Edmund Cannon Banking Crisis University of Verona Lecture 3

Plan for today 2 Review of Monday and Tuesday Finish material from Tuesday Opportunity for questions I shall discuss the formative assessment tomorrow (after I have marked it). Today’s Material: More about Risk Measuring risk: how do they do it (VaR)? Insuring risk: Credit Default Swaps Systemic risk and endogeneity; housing market REPO

How to measure risk 3 Regulators interested in downside risk (things going wrong). Variance (or standard deviation) does not measure precisely this. Most widely used measure is Variance-at-Risk Usually abbreviated VaR (VAR = Vector Auto Regression) VaR = how bad things are if worst 1% (or x% happens) ≈ 1% critical value of the probability distribution

Measuring risk – Value at Risk (VaR) 4

Normal or non-Normal 5 If returns are Normal (= Gaussian) then: The variance is a sufficient statistic for all measures of risk; Estimates of the variance have a chi-squared distribution so it is easy to model how risk depends upon estimation error. If returns are non-Normal then: The variance cannot tell us about the risk of certain situations; Estimates of the variance are unbiased but that is about all we can say; Any model assuming Normality will heavily under-estimate “extreme events”.

Non-Normal returns 6

Statistical issues with VaR 7 Statistical issues: Expected value and Variance relatively easy to estimate; Characteristics of “Tails” much harder to estimate. Intuitive explanation of statistical problem: By definition, very rare events are very rare; Therefore there are very little data. Possible solution: make strong assumptions about the probability distribution (eg Normal) Further problem: many estimates based on inadequate data (eg from last ten years: series is too short).

Difficulty of estimating VaR from data 8

Reducing risk with insurance: Credit Default Swaps 9 One way to reduce risk is to move risk off balance sheet – eg CDO. Alternatively a bank can hold a risky asset on the balance sheet but purchase insurance through a Credit Default Swap. The CDS insures against default. Insurance against price movements is insured through conventional future contracts (which I do not discuss). Compare CDS with conventional insurance.

Conventional Insurance (eg house insurance) 10

Characteristics of conventional insurance 11 Standardised products: Easy to have industry standards; Straightforward to regulate; Possibility of competition. Purchaser must have an “insurable interest”: Genuine insurance. Often purchased by individuals: consumer protection. Insurance companies are leveraged: capital regulation (Solvency I ~ Basel I). Adverse selection and moral hazard.

Credit Default Swaps 12 Pay monthly premium to provider (often a monoline). Receive payment if bond defaults. In problem cases: definition of default determined by ISDA. Differentiated products – no industry standard. Purchaser need not have an “insurable interest”: Traded OTC not on exchange – prices difficult to observe. Minimal regulation of reserve requirements: Market participants impose capital requirements. Who is the appropriate counter party for sovereign debt?

Credit Default Swaps 13

“Endogenous” Risk 14 Basic idea: Economic insitutions magnify good and bad shocks. Mechanism 1: Leverage Unexpectedly good results increase capital (equity) Banks lend more Creates a bubble Mechanism 2: Expectations / perceptions of risk Firms only use recent data to evaluate risk Selection bias Too optimistic in good times; too pessimistic in bad times.

Leverage and endogenous risk (Shin) 15 Leverage increases endogenous risk in all leveraged institutions, not just banks.

Endogenous risk – the crash 16 As asset prices fall (losses mount) leverage rises. Firms sell assets to reduce leverage. Distress selling is an externality to other banks’ balance sheets (especially with mark-to-market pricing).

House price bubbles 17 House prices are very variable. House prices rise  Fewer defaults  Mortgage banks make high profits and increase equity  Under-estimate default risk  Lend more money on easier terms  House prices rise further

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UK House Prices (Nationwide BS survey) Ratio of first-time buyer houses to earnings Source: 21

Ratio of house prices to average earnings (long run) Source: Nationwide, National Statistics, author’s calculations 22

The REPO market 23 A REPO is a short-term loan/deposit to a (shadow) bank. The size of the deposit is too large to attract deposit insurance. The bank gives collateral to the lender during the loan At the end of the loan, the bank repays the loan and gets the collateral back. The advantage of this type of loan is that the lender actually has the collateral during the loan period – so the loan is safe. The only risk to the lender is that the collateral itself may lose value or default.

Reducing risk through collateral: the REPO market 24

Haircuts in REPO 25 Because the collaterial may lose value, the lender lends less cash than the value of the collateral. The difference is called the “haircut” The word haircut is also used to describe any loss made by the lender. Example: The lender/depositor lends €98 of cash to the bank The bank gives an asset worth €100 to the lender/depositor One day later: The lender returns the asset to the bank The bank repays €100 cash

Haircuts and leverage 26 With a haircut of 1%, the bank gets €99 of cash in exchange for €100 of collateral.  The bank can create €100 of additional credit for only €1 of equity (the bank’s own stake). With a haircut of 10%, the bank gets €90 of cash in exchange for €100 of collateral.  The bank can create €100 of additional credit only by providing €10 of equity. So as the haircut rises, for a given amount of equity, the bank creates less credit.

Average haircut across nine types of asset used as collateral (Source: Gorton and Metrick, 2012) 27

Haircuts and pro-cyclicity 28 Perceptions of higher risk lead to higher haircuts. Less credit is created because banks’ equity is fixed in the short run. The bank must reduce its assets by selling them: but since everyone else is selling too, prices fall. The falls in price lead perceptions of risk to rise further and so haircuts continue to rise.