Do UK Banks Need More Capital?

Yes.  The Bank of England’s November 2012 Financial Stability Report has made the case for UK banks to shore up their levels of capital, perhaps to the tune of up to £20-50bn according to the FT.  Three arguments seem to have made: (i) banks may have to pay fines because of “misbehaviour”;  (ii) provisions for expected losses need to be made and (iii) risk weights may not be appropriate, in the sense that the weights applied may under predict risk.  Rather predictably commercial banks have complained about the new requirements arguing that they want more certainty about capital targets.  I am not quite sure that financial institutions, whose basic role is to price payoffs in uncertain future states of nature and allow people to write contracts for smoothing consumption and investment decisions over those uncertain futures, should be calling for certainty otherwise their very rationale seems to me to disappear in a puff of full information.

But more importantly, in a recent talk, I drew upon a chart published in the June 2012 Financial Stability Report (see below, p 6), that showed a pleasing movements towards some reduction in funding costs for more well capitalised banks.  That the market might now be thought to be punishing more risky banks – measured by their level of capital – means that market scrutiny of bank balance sheets may be starting to re-enforce plans for macro-prudential instruments.   So rather than an unwanted deadweight loss, or simple compliance with regulatory demands, there may be direct market benefit for financial institutions that move to more sensible levels of capital.     

One clear reason why the risk held by bank might be under-reported is that under European convention, sovereign bonds are given a zero risk weight in any calculation of risk-weighted assets.  This means that commercial banks do not have to hold any capital against these assets but which nevertheless, in reality, do carry significant risk.   This means that there is a fundamental shortfall in capital held in proportion both to the quantity and actual risk of sovereign debt. 

In fact, I examined the capital shortfall of the banking system in two ways.  Firstly, using the Eurozone Stress tests of late 2011 (Source: EBA, Eurostat, European Commission and Reuters Breaking Views), I examined the losses of all EMU and non-EMU banks in the EU from a 50% haircut (debt forgiveness, essentially) in Greek and also all Portuguese, Italian, Irish, Greek and Spanish Debt under scenarios for a 7% or 10% capital ratio target.  The capital shortfall in the case of only a 50% Greek haircut and a 10% capital target was some Euro348bn, for the UK alone this was a shortfall of Euro72bn.   Obviously some of the required adjustments may have already been made in the last year but such a calculation may not deal with further losses induced in the system, as banks may incur losses to other parties under a generalised haircut.  (These results are reported in The Euro in Danger.)  Secondly, and more recently, I then looked at the loss in terms of GDP from a 75% haircut on Greek debt and 30% on Ireland, Italy, Portugal and Spain.  With the same 10% capital target, we get a shortfall of Euro75bn in the UK, which rises to Euro221bn if the capital target is 15%.  Now while I think it is unlikely that increasing bank capital to extraordinarily high levels will be necessary or sufficient and much work remains to work out what of the optimal amount for each bank and in the system as a whole, this simple calculation seems to imply that the risk of continuing problems in the Euro Area would seem sufficient to justify the extra call for capital of this magnitude. 

Fiscal Multiplier and Bank Dividers

Fiscal multipliers are pretty hard to estimate as they tend not to be particularly stable.  Which is another way of saying that the impact on output of a given change in fiscal policy – which we can define as the planned path of government expenditures and tax receipts over some appropriate planning horizon - depends on a very large number of factors for which it is nearly impossible to condition.   A non-exhaustive list for fiscal policy might include the extent to which the fiscal expansion is expected, credible, temporary or financed by changes in spending or taxes, as well as the debt instruments issued.  The estimated response of the economy will depend how firms, households and banks respond to the changes in fiscal policy but also may be complicated by the response of these same agents to the same shock to which fiscal policy is responding.  The responses of other policy makers such as central bank responses to any fiscal policy and that of other fiscal authorities, particularly in a monetary union, will further complicate any attempts to estimate a clean partial. 

I illustrated some of these issues in a talk to St Catherine’s Political Economy seminar last month.  One early piece of evidence was simply a Table of recent estimates of the multiplier for the UK.  The estimates from these sources give a wide variety depending also on the way in which the fiscal stance is changed.  The outlier in these estimate are those recently derived by the IMF in the October 2012 WEO (Box 1.1), who used the negative residual (where actual output turns out to be below the forecast) of output forecasts from 2010-11 to find some correlation between the timing of fiscal consolidation and the continuing underperformance of the economy.   It turns out though that although the IMF paper tries to apply many controls, they do control for the impact of household and bank deleveraging.

Actually, all kinds of other factors may have led to such an undershoot.  Let me illustrate one.  In this model, “Reserves, liquidity and money:an assessment of balance sheet policies”, in which firms produce monopolistically competitive goods with sticky output prices, optimising households who are credit-constrained by the extent to which banks lend to them in return for collateral in an economy which is driven over the long run by productivity.  This economy can be stabilised by monetary policy changing interest rates or operating open market operations but fiscal policy also has a role by altering the supply of bonds held by the private sector, which act as collateral.  In this model we can alter the size of the government debt by increasing expenditure relative to taxes and trace the impact on output under three scenarios:  (i) a fiscal expansion when policy rates also rise and when banks increase their lending; (ii) a fiscal expansion when policy rates do not rise and the banks increase their lending and (iii) a fiscal expansion when policy rates do not rise and when banks start to delever and contract their level of activity as part of a consolidation. 

The set of impulse responses above are illustrative but show (look at the top left impulse response) that under scenario i) we see a multiplier of around 0.2, under (ii) it is around 0.5 and under (iii) it is around 0.1.  The “fiscal multiplier” in a monetary economy, where banks set the level of broad money depends not only on the policy response.  But also the impact on other interest rates – the external finance premium or bond rates.  And most importantly of all, how the banking sector responds to the state of economy that has led to the need for a fiscal expansion.  This simple calibration shows that cautious banks, or deleveraging banks, who increase the level of monitoring work they undertake and hence hold back on creating new loans can per se offset the impact of any fiscal expansion.   The key therefore, as we have known for some time, is to fix the banking system.  The problem is that the fix also requires deleveraging and consolidation.

Prediction markets and Obama Vs Romney

Four years, I posted a blog on the Iowa Electronic MarketsUS Presidential Election Market.  (For more explanation of the market go to this page.)  For much of time from his nomination in August 2008, it looked very clear from the winner-take-all market that President Obama was going to beat Senator McCain.  Recall that from early September 2008, when the winner take-all market was trading at nearly 50:50, President Obama’s star started an ascendency of such strength that by the date of the 2008 election on 4^th November, the market was trading 90:10 in favour of Obama.   This means that it cost 90 cents to place a bet that the Democrats would poll the majority of votes cast, which would return $1 if this transpired and $0 if not.  To coin a phrase: this time is different (to some extent!). 

In 2012, a similar divergence in the winner-take-all (WTA, the upper chart) market started this summer and continued until late-September when by close of trade on 27 September, WTA had 82:18 for President Obama.  But rather than continuing to cascade towards Obama the prediction market went back to 58:42 by 24^th October: the US public seemed to waver and Mitt Romney built up considerable momentum.  In the last week of October, much was therefore made of an election that was going to be too close to call - which seems to be even more so the case if you look at the Vote Share market (VS, the lower chart).  

But since Hurricane (Cyclone) Sandy the prices in the WTA market have gone back to favour Obama and on Sunday close 4^th November and we stood at 72:28 in favour of the incumbent.  It seems that Iowa prediction markets are calling it for the President Obama, or at least that he will get the majority of the popular vote.  Unfortunately prediction markets have not taken off in the way that I had hoped a few years ago and the Iowa markets are still far from deep and liquid with a maximum bet of $500.  But the ability for market participants to trade assets in a manner to capture the probability of different states of the future remains of great use.  At the very least to someone over here in the UK, who cannot follow every turn in the US news - and yet from this market, I get a clean probability on a daily basis.  At the least we should probably ignore opinion polls and place a bit more weight on the implied probabilities from markets in which people place real money on their views.  A surprise may, of course, await us but at least we do not have very long to wait.

Hedges, Credit Default Swaps and the Euro Area - would you credit it?

About this time very year, as the clocks go back, I ask my students: How do I hedge risk?  Eventually we stumble on the answer which involves buying an asset whose prices changes, or returns in financial language, are negatively correlated with those of my current portfolio.  Thus I give up a little of the returns from my current portfolio and add an asset whose returns will be high (low) when those of my current portfolio will be low (high).  And so I ensure, through the purchase (giving up of some of returns) of a hedge, that my returns or income stream is better stabilised.   The hedge will not make you rich and “will not make you look five pounds thinner” but will be preferred by anyone who wishes to stabilise returns from their portfolio over a larger range of possible events.  The price that people are willing to pay for hedges can give us very useful information on the market’s perception of risk.

Let us, for example, consider credit default swaps on sovereign debt.  These instruments are simply instrument designed to make a risky government bond into a risk-free government bond (you can buy them on corporates but let's concentrate on govvies).  The holder of a risky bond buys a hedge from someone who wishes to sell insurance.  The seller of the credit default swap (CDS) collects the premia from the owner of the risky bond and insures against default by promising to pay the par value of the bond in the event of a default, or “credit event” by the original debt issuer.  In the event of no default, the seller of the CDS simply collects premia and the owner of the bond has reduces his stream of payoffs by the amount of the insurance paid.  The returns from the risky bonds are thus shared between the owner and the seller of the CDS and in principle the combination of holding a risky bond plus a CDS “insurance” contract recovers a risk-free bond for the bond holder.  The seller of the CDS is just collecting insurance premia, having calculated that the expected value of these premia are no less than the cost of par value of the bonds insured times the probability of default. 

The buyer of the CDS pays a percentage of their notional principal and this is called the CDS spread and given reasonably ordered markets are indicative of the riskiness of a given sovereign’s (or corporate's) debt.  There are a number of caveats attached to reading the spreads as indicating risk directly: (i) liquidity in CDS markets, there are over the counter may not always be high, which means spreads may reflect time-varying liquidity premia; (ii) insurance premia may include fixed cost, which drives the spread up; (iii) they reflect risk aversion rather that credit risk, per se, and, relatedly (iv) may reflect a more general contagion rather than an individual country or sovereign risk.  And so we have to be very careful in interpreting the level of spreads and their changes.  

But for the sake of telling a story, let us now look at this CDS spreads for 10 year protection for a group of advanced economies in and outside the Euro Area.  The actual spreads suggest that Spain and Italy lie outside the norm, with spreads at around 300bp.  But if we simply re-index the series for January 2010, which is rather arbitrary admittedly, but we might use a start date of sorts for the Euro-crisis – it is the date that the EU cast doubts on theGreek deficit numbers – we can observe a bifurcation of sorts between the change in the spread between 2010 and today for the EMU countries and non-EMU countries.  The latter have been relatively flat, implying the financial market price have not priced in especially higher rates of Soveriegn risk, even though sustained economic growth has not returned. But for the four Euro Area economies Italy, France, Germany and Spain, CDS spreads seemed to have, at least, tripled.  Whether this is contagion or liquidity or a true measure of heightened Euro Area risk, I leave for another time.  But the price of a hedge does seem to say something clear cut about the continuing problems of the Euro Area and that much work remains to be done.

Did policymakers learn to blow bubbles in 1987?

We have not yet, as a profession, teased out the contribution to the business cycle from monetary policy actions.  This is, in part, because there is not only considerable dispute on how to measure monetary actions but also we know that any results will be heavily dependent on the particular model that is chosen.  There is another reason.  We tend to think of policy as acting to stabilise the economy from shocks, so that agents will plan over the longer run in a manner consistent with the policymakers key objectives.  But what if policy gets it wrong from time to time?  Then it has the ability to increase as well as reduce the volatility of the economic cycle.  And so working out the contribution to an event from something that both may have caused it and responded to it, turns out to be quite hard.

On Friday, at both my lectures, I reminded my students of the events of 19^th October 1987, so-called Black Monday.  Or rather given their youth, offered the historical account.  Although this was a global event, I concentrated on the FT100.   The index of leading companies, see Figure, was based to 1000 in January 1984.  So we can see that by New Year’s Day on 1987, there had been a 68% increase in three years, implying an annual return of just under 19% and the index stood at 1679.  By 16^th July, the index had gained another 764 points to reach 2443, giving a further 46% return in just over half a year.  The correction to this boom was rapid.  There was an 11% fall in the index on Monday, followed by further falls on Tuesday, Thursday and Friday.  So by the end of that week, the index was at 1684 and nearly 27% down on the previous Friday close.  There are a number of contemporary accounts of the proximate causes of this large correction: margin calls, automated stop-loss trades, trading desks-cum-ghost towns as a storm prevented people manning the desks but all seem to suggest to me simply that any downward correction may have been somewhat amplified (See Carlson, 2007, for a nice summary of the the US view).

 

The question facing policymakers was whether this fall in equity prices was a bubble bursting or a market re-valuation of firms’ profitability.  The former implies some form of correction back to fundamentals but the latter change in the underlying profitability of the large firms and by association the economy.  Either way, of course, the possibility of panic remained so perhaps something had to be seen to be done.  Indeed there was a considerable attempt to co-ordinate the responses across central banks throughout the world.  And so Bank Rate was cut from 9 7/8 by 150Bp in three steps, starting on Friday 23^rd, to fall to 8 3/8 by early December.  Equity prices reached their lowest point after this crash on 9^th November at 1565 and some sort of recovery in prices commenced.  Certainly there was no Great Depression as some doomsters (I should look up who they were) were arguing and the business cycle expansion continued until the last quarter of 1990.  With the benefit of considerable hindsight, it would appear that Black Monday was simply a correction and the policy response initially helped adjustment to the new path for equity prices.  In practice, subsequently, house prices were stoked up to a great extent, households became rather indebted and the economy subsequently could not bear the real rates required from continued membership of the ERM but I can tell that story another time.

And so when we turn to list the reasons for the financial crash of 2007/8, we do, I think, tend to overlook the role of excessively accommodative monetary policy in stoking the imbalances that the crisis finally revealed.  Equity market turbulence in the early years of this century led to super-accommodative monetary policy, alongside levels of transparency in policymaking that were designed to reduce uncertainty about the level and path of policy rates.  Casually, at least these policy choices seemed to have played a role in prolonging the business cycle and also supporting asset prices rather like the situation in the late 1980s.  A representative policy maker in their late forties or early fifties in 2003, would have been in his or her mid-to-late 30s in 1987 and I wonder to what extent the experience of 1987 was instructive.  I doubt we shall be able to point the finger for the causes of this crisis at policymakers who had learnt formative lessons as to how to respond to a crises with the Big One in 1987 but I wonder if they did grow up to become bubble blowers?