Maturity mismatch, open market operations (and liquidity regulation) - preliminary - Jens Eisenschmidt and Cornelia Holthausen Vienna, 3 October 2011 The views expressed in this paper are our own and do not necessarily reflect those of the ECB or the Eurosystem

2 What the paper is about Observations –Higher demand for central bank (ECB) liquidity during crisis, especially longer term –Anecdotal evidence: especially banks with need to roll-over funding had high demand for long-term funds Aim of this paper –Establish link between these observations Do banks with high maturity mismatch rely more heavily on central bank liquidity? Can we justify this theoretically?

3 What the paper is about Observations –Higher demand for central bank (ECB) liquidity during crisis, especially longer term –Anecdotal evidence: especially banks with need to roll-over funding had high demand for long-term funds Aim of this paper –Establish link between these observations Do banks with high maturity mismatch rely more heavily on central bank liquidity? Can we justify this theoretically?

4 Background In pre-crisis times, the Eurosystem conducted –Main refinancing operations (MRO): 1 week maturity –Longer-term refinancing operations (LTROS): 3 month Until October 2008: variable rate tenders –Pre-fixed quantity; Pay-your-bid –Higher demand → higher willingness to pay → increased marginal bid rates –Banks were willing to pay premium to obtain central bank liquidity –This was especially the case for longer-term operations (LTROs, 3m maturity)

5 Premium for long-term central bank funds Marginal rates in 3-month LTROs and 3-month OIS rates at day of the auction, January 2006 – September 2008

6 Preference for longer-term central bank refinancing

7 Introduction – maturity mismatch Why did banks prefer longer-term refinancing from CB? This paper argues: –Banks want to reduce their maturity mismatch Assets: long term Liabilities: short term –Frequent roll-over of loans could also signal stress (“stigma” of market funding) → better to appear in market less frequently –Market for longer-term loans dried up –This increased demand for longer-term CB funds

8 Introduction This paper: 1.High stylized theoretical model explaining the bidding behaviour of banks that care about their maturity mismatch –Also considering the effects of the liquidity regulation (esp. Basel III) 2.Empirical investigation of how bank’s bidding behaviour relates to their credit risk and how the credit risk relates to the maturity structure of their balance sheets

9 Outline 1.Introduction 2.Literature review 3.A theoretical model of maturity mismatch and central bank liquidity Liquidity regulation 4.Empirical analysis 5.Conclusion

10 2.Related literature Maturity structure of bank balance sheets –Baltensperger (1980) –Flannery (AER, 1994); Diamond (QJE, 1991) –Brunnermeier/Oehmke (2010) Recently proposed liquidity regulation –Huberman/Repullo (2010) –Perotti/Suarez (2010) –Bindseil/Lamoot (2011) –Schmitz (2011)

11 3.A theoretical model - assumptions Banks Large number of identical, risk neutral banks Balance sheet size of 1 Long-term riskless assets (from time 0, until beyond time 3) Liabilities: –An amount 1- α 0 is already financed (long-term) –The amount α 0 needs to be refinanced at time 1 –Options are: short term (1 period), long-term (2 periods), in the market, or with the central bank –Composition of funding is known (no private information)

12 More assumptions Financial crisis With probability γ, there is a financial crisis at time 2 or time 3 A financial crisis is persistent, i.e. will last more than one period When there is a financial crisis at time 2, it is expected that –Lenders could hoard liquidity; rolling-over of loans might not be fully possible –Knowing this, and assuming they will need to liquidate their project / go bankrupt in this case, borrowers may not always repay

13 More assumptions Interbank market There are risk neutral, cash-rich agents who seek profitable investment opportunities and may lend in the unsecured interbank market (In crisis times, these agents might withdraw) They have an outside option to invest at the riskless rate → Interest rate is determined by them Assume that the probability of a bank repaying a loan is inversely related to its share of short-term funding ( α 1 ) When α 1 = 0 (only LT loans): sure repayment When α 1 > 0: pr(repayment) is lower if crisis is likely

14 Timing Time t=0t=1t=2t=3 Assets 1- α 0 existing funding α 0 ST funding maturing at t=1

15 Timing Time t=0t=1t=2t=3 Assets 1- α 0 existing funding α 0 ST funding maturing at t=1 We will consider the choice of refinancing at t=1

16 Timing Time t=0t=1t=2t=3 Assets 1- α 0 existing funding α 0 ST funding maturing at t=1 Choice between Roll-over of ST loans LT loan (2 periods)

17 The market for short term funds at t=1 Denote 1+r 1 the risk free, 1 period market rate Lenders are willing to lend only if expected return equals the risk free rate. With probability γ, financial crisis – repayment less likely probability 1- γα 1 The interest rate on short-term loans then is: (recall that all banks are identical) Liquidity risk premium

18 The market for long term funds at t=1 Denote the risk free interest rate on long-term (2-period) loans 1+r 12 (discounted to one period) Standard assumption: 1+r 12 >1+r 1 Simplifying assumption: we consider a situation in which γ is so high that the long-term interbank market breaks down With high γ (and in the absence of central bank liquidity provision, banks have no choice but refinance short-term the entire amount α 0) –Liquidity risk premium very high –Maturity mismatch cannot be reduced

19 The central bank Assume the central bank offers liquidity to banks at maturities of 1 or 2 periods in variable rate tenders with minimum bid rate Reserve requirements normalized to 0. Minimum interest rates are the risk-free rates –1+r 1 for one period –(1+r 12 ) 2 for two periods Central bank restricts liquidity supply (as in period August 2007 – September 2008)

20 The central bank: 1 period operation Variable rate tender: if banks have a high willingness to pay, they may bid up the marginal rate to the market rate (unless the demanded quantity is smaller than the offered volume) Rate in one-period operation is given by market rate (willingness-to-pay = market rate; Nash equilibrium):

21 The central bank: 2 period operations Rate in two-period operation has no market equivalent Compare instead to one-period rate, but note: LT refinancing with the central bank reduces share of ST funding and thus reduces liquidity risk premium! Denote – α 1 = share of total ST funding; – δ ≡ α 0 – α 1 = share of LT funding with the central bank Interest rate on the LT loan from the central bank is choice

22 ST and LT refinancing costs γ =0.3; r 1 =0; r 12 =0.2; α 0 =0.2

23 ST and LT refinancing costs γ =0.3; r 1 =0; r 12 =0.2; α 10 =0.2 α changes the proportion of ST funding, and the rate on ST funding

24 Total refinancing cost Refinancing costs are minimized at α* (interior solution)

25 Results Proposition 1: Under the above assumptions (market breakdown for LT funds, CB liquidity provision), where α * denotes banks’ optimal funding strategy, we have 0 < α 1 * < α and δ *= α 0 – α 1 * Comparative statics: –A higher probability of a crisis reduces α 1 * (i.e. less ST refinancing is chosen) –A flatter yield curve (r 12 -r 1 ) reduces α 1 * –Banks with low share of ex-ante LT funding (low 1- α 0 ) demand more CB funding

26 3a.Liquidity regulation (Basel III) Aim: To promote the resilience of banks’ liquidity risk profiles Liquidity Coverage Ratio: banks need an adequate level of unencumbered, high-quality liquid assets to meet net cash outflows under a well-defined 1-month stress scenario Net Stable Funding Ratio (NSFR): minimum amount of funding that is expected to be stable under conditions of extended stress (long term measure) Question addressed here: does the NSFR have implications for the demand for central bank funds?

27 Liquidity regulation Consider the NSFR: aims at reducing maturity mismatch, and demands that liabilities have somewhat similar maturity profile as assets In the model, this is equivalent to demanding an upper limit on α. Given the assumption that there is no LT market if crisis is highly likely, a binding regulation will lead to increased demand for LT financing from central bank.

28 4.Empirical analysis – questions Main question: Is there a relationship between maturity mismatch of a bank and its reliance on central bank refinancing, its demand for long-term central bank refinancing? Problem: No data on maturity mismatch for majority of banks. Therefore, we instead ask two questions: –Is there a relationship between maturity mismatch and bank risk? –Is there a relationship between bank risk and demand behaviour in Eurosystem refinancing operations? We are not aware of any recent (empirical) literature on maturity transformation (i.e. mismatch) of banks (Niehans and Hewson 1976, Eurodollar market)

29 Data and methodology Relationship between maturity mismatch and bank risk: –Panel regression, explaining bank risk with maturity mismatch Dependent variable: Average CDS spreads of these banks for each year Explanatory variable: Bank level data on maturity mismatch from annual reports and regulatory filings for 20 Euribor panel banks –Period: 3 years ( ), 60 observations Control variable (dummy, from Factiva), if bank experienced stress event in the period (Closure, nationalisation, forced capitalisation or injection of government funds, forced merger, recapitalisation)

30 Maturity mismatch Maturity (in days)MeanMaxMin Assets Liabilities Mean Mismatch (in days)

31 Data and methodology Relationship between bank risk and demand behaviour in Eurosystem refinancing operations: –Descriptive statistics, conditional on bank type (stressed, non- stressed) Bidding data at bank level for 354 most active banks in Eurosystem refinancing operations –Period: 01/2007 – 10/2008, observations

32 Results: maturity mismatch A bigger maturity mismatch is associated with higher credit risk –increase by one day increases CDS spreads by 0.05 Relationship continues to hold –if control for severe stress event is added to the regression –if maturity mismatch is scaled by the size of the respective banking book

33 Empirical analysis – background slides

34 Empirical analysis – background slides

35 Empirical analysis – results Non-stressed banks –Before crisis: Majority does not participate at all, mainstay (for those who participate) is MRO, very little reliance on LTRO –During crisis: Participation increases, especially in LTROs (but still significantly lower than stressed banks pre-crisis LTRO reliance) Stressed banks (i.e. banks that experienced at least one stress event in the sample period, 64 out of 354 are stressed) –Non participation drops (slightly, from 35%) –Heavy reliance on LTRO refinancing (already before crisis high LTRO reliance!) –Are significantly more likely to obtain funding simultaneously in MROs and LTROs than non-stressed banks

36 Empirical analysis – results

37 Empirical analysis – further work Related to bank risk – maturity mismatch analysis Control for bank capital levels and, ideally, for business model Expand sample Related to refinancing demand – bank risk analysis We have in total 7 different stress events, check how additional categories change results Introduce control for mortgage banks (or banks with large mortgage book) Expand “non-crisis” sample to period before 2007

38 Conclusion Paper studied the causes of increased demand for long-term central bank funding during the crisis Theoretical model finds: –Banks with a high maturity mismatch of assets and liabilities have highest willingness to pay in long-term CB auctions (because they aim at reducing the mismatch) –This effect is stronger, the more severe the crisis Empirical analysis finds: –There is a relationship between a measure of maturity mismatch in the banking book and bank risk –Banks under stress display a significantly different demand behaviour in Eurosystem operations than non-stressed banks

39 Thank you!

40 Empirical analysis – background slides Stress events Closure by supervisory authority Nationalisation Forced recapitalisation or injection of government funds Forced merger Recapitalisation Write-downs (>10% of capital) Profit warning