed Economies

Energy S&P GSCI Four Energy Commodities Spot Global FactorsMetals S&P GSCI Industrial Metals Spot Global FactorsGold S&P GSCI Precious Metal Spot Global FactorsFood S&P GSCI Agriculture Spot Global Factors

Real Estate MSCI World Real Estate Global FactorsHedge Funds HFRX Global Hedge Fund Index Global Factors

USD FX JP Morgan US Real Effective Exchange Rate (Trade-Weighted) Index Global FactorsUS Policy US Economic Policy Uncertainty Index Global Factors

Macro Risk Citi World Short Term Macro Risk Index Global FactorsMacro Risk Citi World Long Term Macro Risk Index Global FactorsMacro Risk Citigroup Economic Surprise Index, China Global FactorsMacro Risk Citigroup Economic Surprise Index, Eurozone Global FactorsMacro Risk Citigroup Economic Surprise Index, USA Global Factors

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