Hedging Demand Deposits Interest Rate Margins Jean-Paul LAURENT, Mohamed HOUKARI
[email protected] ;
[email protected] Alexandre ADAM, BNP Paribas Asset and Liability Management Mohamed HOUKARI, ISFA, Université de Lyon, Université Lyon 1 and BNP Paribas ALM Jean-Paul LAURENT, ISFA, Université de Lyon, Université Lyon 1
PRESENTATION OUTLOOK
Overview and Context
Modeling Framework, Objective and Optimal Strategy
Empirical Results
Conclusions
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
2
Demand Deposits in Bank Balance Sheet
Demand Deposits involve huge amounts
(Bank of America Annual Report – Dec. 2007; Source: SEC) Average Balance 2007
(Dollars in millions)
2006
Assets Federal funds sold and securities purchased under agreements to resell
$
155,828
$
175,334
Trading account assets
187,287
145,321
Debt securities
186,466
225,219
Loans and leases, net of allowance for loan and lease losses
766,329
643,259
All other assets
306,163
277,548
Total assets
$
1,602,073
$
1,466,681
$
717,182
$
672,995
Liabilities Deposits
253,481
286,903
82,721
64,689
Commercial paper and other short-term borrowings
171,333
124,229
Long-term debt
169,855
130,124
70,839
57,278
1,465,411
1,336,218
136,662
130,463
Federal funds purchased and securities sold under agreements to repurchase Trading account liabilities
All other liabilities Total liabilities Shareholders’ equity Total liabilities and shareholders’ equity
$
1,602,073
$
1,466,681
US Banks are monitored by the SEC as for Interest Rate Risk
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
3
Demand Deposit Interest Rate Margin – Definition
Demand Deposit Interest Rate Margin for a given quarter:
Income generated by the investment of Demand Deposit Amount on interbank markets while paying a deposit rate to customers
Risks in Interest Rate Margins:
Interest Rate Risk:
1. Investment on interbank markets
2. Paying an interest rate to customers (possibly correlated to market rates)
3. Demand Deposit amount is subject to transfer effects from customers, due to market rate variations
Non hedgeable Risk Factors on the Deposit Amount:
Business Risk: Competition between banks, customer behavior independent from market conditions, etc.
Model Risk
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
4
We need to focus on Interest Rate Margins…
… according to the IFRS (International accounting standards) :
The IFRS recommend the accounting of non maturing assets and liabilities at Amortized Cost / Historical Cost
Being studied: Recognition of related hedging strategies from the accounting viewpoint
Interest Margin Hedge (IMH).
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
5
Why do not we use the Demand Deposit Fair Value?
The fair value of Demand Deposits:
is computed by Discounting future interest rate margins on the DD activity
Risk-neutral expectation of the related sum
Demand Deposits are a complex financial product!
The fair-value involves some pricing of non-hedgeable risks
Business risk, customers’ behaviour, etc.
Which risk-neutral measure should we use?
Practical concern for banking establishments
Fair Value-based hedging strategies lack of robustness as for model specification.
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
6
Risk Mitigation within Interest Rate Margins
Hedging Demand Deposit Interest Rate Margins:
We mitigate risk using Interest Rate Derivatives such as Interest Rate Swaps
We include a risk premium on interest rate markets
Investing in long-term assets financed by short-term liabilities is rewarding.
Return-Risk Tradeoff between:
Risk Reduction:
Using Interest Rate Swaps
Return Opportunities:
Friday, 30th 2009
Taking advantage of long term investment risk premium.
Hedging Demand Deposits Interest Rate Margins
7
PRESENTATION OUTLOOK
Overview and Context
Modeling Framework, Objective and Optimal Strategy
Empirical Results
Conclusions
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
8
Setting the Objective Interest Rate Margin
IRM g (K T , LT ) = K T (LT − g (LT )) ⋅ ∆T
Deposit Amount at T Investment Market Rate during time interval [T,T+∆T] Customer rate at T
Mean-variance framework:
Including a return constraint – due to the interest rate risk premium
[
min E IRM g (K T , LT ) − S S
Friday, 30th 2009
]
2
under constraint
[
]
E IRM g (K T , LT ) − S ≥ r
Hedging Demand Deposits Interest Rate Margins
9
Dynamics for Market Rate
Lt = L(t , T , T + ∆T )
Libor Market Model for Investment Market Rate
dLt = µ L dt + σ L dWL (t ) Lt
µL ≠ 0
Ex.: Brace, Gatarek, Musiela (1997)
Long-Term Investment Risk Premium
Coefficient specification assumptions:
Our model: µ L , σ L constant (and can be easily extended to time-dependent framework)
‘Almost Complete’ framework
Friday, 30th 2009
H. Pagès (1987), Pham, Rheinländer, Schweizer (1998), Laurent, Pham (1998) W µ L , σ L bounded and adapted to F L Hedging Demand Deposits Interest Rate Margins
10
Deposit Amount Dynamics
Diffusion process for Deposit Amount
[
]
dK t = K t µ K dt + σ K d WK (t )
(US marketplace)
Sensitivity of deposit amount to market rates
Money transfers between deposits and other accounts
Interest Rate partial contingence.
680
4
660
3,5
640
3
620 2,5 600 2 580 1,5 560 1
540
Friday, 30th 2009
juil-07
avr-07
janv-07
juil-06
oct-06
avr-06
janv-05
juil-04
oct-04
avr-04
janv-04
juil-03
oct-03
avr-03
janv-03
juil-02
dWK (t ) = ρdWL (t ) + 1 − ρ 2 dWK (t )
oct-02
avr-02
janv-02
juil-01
oct-01
avr-01
oct-00
0 janv-01
500 janv-06
Incomplete market framework
juil-05
0,5
US Demand Deposit Amount US M2 Own Rate
520
oct-05
Business risk, …
avr-05
−1 < ρ < 0
Hedging Demand Deposits Interest Rate Margins
11
97
Euro Overnight Deposits
EuroZone − µˆ K = 10.19%, σˆ K = 6.56%
Friday, 30th 2009 Turkey - M1-M0
Hedging Demand Deposits Interest Rate Margins sept-07
mai-07
janv-07
sept-06
mai-06
janv-06
sept-05
mai-05
janv-05
sept-04
mai-04
janv-04
sept-03
mai-03
janv-03
sept-02
mai-02
janv-02
0
mai-01
0
sept-01
100
janv-01
500
mai-00
1000
sept-00
300
janv-00
400
mai-99
1500
sept-99
30000
2500 600
15000 200
200
0
UAH Bln.
500
janv-99
2000
mai-98
US and Euro Zone
sept-98
700
TRY Bln.
3000
USD bln.
800
janv-98
EUR bln. 3500
sept-97
19 -0 9 9 19 8-0 98 1 19 -0 9 5 19 8-0 99 9 19 -0 9 1 19 9-0 99 5 20 -0 0 9 20 0-0 00 1 20 -0 0 5 20 0-0 01 9 20 -0 0 1 20 1-0 01 5 20 -0 0 9 20 2-0 02 1 20 -0 0 5 20 2-0 03 9 20 -0 0 1 20 3-0 03 5 20 -0 0 9 20 4-0 0 1 20 4-0 04 5 20 -0 0 9 20 5-0 05 1 20 -0 0 5 20 5-0 06 9 20 -0 0 1 20 6-0 0 5 20 6-0 07 9 20 -0 0 1 20 7-0 07 5 -0 9
19
Deposit Amount Dynamics – Examples
dK t = K t (µ K dt + σ K dWK (t )) Emerging Markets (Turkey, Ukraine) 400
25000 350
20000 300
250
10000 150
5000 100
50
0
US Demand Deposits
Ukraine - M1-M0
Turkey − µˆ K = 51.74%, σˆ K = 37.38% 12
Modeling Deposit Rate – Examples
We assume the customer rate to be a function of the market rate.
Affine in general (US) / Sometimes more complex (Japan)
g (LT ) = α + β ⋅ LT
g (LT ) = (α + β ⋅ LT ) ⋅ 1{LT ≥ R}
United States
Japan
3.00% M2 Own Rate
0,9 JPY Libor 3M
0,8
2.50%
Japanese M2 Own Rate
0,7 2.00%
0,6
Affine Dependance
0,5
1.50%
0,4 1.00%
0,3
Quasi Zero Rates !
0,2 0.50%
0,1 USD 3M Libor Rate
Hedging Demand Deposits Interest Rate Margins
mars-07
sept-06
mars-06
sept-05
mars-05
sept-04
mars-04
sept-03
mars-03
sept-02
mars-02
sept-01
mars-01
sept-00
mars-00
sept-99
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
0.00%
Friday, 30th 2009
mars-99
0
0.00%
13
Sets of Hedging Strategies
1st case: Investment in FRAs contracted at t=0
… is contained in …
H S 1 = {S = θ (LT − L0 ) ; θ ∈ R}
2nd case: Dynamic self-financed strategies taking into account the evolution of market rates only
HS2
… is contained in …
T ⎧ ⎫ L L L = ⎨S = ∫ θ t dLt ; θ ∈ Θ ⎬ 0 ⎩ ⎭
Set of admissible investment strategies adapted to
F WL
3rd case: Dynamic strategies taking into account the evolution of the deposit amount T ⎧ ⎫ H D = ⎨S = ∫ θ t dLt ; θ ∈ Θ⎬ 0 ⎩ ⎭
z Friday, 30th 2009
Set of admissible investment strategies adapted to
F WL ∨ F WK
‘Admissible strategies’ are such that each of the sets above are closed Hedging Demand Deposits Interest Rate Margins
14
Variance-Minimal Measure
Martingale Minimal Measure / Variance Minimal Measure T ⎛ 1T 2 ⎞ dP ⎜ = exp⎜ − ∫ λ dt − ∫ λdWL (t )⎟⎟
Martingale Minimal Measure: dP 0 ⎝ 20 ⎠ Föllmer, Schweizer (1990)
In ‘almost complete models’, it coincides with the variance minimal measure:
⎡ dQ ⎤ P ∈ Arg min E P ⎢ Q∈Π RN ⎣ dP ⎥⎦
2
Delbaen, Schachermayer (1996)
N.B.: In our case, the Variance Minimal Measure density is a power λ − function of the Libor rate. dP ⎛ LT ⎞ σ ⎛1 ⎞ = ⎜ ⎟ exp ⎜ ( λ 2 − λσ L ) T ⎟ L
dP
Friday, 30th 2009
⎝ L0 ⎠
⎝2
Hedging Demand Deposits Interest Rate Margins
⎠
15
Optimal Dynamic Hedging Strategy – Case #2 T ⎡ ⎤ P minL E ⎢ IRM g (K T , LT ) − ∫ θ t dLt ⎥ θ ∈Θ 0 ⎣ ⎦
In Case #2, we determine:
The projection theorem applies
Delbaen, Monat, Schachermayer, Schweizer, Stricker (1997)
In case #2, the solution consists in replicating
where
2
ϕ S 2 (LT )
ϕ S 2 ( x ) = E P [IRM g (K T , LT ) LT = x ]− E P [IRM g (K T , LT )]
Under the “almost complete” assumption, this payoff can be replicated on interest rate markets.
Friday, 30th 2009
N.B.: The latter payoff is a function of
LT
Hedging Demand Deposits Interest Rate Margins
16
Optimal Dynamic Hedging Strategy – Case #3 2 T ⎡ ⎤ P We recall the related problem: min E ⎢ IRM g (K T , LT ) − ∫ θ t dLt ⎥ θ ∈Θ 0 ⎣ ⎦
The solution is dynamically determined as follows: P ∂ E λ ** t [IRM (K T , LT )] θt = + EtP IRM g (K T , LT ) − Vt x** , θ ** ∂Lt σ L Lt
[ [
Delta term
+
Hedging Numéraire
] (
×
)]
Feedback term -
Shift between the RN anticipation of the margin and the present value of the hedging portfolio
Investment in some Elementary Portfolio which verifies This portfolio aims at some fixed return while minimizing the final quadratic dispersion. Friday, 30th 2009
2
⎡ λ ⎤ ⎡ ⎤ EP ⎢∫ dLt − (− 1)⎥ = min E P ⎢ ∫ θ t dLt − (− 1)⎥ θ ∈Θ ⎣ 0 σ L Lt ⎦ ⎣0 ⎦ T
T
Hedging Demand Deposits Interest Rate Margins
2
17
Optimal Dynamic Hedging Strategy – Some Remarks
Case of No Deposit Rate: g (LT ) = 0
Explicit solution (Duffie and Richardson (1991)):
[
] , L )] ⎛ ρσ = ⎜1 +
EtP IRM g (K T , LT ) = K t Lt exp[(T − t )(µ K − ρσ K λ + ρσ K σ L )]
[
∂EtP IRM g (K T ∂Lt
T
⎜ ⎝
K
σL
⎞ ⎟⎟ K t exp[(T − t )(µ K − ρσ K λ + ρσ K σ L )] ⎠
The model works for ‘almost complete models’
The Hedging Numéraire remains the following: t
HN t = 1 + ∫ 0
Friday, 30th 2009
λ σ L Lt
2
dLt
or
T T ⎡ ⎤ ⎡ ⎤ λ P P E ⎢∫ dLt − (− 1)⎥ = min E ⎢ ∫ θ t dLt − (− 1)⎥ θ ∈Θ ⎣ 0 σ L Lt ⎦ ⎣0 ⎦
Hedging Demand Deposits Interest Rate Margins
2
18
PRESENTATION OUTLOOK
Overview and Context
Modeling Framework, Objective and Optimal Strategy
Empirical Results
Conclusions
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
19
Comparing Strategies in Mean-Variance Framework
Efficient Frontiers
Dynamic Efficient Frontier vs. Other Strategies at minimum variance point
More discrepancies between strategies when the deposit rate escapes from linearity Mean-Variance Framework - No Deposit Rate
Mean-Variance Framework - Barrier Deposit Rate Barrier Threshold = 3,00% - L(0) = 2,50% Deposit Rate = a. L(T) + b if L(T) > Threshold; a = 30% ; b = -0,50%
3,45
3,20
3,40 3,35 Expected Return
Expected Return
3,15
3,10
3,05
3,30 3,25 3,20 3,15
3,00 3,10 2,95 0,20
0,22
0,24
0,26
0,28
0,30
0,32
0,34
0,36
0,38
0,40
3,05 0,15
0,20
0,25
0,30
0,35
Standard Deviation
Blue: Unhedged Margin
Green: Delta-Hedging at t=0 only
Red: Optimal Dynamic Strategy following only market rates
Purple: Dynamic Delta-Hedging
0,40
0,45
0,50
0,55
0,60
0,65
Standard Deviation
The performances of other hedging strategies strongly depend upon the specification of the deposit rate.
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
20
Dealing with Deposits’ ‘Specific’ Risk
Comparing the optimal dynamic strategy following only market rates (blue) and the optimal dynamic strategy following both rates and deposits (pink):
At minimum variance point (risk minimization)
As expected, the deposits’ ‘specific’ risk is better assessed using a dynamic strategy following both rates and the deposit amount Risk Reduction and Correlation Total Deposit Volatility = 6.5% - K(0) = 100 0,35
Hedged Margin Standard Deviation
0,30 0,25 0,20 0,15 0,10 Optimal Dynamic Hedge (Rates)
0,05
Optimal Dynamic Hedge (rates + deposits)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Deposit / Rates Correlation Parameter
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
21
Robustness towards Risk Criterion
The mean-variance optimal dynamic strategy (following deposits and rates) behaves quite well under other risk criteria
Example of Expected Shortfall (99.5%) and VaR (99.95%). ES (99.5%)
Standard Deviation Barrier Deposit Rate
Expected Return Level
Risk Reduction
Level
VaR (99.95%)
Risk Reduction
Level
Unhedged Margin
3.16
0.39
Static Hedge Case 1
3.04
0.28
-0.11
-2.34
-0.32
-2.26
-0.36
Static Hedge Case 2
3.01
0.23
-0.16
-2.26
-0.24
-2.04
-0.14
Jarrow and van Deventer
3.01
0.24
-0.15
-2.35
-0.33
-2.25
-0.35
Optimal Dynamic Hedge
3.01
0.22
-0.17
-2.38
-0.36
-2.29
-0.39
The optimal dynamic strategy features better tail distribution than for other strategies
Blue: Optimal Dynamic Strategy (following rates)
Pink: Optimal Dynamic Strategy (following both deposits and rates)
-1.90
Probability Densities Hedging Following Rates vs. Hedging Following Deposits and Rates 1,6 1,4
Hedging Following Rates
1,2
Hedging Following Rates and D it
1,0 Density
-2.02
Risk Reduction
0,8 0,6 0,4 0,2 -
-
0,50
1,00
1,50
2,00
2,50
3,00
3,50
4,00
4,50
5,00
Interest Rate Margin Level (incl. Hedge)
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
22
Dealing with Massive Bank Run
Introducing a Poisson Jump component in the deposit amount:
[
]
dK t = K t µ K dt + σ K d WK (t ) − dN (t )
(N (t ))0≤t ≤T is assumed to be independent from WK and
WL
∂EtP [IRM (KT , LT )] λ + EtP IRM g (K T , LT ) − Vt x** , θ ** Then, we have: θ = ∂Lt σ L Lt ** t
[ [
] (
)]
EtP ⎣⎡ IRM g ( KT , LT ) ⎦⎤ = e −γ (T −t ) × (Previous conditional expectation term)
Due to independence, the jump element can be put out the conditional expectations
N.B.: When a bank run occurs, the manager keeps investing the current hedging portfolio’s value in the Hedging Numéraire
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
23
PRESENTATION OUTLOOK
Overview and Context
Modeling Framework, Objective and Optimal Strategy
Empirical Results
Conclusions
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
24
Conclusions (1)
A dynamic strategy to assess risk in mean-variance framework
Results about Mean-variance hedging in incomplete markets yield explicit dynamic hedging strategies
Practical Conclusions:
Better assessment of deposits’ ‘specific’ risk with a dynamic strategy taking into account both deposits and rates;
Lack of stability for other strategies towards the deposit rate’s specification;
Robustness towards risk criterion
No negative consequences as for tail distribution
Additivity of Optimal Dynamic Strategies
Applicable to various balance sheet items
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
25
Conclusions (2)
We use some mathematical finance concepts:
For Financial Engineering problems
with the aim of providing applicable strategies
And improve risk management processes
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
26
Technical References
Duffie, D., Richardson, H. R., 1991. Mean-variance hedging in continuous time. Annals of Applied Probability 1(1).
Gouriéroux, C., Laurent, J.-P., Pham, H., 1998. Mean-variance hedging and numéraire. Mathematical Finance 8(3).
Hutchison, D., Pennacchi, G., 1996. Measuring Rents and Interest Rate Risk in Imperfect Financial Markets : The Case of Retail Bank Deposits. Journal of Financial and Quantitative Analysis 31(3).
Jarrow, R., van Deventer, D., 1998. The arbitrage-free valuation and hedging of demand deposits and credit card loans. Journal of Banking and Finance 22.
O’Brien, J., 2000. Estimating the value and interest risk of interest-bearing transactions deposits. Division of Research and Statistics / Board of Governors / Federal Reserve System.
Friday, 30th 2009
Hedging Demand Deposits Interest Rate Margins
27