As opiniões expressas neste trabalho são exclusivamente do(s) autor(es) e não refletem, necessariamente, a visão do Banco fl t
i
t
i ã d B
Central do Brasil ou de seus membros.
The views expressed in this work are those of the author(s) and do not necessarily reflect those of the Banco Central do Brasil or its members. Systemic
y
Risk in the Brazilian Banking
g System
y
–
An approach by the CoVaR method
Gustavo Araújo e Sérgio Leão
Banco Central do Brasil
• The
Th aim
i off this
thi study
t d is to estimate
i t
ti t and
d
compare the contribution to the systemic risk
of Brazilian financial institutions. • For this
F thi purpose we use the
th CoVaR
C V R metric, ti
developed by Adrian & Brunnermeier (2011).
• The route for transmission of risk from one bank to another can be both direct and indirect (Brunnermeier, 2009; Brunnermeier & Pedersen, 2009; Tirole, 2011):
– Direct contagion: risks of possible default of a bank in its g
p
bilateral contracts.
– Indirect contagion: what we are most interested in this article (Liquidity Spiral)
• The indirect contagion can have an even greater i
impact on the financial system’s overall stability t
th fi
i l t ’
ll t bilit
(liquidity spiral):
– An institution experiencing an adverse liquidity shock may have to resort to hasty asset sales (fire sales), causing not only a fall in the price of those assets but also an increase
only a fall in the price of those assets, but also an increase in market volatility. • liquidity spiral (cont.) :
– This
This increase in volatility can generate additional margin increase in volatility can generate additional margin
calls and failure to meet the (microprudential) risk limits of the other institutions in the market.
the other institutions in the market. – This in turn can lead to a new movement to sell assets both by the original institution and the others affected, y
g
increasing the market volatility even more. • Liquidity spiral:
Adverse Liquidity Shock
Fire Sales
Fall in Asset Prices
Funding Liquidity P bl
Problems
Increase in Market Volatility
Additional Margin Calls
Failure to Meet the (Microprudential) (Microprudential)
Risk Limits
• In principle, the CoVaR
p
p
is able to measure the effects of this indirect contagion on the return on assets of the financial system, because it reflects how much the return of the financial system varies when one bank is suffering an adverse shock.
• We follow the method proposed by Adrian & p p
y
Brunnermeier (2011) for estimating the CoVaR.
Based on the return on assets of each bank and the
• Based on the return on assets of each bank and the aggregate of the financial system, we apply quantile
regressions in order to estimate the CoVaR of the regressions in order to estimate the CoVaR
of the
Financial System (FS) related to each bank. 1-q
q
E(X)
1-q
q
E(X)
FS is:
• We evaluate the estimated equation with the q
independent variables of interest:
• Therefore
• Database:
– The financial system considered is publicly traded Brazilian banks.
– The database used is weekly (we assumed that in the three weekly dates after the balance sheet reference date, the b k l
book values of assets and equity did not change).
f
t
d
it did t h
)
– Observations from January 1, 2006 to July 27, 2012.
– In terms of representation, the sample covers 71% of total I
f
i
h
l
71% f
l
bank assets and 85% of the assets of national private banks.
• Database:
– Institutions like CEF and HSBC were left out of the database because the method used requires the institutions to have shares listed for trading. – Of the 23 banks in our database (the FS), 16 are private and 7
7 are public. bli
– The private ones have a 79% market share (the leading participants are Itaú Unibanco and Bradesco).
participants are Itaú
and Bradesco)
– Among the private banks, three are part of multinational conglomerates the standout being Santander with a 13%
conglomerates, the standout being Santander, with a 13% share.
• There are three main caveats in reading and interpreting the results:
– The estimation period may be different for different banks.
– Some banks have few observations.
– The liquidity of the shares of some banks is small.
Institutions
i i
PINE
BTG PACTUAL
CRUZEIRO DO SUL
PANAMERICANO
DAYCOVAL
ABC-BRASIL
SANTANDER
INDUSVAL
BIC
BANESTES
SOFISA
BANCO DO EST.DE SERGIPE
NOSSA CAIXA
BANCO DO BRASIL
RENNER
MERCANTIL DO BRASIL
BANCO DA AMAZONIA
BANRISUL
ITAU UNIBANCO
BRADESCO
SUDAMERIS
ALFA
BRB
VaR 5%
VaR 1%
-15.6%
-13.0%
-13.0%
-12.3%
12 3%
-10.8%
-10.7%
-10.6%
-10
10.6%
6%
-9.9%
-9.7%
-9.6%
-9.2%
-9.2%
-9.0%
-8.7%
-8.1%
-8.0%
-7.7%
-7.6%
-7.5%
-6.8%
6 8%
-6.3%
-6.2%
-32.6%
-14.1%
-17.8%
-26.3%
26 3%
-16.1%
-15.3%
-22.2%
-30
30.1%
1%
-15.6%
-24.7%
-17.3%
-16.1%
-18.3%
-15.6%
-17.0%
-15.0%
-15.7%
-15.9%
-14.6%
-12.4%
-13.5%
13 5%
-9.0%
-10.6%
I tit ti
Institutions
BANCO DO BRASIL
ITAU UNIBANCO
BRADESCO
DAYCOVAL
CRUZEIRO DO SUL
PINE
RENNER
BANRISUL
ABC-BRASIL
BTG PACTUAL
ALFA
SOFISA
BANESTES
SANTANDER
BANCO DO EST. DE SERGIPE.
BANCO DA AMAZONIA
INDUSVAL
BIC
SUDAMERIS
BRB
MERCANTIL DO BRASIL
NOSSA CAIXA
PANAMERICANO
-4,90%
-4,80%
-4,80%
-3,90%
3 90%
-3,60%
-3,50%
-3,50%
-2 80%
-2,80%
-2,60%
-2,60%
-2,40%
-2
2,10%
10%
-2,10%
-2,10%
-2,10%
-1,90%
,
-1,80%
-1,70%
-1,10%
-1,10%
-1,00%
-0,40%
-0,10%
-8,60%
-10,10%
-9,00%
-5,70%
5 70%
-10,00%
-8,80%
-2,10%
-4 80%
-4,80%
-6,10%
-2,80%
-5,70%
-9
9,90%
90%
-7,00%
-6,20%
-4,00%
-6,70%
,
-5,70%
-2,30%
-4,20%
-0,70%
-2,40%
-0,40%
-1,00%
Graph 2 – VaR1% x CoVaR
Graph 1 – VaR5% x CoVaR
‐11.0%
‐9.0%
‐9.0%
‐7.0%
‐7.0%
CoVaR
CoVaR
‐11.0%
‐5.0%
‐3.0%
‐5.0%
‐3.0%
‐1.0%
1 0%
‐1.0%
1 0%
1.0%
1.0%
‐16.0%
‐14.0%
‐12.0%
VaR5%
‐10.0%
‐8.0%
‐6.0%
‐33.0%
‐28.0%
‐23.0%
VaR1%
‐18.0%
‐13.0%
‐8.0%
• Final Considerations:
– The aim of this article is to evaluate the application of a measure of systemic risk – the CoVaR – to the Brazilian banking system.
– the relevant metric is CoVaR, which measures the contribution of a single financial institution to the entire system’s risk.
• The results indicate that:
i.
the VaR is an insufficient measure to capture an institution’s systemic risk; ii. although the largest institutions have the lowest individual risk, they pose the highest systemic risks; iii. some small institutions are also among the group presenting high systemic risks; • Results(cont.):
iv. an additional unit of individual risk for larger institutions is more strongly related to greater systemic risk than an additional unit of individual risk in a small institution; v. on average, the systemic risk is lower for public‐sector FIs than for private‐sector ones.
For more details about this work, see WPS For
more details about this work, see WPS
307 in the BCB home page.
Thank You
Thank You
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