Relationships in the Interbank Market · 2020-02-04 · Relationships in the Interbank Market...
Transcript of Relationships in the Interbank Market · 2020-02-04 · Relationships in the Interbank Market...
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Relationships in the Interbank Market
Jonathan Chiu Jens Eisenschmidt Cyril MonnetBank of Canada European Central Bank BIS/U Bern/SZ Gerzensee
ECB Money Market Workshop
November 2019
The views expressed in this paper are not necessarily
the views of the Bank of Canada, the European Central Bank or the
Bank for International Settlements.
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Introduction
I Most central banks now implement monetary policy by usinga corridor/channel system to influence the interest rate in theinterbank market.
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Introduction
I Most central banks now implement monetary policy by usinga corridor/channel system to influence the interest rate in theinterbank market.
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But there are anomalies...
I Existence of arbitrage opportunities?
I Practitioners: concerns about “relationships”
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But there are anomalies...
I Existence of arbitrage opportunities?
I Practitioners: concerns about “relationships”
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Structure of the Interbank Market
Interbank markets exhibit a tiered structure (Stigum, 2007):
I OTC transactions: larger banks acting on their own or acustomer’s behalf
I Lending relationships: repeated transactions betweensmall-to-medium sized and larger banks
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Core-periphery Structure of the Interbank Market
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Bech and Atalay (2008)
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Related Literature
I Empirical studies stress the importance of lending relationships
I e.g. Afonso, Kovner and Schoar (2014)
“More than half of the banks form stable and persistent trading
relationships.”
I Most models of interbank markets fail to capture
I Model it as a frictionless market (e.g. Bech and Keister,2017), or randomly matched banks conducting “spot” trades(e.g. Afonso and Lagos, 2015)
I Exceptions: e.g. Blasques, Brauning, and van Lelyveld (2018)
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What We Do
I This paper models trading relationships in the interbankmarket under a corridor system
I endogenize network
I explain the anomalies
I conduct quantitative exercise based on MMSR data
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MMSR Data
I Many empirical studies rely on indirect inference and caninvolve significant measurement errors (Armantier andCopeland, 2012)
I Money Market Statistical Reporting (MMSR) dataset allowsus to study confirmed transaction data.
I Large banks (RA) are required to report money market tradesI cover about 80 percent of Euro Area money market activities
I Our sample period: July 1, 2016 to July 1, 2018:I deposit facility rate (DFR) was -0.4 %I the marginal lending facility rate was 0.25%.
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MMSR Data
I Many empirical studies rely on indirect inference and caninvolve significant measurement errors (Armantier andCopeland, 2012)
I Money Market Statistical Reporting (MMSR) dataset allowsus to study confirmed transaction data.
I Large banks (RA) are required to report money market tradesI cover about 80 percent of Euro Area money market activities
I Our sample period: July 1, 2016 to July 1, 2018:I deposit facility rate (DFR) was -0.4 %I the marginal lending facility rate was 0.25%.
![Page 12: Relationships in the Interbank Market · 2020-02-04 · Relationships in the Interbank Market Jonathan Chiu Jens Eisenschmidt Cyril Monnet Bank of Canada European Central Bank BIS/U](https://reader033.fdocuments.in/reader033/viewer/2022042621/5f5ff448dcbde41c0f3a3d77/html5/thumbnails/12.jpg)
MMSR Data
I Many empirical studies rely on indirect inference and caninvolve significant measurement errors (Armantier andCopeland, 2012)
I Money Market Statistical Reporting (MMSR) dataset allowsus to study confirmed transaction data.
I Large banks (RA) are required to report money market tradesI cover about 80 percent of Euro Area money market activities
I Our sample period: July 1, 2016 to July 1, 2018:I deposit facility rate (DFR) was -0.4 %I the marginal lending facility rate was 0.25%.
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MMSR Data: Number of Trading Partners
Figure: (a) Share of volume of non-RA by number of RA counterparties,(b) Share of volume of RA by number of counterparties
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MMSR Data: Trading Below the Floor
Among the loans from non-RA to RA, roughly 39% are conductedbelow the DFR.
Table: Summary Statistics
Non-RA to RA RA to non-RA
No. of transactions 10099 146999
Percentage of total 6.43% 93.57%
Average rates -0.38% -0.34%
Average size (millions) 53 28
Fraction of trades below DFR 38.83% 0.06%
Average rates below DFR -0.44% -0.40%
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Road Map
1. Basic model (No relationships)
I Costless participation and one-shot trade in money market
2. Extend the basic model
I Costly participation and repeated trade
I Endogenize tiered structure in the money marketI Relationship premium for interest rate
3. Quantitive exercise based on MMSR data
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Basic Model (No Relationship)
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The Basic Model (no relstionship)
I One period
I A [0,1] continunm of risk neutral, profit maximizing banks
I A liquidity shock ε ∼ G (.)
I m reserve requirement (m = 0)
I An interbank market
I A central bank offering lending (iL) and deposit (iD) facility
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Sequence of events
CB liquidity tender: lend out liquidity at 1 + i
1. Liquidity shock: ε ∼ G (ε)
2. Money mkt: bilateral trade s.t. search & bargaining
3. Standing facilities: deposit at iD , borrow at iL
SettlementD(1 + iD)
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Sequence of events
CB liquidity tender: lend out liquidity at 1 + i
1. Liquidity shock: ε ∼ G (ε)
2. Money mkt: bilateral trade s.t. search & bargaining
3. Standing facilities: deposit at iD , borrow at iL
SettlementD(1 + iD)
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Sequence of events
CB liquidity tender: lend out liquidity at 1 + i
1. Liquidity shock: ε ∼ G (ε)
2. Money mkt: bilateral trade s.t. search & bargaining
3. Standing facilities: deposit if m > m, borrow if m < mSettlement: D(1 + iD) or L(1 + iL)
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Sequence of events
CB liquidity tender: lend out liquidity at 1 + i
1. Liquidity shock: ε ∼ G (ε)
2. Money mkt: bilateral trade s.t. search & bargaining
3. Standing facilities: deposit if m > m, borrow if m < mSettlement: D(1 + iD) or L(1 + iL)
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An OTC interbank market with sorting
liquidity shock OTC money mkt standing facitlity
bargaining
borrowing& lending
m+ ε
borrowers
lenders
matching
nb
nl
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OTC interbank money market (Cont’d)
I Lender (m+ > 0) and borrower (m− < 0) negotiate anovernight loan (d , `) determined by proportional bargaining:
maxd ,`
S− + S+,
s.t.
S+ = Θ(S− + S+)
I borrower’s surplus: S− = V3(m−+d ,−`)− V3(m−, 0)
I lender’s surplus: S+ = V3(m+−d ,`)− V3(m+, 0)
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OTC interbank money market (Cont’d)I Banks split their balances
d(m+,m−) =m+ −m−
2
I OTC rate is given by
i(m+,m−) = ΘV3(m− + d)− V3(m−)
βd
+(1−Θ)V3(m+)− V3(m+ − d)
βd− 1
I OTC rate is always within the corridor
1.02 1.022 1.024 1.026 1.028 1.03 1.032 1.034 1.036 1.038 1.0430
35
40
45
50
55
60
65
OTC rates
freq
.
iD = 0.02
iL = 0.04
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Increase reserve supply
m
iD
iL
i
i + ∆
- Skew OTC rate distribution:
1.02 1.022 1.024 1.026 1.028 1.03 1.032 1.034 1.036 1.038 1.0410
20
30
40
50
60
70
80
OTC rates
freq
.
i = 0.03
i = 0.025
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Interbank Overnight Rates in Canada
−0.3 −0.2 −0.1 0 0.1 0.2 0.30
10
20
30
40
50
60
70
80
90
100Distribution of Interest Spread
Symmetric corridor
(before 2009)
−0.1 0 0.1 0.2 0.30
10
20
30
40
50
60
70
80
90
100Distribution of Interest Spread
Floor system
(2009)
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Extend the Model
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Model
I Infinite horizon: t = 1, 2, 3...
I Two types of banks:I “large” banks (as in basic model)I “small” banks
I Core interbank market:I large banks participate for free (as in basic model)I small banks need to pay a cost γ to participate⇒ incentive to build a long-term relationship and use largebank as a correspondance bank
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Model
I Infinite horizon: t = 1, 2, 3...
I Two types of banks:I “large” banks (as in basic model)I “small” banks
I Core interbank market:I large banks participate for free (as in basic model)I small banks need to pay a cost γ to participate⇒ incentive to build a long-term relationship and use largebank as a correspondance bank
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Model
I Infinite horizon: t = 1, 2, 3...
I Two types of banks:I “large” banks (as in basic model)I “small” banks
I Core interbank market:I large banks participate for free (as in basic model)I small banks need to pay a cost γ to participate⇒ incentive to use large banks as a correspondence banks bybuilding a long-term relationship with them
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Model (Cont’d)
I A relationship between a small and a large bank
I allows them to meet and trade every period before the OTCmarket opens
I subject to exogenous separation w.p. σ
I To build a relationship
I find partner in a relationship marketI single small banks pay κS to searchI single large banks pay κL to searchI subject to random matching
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Sequence of events
liquidity auction liquidity shock core money mkt standing facitlity
CB CB CB
+ +
CB
+
relationship building
relationship loans
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Relationship Building
A single bank j decides whether to search for a partner:
max{∆ρj [V j1(1)− V j
1(0)](1− σ)− κj︸ ︷︷ ︸search for a partner
, 0}
where ∆ρj = higher prob. of building a relationship
where V j1(1) = continuation value with a relationship
where V j1(0) = continuation value without a relationship
where σ = separation ratewhere κj = cost of building relationship
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Relationship Loans
I In a relationship, large bank with mL and small bank with mS
negotiate a loan (dREL, `REL).
I Proportional bargaining:
maxd ,`
TSS + TSL,
s.t.
TSS = θ(TSS + TSL)
I large bank’s surplus: TSL = V L4 (mL+d ,−`,1)− V L
4 (mL,0,0)
I small bank’s surplus: TSS = V S4 (mS−d ,`,1)− V S
4 (mS ,0,0)
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Relationship Premium for Interest Rate
Spot transaction:
i(m+,m−) =ΘV5(m− + d)− V5(m−)
βd+ (1−Θ)
V5(m+)− V5(m+ − d)
βd︸ ︷︷ ︸−1
∈[iD ,iL]
Relationship transaction:
iREL(mS ,mL) =θV L
4 (mL + d)− V L4 (mL)
βd+ (1− θ)
V S4 (mS)− V S
4 (mS − d)
βd︸ ︷︷ ︸benefit of borrower + cost of lender of
trading in current period
+θ[V L
1 (1)− V L1 (0)]− (1− θ)[V S
1 (1)− V S1 (0)]
d︸ ︷︷ ︸benefit of borrower + cost of lender of
keeping relationship tomorrow
− 1
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Relationship Premium for Interest Rate
Spot transaction:
i(m+,m−) =ΘV5(m− + d)− V5(m−)
βd+ (1−Θ)
V5(m+)− V5(m+ − d)
βd︸ ︷︷ ︸−1
∈[iD ,iL]
Relationship transaction:
iREL(mS ,mL) =θV L
4 (mL + d)− V L4 (mL)
βd+ (1− θ)
V S4 (mS)− V S
4 (mS − d)
βd︸ ︷︷ ︸benefit of borrower + cost of lender of
trading in current period
+θ[V L
1 (1)− V L1 (0)]− (1− θ)[V S
1 (1)− V S1 (0)]
d︸ ︷︷ ︸benefit of borrower + cost of lender of
keeping relationship tomorrow
− 1
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Relationship Premium for Interest Rate
Spot trade:
i(m+,m−) =ΘV5(m− + d)− V5(m−)
βd+ (1−Θ)
V5(m+)− V5(m+ − d)
βd︸ ︷︷ ︸−1
∈[iD ,iL]
Relationship transaction:
iREL(mS ,mL) =θV L
4 (mL + d)− V L4 (mL)
βd+ (1− θ)
V S4 (mS)− V S
4 (mS − d)
βd︸ ︷︷ ︸∈ [iD , iL]
benefit of
+θ[V L
1 (1)− V L1 (0)]− (1− θ)[V S
1 (1)− V S1 (0)]
d︸ ︷︷ ︸relationship premium
benecan be +ve or -vefit of
− 1
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Relationship Premium for Interest Rate
iREL(mS ,mL) =θV L4 (mL + d)− V L
4 (mL)
βd+ (1− θ)
V S4 (mS)− V S
4 (mS − d)
βd︸ ︷︷ ︸∈ [iD , iL]benefit of
+θ[V L
1 (1)− V L1 (0)]− (1− θ)[V S
1 (1)− V S1 (0)]
d︸ ︷︷ ︸relationship premium
benecan be +ve or -vefit of
− 1
E.g., when θ low, or when small bank values relationship a lot,then the relationship premium- lowers the rate when large bank borrows,- raises the rate when large bank lends
Consistent with findings in the fed funds market (Ashcraft and Duffie, 2007).
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Relationship Premium for Interest Rate
iREL(mS ,mL) =θV L4 (mL + d)− V L
4 (mL)
βd+ (1− θ)
V S4 (mS)− V S
4 (mS − d)
βd︸ ︷︷ ︸∈ [iD , iL]benefit of
+θ[V L
1 (1)− V L1 (0)]− (1− θ)[V S
1 (1)− V S1 (0)]
d︸ ︷︷ ︸relationship premium
benecan be +ve or -vefit of
− 1
E.g., when θ low, or when small bank values relationship a lot,then the relationship premium- lowers the rate when large bank borrows,- raises the rate when large bank lends
Consistent with findings in the fed funds market (Ashcraft and Duffie, 2007).
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Relationship Premium for Interest Rate (Cont’d)
1.02 1.025 1.03 1.035 1.040
5
10
15
20Relationship rates
freq
.
1.02 1.025 1.03 1.035 1.040
20
40
60
80
100OTC rates
freq
.
Consistent with experiences in many countries that the deposit rates on reservedo not always provide a lower bound for short-term market rates. (Bowman,Gagnon and Leahy, 2010)
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Endogenous Tiered Structure
Network depends on participation cost and monetary policy
high γγ = 0
i = 0.5(iD + iL)
No Relationship Many Relationships
high γi close to iD
Few Relationships
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Quantitative Exercise
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Recall: Core-periphery Structure
Median numbers of partners:
I Non-RA: 2
I RA: 182
Figure: (a) Share of volume of non-RA by number of RA counterparties,(b) Share of volume of RA by number of counterparties
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Recall: Loan Rates Below the Floor
Among the loans from non-RA to RA, roughly 39% are conductedbelow the DFR.
Table: Summary Statistics
Non-RA to RA RA to non-RA
No. of transactions 10099 146999
Percentage of total 6.43% 93.57%
Average rates -0.38% -0.34%
Average size (millions) 53 28
Fraction of trades below DFR 38.83% 0.06%
Average rates below DFR -0.44% -0.40%
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Quantitative Exercise
Parameter Definition Value
β discount factor 0.9999
i` lending facility rate −0.00001
id deposit facility rate 0.0000068
Θ lender’s bargaining power in core market 0.5
θ S bank’s bargaining power in periphery market 0.9
n measure of L banks 0.1
σ probability of relationship separation 0.003
γ core market participation cost 0.0002
κS S bank’s costs for building a new relationship 0.00001
κL L bank’s costs for building a new relationship 0.00001
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Quantitative Exercise (Cont’d)
Table: Implications of Model
Data Model
Fraction of trades where banks L are borrowers 6.43% 6.51%
Median rate when banks L borrow -0.39% -0.40%
Median rate when banks L lend -0.34% -0.32%
Fraction of loans below id when banks L borrow 38.83% 35.00%
Fraction of loans below id when banks L lend 0.06% 0.00%
Median no. of relationships of banks S 2 2
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Interbank Network
Figure: Simulated Network
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Interest Rate Distribution
Distribution of rates in core market
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2
rates (%)
0
10
20
30
40
freq
uenc
y (%
)
Distribution of rates in peripheral market
-0.6 -0.4 -0.2 0 0.2 0.4
rates (%)
0
20
40
60
80
freq
uenc
y (%
)
Figure: Interest Rate Distribution
1 2 3 4 5 6 7 8
no. of relationships
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
freq
. (%
)
Figure: No. of Relationships of Sbanks
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Quantitative Exercise: Widening the Corridor i` − id
Reduce banks’ outside optionsI lending and deposit facilities become less attractive
I increase the value of a relationship for small banks
I incresse the number of relationships
I increase the fraction of loans trading below the floor and therelationship premium
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Quantitative Exercise: Increase in small banks’ reservebalances
Reduce small banks’ need to borrowI decrease the value of a relationship to small banks
I decrease their incentives to build relationships
I reduce the number of relationships
I decrease the fraction of loans trading below the floor
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Quantitative Exercise: Increase in large banks’ reservebalances
I increase the value of a relationship to S
I increase their incentives to build relationships
I increase the number of relationships
I increase the fraction of loans trading below the floor
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Quantitative Exercise: Increase in reserve balances
−2 0 2
−0.3
−0.25
−0.2
−0.15
−0.1
w. avg. ra
tes (
%)
∆ µ
Core market
−2 0 2
−0.3
−0.25
−0.2
−0.15
−0.1
w. avg. ra
tes (
%)
∆ µ
Periphery market
−2 0 2
−0.3
−0.25
−0.2
−0.15
−0.1
∆ µ
w. avg. ra
tes (
%)
All
λ=0.5
λ=1.0
λ=1.5
Large banks are more active in the marketI Increasing the fraction of new reserves allocated to large banks
(λ ↓) leads to stronger effects
I ... because funds can reach the interbank market more directlythrough L banks
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Conclusion
I We develop a model of interbank money market featuringcostly participation and repeated relationship.
I The model helps understand
1. Policy effects on interbank network, relationships and interestrate dispersion
2. Some “anomalies”
The model is simple and tractable
I Can be used to investigate quantitively the short-run andlong-run effects of running and “exiting” the floor system.
I Many possible improvements:I Secured transactionsI Credit riskI Asset markets
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Conclusion
I We develop a model of interbank money market featuringcostly participation and repeated relationship.
I The model helps understand
1. Policy effects on interbank network, relationships and interestrate dispersion
2. Some “anomalies”
The model is simple and tractable
I Can be used to investigate quantitively the short-run andlong-run effects of running and “exiting” the floor system.
I Many possible improvements:I Secured transactionsI Credit riskI Asset markets