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Networks of counterparties in the centrally cleared EU-wideinterest rate derivatives market1
Pawe l Fiedor∗ Sarah Lapschies∗ Lucia Orszaghova∗,†,‡
∗European Systemic Risk Board Secretariat
†Narodna banka Slovenska
‡University of Economics in Bratislava
1The views expressed are not necessarily the views of the ESRB, or the ESCB.
Overview of the presentation
Dataset
Results
Conclusions
What data do we use?
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339
0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
Dataset
All open centrally cleared interest rate derivative contracts in the EU:
I From all 6 trade repositories
I Including both house & client clearing
Trade Repository # of contracts
UnaVistaDTCC OTCDTCC ETDRegis-TRKDPWCMEICE
Total 4,157,339 0.0
0.2
0.4
0.6
0.8
1e+05 1e+08 1e+11Notional amount (EUR)
Den
sity
What kind of companies are in the network?
Institutions
We have a variety of institutions present in the centrally cleared IRD market:
Type of institution Full House Client
CCP 17 17 0G16 16 15 16Bank 608 184 591Other financial 5,438 492 5,246Insurance & pension 420 7 419Non-financial 86 12 82
Total 6,585 727 6,354
Institutions
We have a variety of institutions present in the centrally cleared IRD market:
Type of institution Full House Client
CCP 17 17 0G16 16 15 16Bank 608 184 591Other financial 5,438 492 5,246Insurance & pension 420 7 419Non-financial 86 12 82
Total 6,585 727 6,354
Institutions
We have a variety of institutions present in the centrally cleared IRD market:
Type of institution Full House Client
CCP 17 17 0G16 16 15 16Bank 608 184 591Other financial 5,438 492 5,246Insurance & pension 420 7 419Non-financial 86 12 82
Total 6,585 727 6,354
Institutions
We have a variety of institutions present in the centrally cleared IRD market:
Type of institution Full House Client
CCP 17 17 0G16 16 15 16Bank 608 184 591Other financial 5,438 492 5,246Insurance & pension 420 7 419Non-financial 86 12 82
Total 6,585 727 6,354
Institutions
We have a variety of institutions present in the centrally cleared IRD market:
Type of institution Full House Client
CCP 17 17 0G16 16 15 16Bank 608 184 591Other financial 5,438 492 5,246Insurance & pension 420 7 419Non-financial 86 12 82
Total 6,585 727 6,354
What does the network look like?
The network structure
Around 90% of the counterparty relations are on the client clearing side.
The network structure
The full network has three tiers: inner core, outer core, and periphery.
The network structure
House clearing network (on the left) has a different structure: only two tiers.
The network structure
The inner core, of mostly large dealers, creates the backbone of the network.
Is the network stable over time?
Persistence across time
The network is relatively stable between Q3 & Q4 of 2016, including thecounterparty relations.
Persistence across time
The network is relatively stable between Q3 & Q4 of 2016, including thecounterparty relations.
CC
P−C
MC
M−C
lientFU
LL
AUD BRL CAD CHF CZK DKK EUR GBP HKD HUF JPY MXN NOK NZD PLN SEK SGD USD ZAR
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
Currency
% o
f edg
es
common only in one period
CC
P−C
MC
M−C
lientFU
LL
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
2056
2057
2058
2059
2060
2061
2062
2063
2064
2065
2066
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
0.00
0.25
0.50
0.75
1.00
Maturity year
% o
f edg
es
common only in one period
What can we find in the networks?
Average number of counterparty relations by type
Difference between the full network and the house cleaning network by maturity
BANK CCP G16 INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
1
10
100
Maturity year
Deg
ree
BANK CCP G16 INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
2020
2030
2040
2050
2060
1
10
Maturity year
Deg
ree
Average number of counterparty relations by type
Difference between the full network and the house cleaning network by currency
0
50
100
150
200
AUD BRL CAD CHF CZK DKK EUR GBP HKD HUF JPY KRW MXN NOK NZD PLN SEK SGD USD ZARCurrency
Deg
ree
TYPE BANK G16 INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
0
1
2
3
AUD BRL CAD CHF CZK DKK EUR GBP HKD HUF JPY MXN NOK NZD PLN SEK SGD USD ZARCurrency
Deg
ree
TYPE BANK G16 INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
Are the networks stable if we remove counterparties?
Random removal of counterparties by type
We remove a number of institution at random and see how many additionalones are disconnected with the main component.
Random removal of counterparties by type
For the full network G16 dealers have the most effect, followed by banks, andonly then CCPs.
Random removal of counterparties by type
For the house clearing network this information is lost, while it’s useful forfinancial stability, e.g. question of the suspension of clearing obligation.
Removal of the largest clearing members
We remove a number of the largest clearing members and see how manyadditional ones are disconnected with the main component.
BANK INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100
0.00
0.25
0.50
0.75
1.00
Number of removed clearing members
% o
f ins
titut
ions
losi
ng a
cces
s to
the
mai
n m
arke
t hub
Access to liquidity
We define access to liquidity of an institution as the total number ofcounterparty relations of its direct neighbours.
Type of institution Total access to liquidity Average access to liquidity
G16 16,899 1,056.19Non-financial 9,580 111.40Bank 15,046 24.75Insurance & pension 9,839 23.43Other financial 17,160 3.16
When we remove clearing members at random the loss of access to liquidity isproportional to the starting access to liquidity, irrespective of the type of theinstitution.
Access to liquidity
We define access to liquidity of an institution as the total number ofcounterparty relations of its direct neighbours.
Type of institution Total access to liquidity Average access to liquidity
G16 16,899 1,056.19Non-financial 9,580 111.40Bank 15,046 24.75Insurance & pension 9,839 23.43Other financial 17,160 3.16
When we remove clearing members at random the loss of access to liquidity isproportional to the starting access to liquidity, irrespective of the type of theinstitution.
Access to liquidity
We define access to liquidity of an institution as the total number ofcounterparty relations of its direct neighbours.
Type of institution Total access to liquidity Average access to liquidity
G16 16,899 1,056.19Non-financial 9,580 111.40Bank 15,046 24.75Insurance & pension 9,839 23.43Other financial 17,160 3.16
When we remove clearing members at random the loss of access to liquidity isproportional to the starting access to liquidity, irrespective of the type of theinstitution.
Access to liquidity
We define access to liquidity of an institution as the total number ofcounterparty relations of its direct neighbours.
Type of institution Total access to liquidity Average access to liquidity
G16 16,899 1,056.19Non-financial 9,580 111.40Bank 15,046 24.75Insurance & pension 9,839 23.43Other financial 17,160 3.16
When we remove clearing members at random the loss of access to liquidity isproportional to the starting access to liquidity, irrespective of the type of theinstitution.
Access to liquidity
However, it is still useful to see what the impact of the removal of the largestclearing members is on the access to liquidity of various types of institutions.
BANK G16 INSURANCE & PENSION NON−FINANCIAL OTHER FINANCIAL
1 10 100
1000 1 10 10
0
1000 1 10 100
1000 1 10 10
0
1000 1 10 10
0
1000
0.00
0.25
0.50
0.75
1.00
Number of removed clearing members
% lo
ss in
acc
ess
to li
quid
ity
Conclusions
Main findings:
I Client clearing is important and changes the perception of the centrallycleared interest rate derivatives market dramatically:
I In particular, the insurance sector is only visible via client clearing;I Importance of various types of institutions changes dramatically;
I CCPs are not systemic in isolation, and should be analysed in conjunctionwith G16 dealers – also for policy issues (e.g. R&R).
Conclusions
Main findings:
I Client clearing is important and changes the perception of the centrallycleared interest rate derivatives market dramatically:
I In particular, the insurance sector is only visible via client clearing;I Importance of various types of institutions changes dramatically;
I CCPs are not systemic in isolation, and should be analysed in conjunctionwith G16 dealers – also for policy issues (e.g. R&R).
Conclusions
Main findings:
I Client clearing is important and changes the perception of the centrallycleared interest rate derivatives market dramatically:
I In particular, the insurance sector is only visible via client clearing;
I Importance of various types of institutions changes dramatically;
I CCPs are not systemic in isolation, and should be analysed in conjunctionwith G16 dealers – also for policy issues (e.g. R&R).
Conclusions
Main findings:
I Client clearing is important and changes the perception of the centrallycleared interest rate derivatives market dramatically:
I In particular, the insurance sector is only visible via client clearing;I Importance of various types of institutions changes dramatically;
I CCPs are not systemic in isolation, and should be analysed in conjunctionwith G16 dealers – also for policy issues (e.g. R&R).
Conclusions
Main findings:
I Client clearing is important and changes the perception of the centrallycleared interest rate derivatives market dramatically:
I In particular, the insurance sector is only visible via client clearing;I Importance of various types of institutions changes dramatically;
I CCPs are not systemic in isolation, and should be analysed in conjunctionwith G16 dealers – also for policy issues (e.g. R&R).
Thank you