The Epsilon Theory post focusses on the Covid 19 fallout currently playing out but is also worth reading for the broader challenges it offers anyone trying to use models and probabilities to manage real world outcomes …
This post sets out a case for a bank choosing to incorporate a discretionary Cyclical Buffer (CyB) into its Internal Capital Adequacy Assessment Process (ICAAP). The size of the buffer is a risk appetite choice each individual bank must make. The example I have used to illustrate the idea is calibrated to absorb the expected impact of an economic downturn that is severe but not necessarily a financial crisis style event. My objective is to illustrate the ways in which incorporating a Cyclical Buffer in the target capital structure offers:
an intuitive connection between a bank’s aggregate risk appetite and its target capital structure;
a means of more clearly defining the point where losses transition from expected to unexpected; and
a mechanism that reduces both the pro cyclicality of a risk sensitive capital regime and the tendency for the transition to unexpected losses to trigger a loss of confidence in the bank.
The value of improved clarity, coherence and consistency in the risk appetite settings is I think reasonably self evident. The need for greater clarity in the distinction between expected and unexpected loss perhaps less so. The value of this Cyclical Buffer proposal ultimately depends on its capacity to enhance the resilience of the capital adequacy regime in the face of economic downturns without compromising its risk sensitivity.
There are no absolutes when we deal with what happens under stress but I believe a Cyclical Buffer such as is outlined in this post also has the potential to help mitigate the risk of loss of confidence in the bank when losses are no longer part of what stakeholders expect but have moved into the domain of uncertainty. I am not suggesting that this would solve the problem of financial crisis. I am suggesting that it is a relatively simple enhancement to a bank’s ICAAP that has the potential to make banks more resilient (and transparent) with no obvious downsides.
In Capital 101, we learn that capital is meant to cover “unexpected loss” and that there is a neat division between expected and unexpected loss. The extract below from an early BCBS publication sets out the standard explanation …
Expected and unexpected credit loss
The BCBS publication from which this image is sourced explained that
“While it is never possible to know in advance the losses a bank will suffer in a particular year, a bank can forecast the average level of credit losses it can reasonably expect to experience. These losses are referred to as Expected Losses (EL) ….”
One of the functions of bank capital is to provide a buffer to protect a bank’s debt holders against peak losses that exceed expected levels… Losses above expected levels are usually referred to as Unexpected Losses (UL) – institutions know they will occur now and then, but they cannot know in advance their timing or severity….”
“An Explanatory Note on the Basel II IRB Risk Weight Functions” BCBS July 2005
There was a time when the Internal Ratings Based approach, combining some elegant theory and relatively simple math, seemed to have all the answers
A simple intuitive division between expected and unexpected loss
Allowing expected loss to be quantified and directly covered by risk margins in pricing while the required return on unexpected loss could be assigned to the cost of equity
A precise relationship between expected and unexpected loss, defined by the statistical parameters of the assumed loss distribution
The capacity to “control” the risk of unexpected loss by applying seemingly unquestionably strong confidence levels (i.e. typically 1:1000 years plus) to the measurement of target capital requirements
It even seemed to offer a means of neatly calibrating the capital requirement to the probability of default of your target debt rating (e.g. a AA senior debt rating with a 5bp probability of default = a 99.95% confidence level; QED)
If only it was that simple … but expected loss is still a good place to start
The problem (from a capital adequacy perspective) with both IFRS9 and REL is that the “expected” value still depends on the state of the credit cycle at the time we are taking its measure. REL incorporates a Downturn measure of Loss Given Default (DLGD) but the other inputs (Probability of Default and Exposure at Default) are average values taken across a cycle, not the values we expect to experience at the peak of the cycle downturn.
We typically don’t know exactly when the credit cycle will turn down, or by how much and how long, but we can reasonably expect that it will turn down at some time in the future. Notwithstanding the “Great Moderation” thesis that gained currency prior to the GFC, the long run of history suggests that it is dangerous to bet against the probability of a severe downturn occurring once every 15 to 25 years. Incorporating a measure into the Internal Capital Adequacy Process (ICAAP) that captures this aspect of expected loss provides a useful reference point and a potential trigger for reviewing why the capital decline has exceeded expectations.
One of the problems with advanced model based approaches like IRB is that banks experience large value losses much more frequently than the models suggest they should. As a consequence, the seemingly high margins of safety implied by 1:1000 year plus confidence levels in the modelling do not appear to live up to their promise.
A better way of dealing with uncertainty
One of the core principles underpinning this proposal is that the boundary between risk (which can be measured with reasonable accuracy) and uncertainty (which can not be measured with any degree of precision) probably lies around the 1:25 year confidence level (what we usually label a “severe recession). I recognise that reasonable people might adopt a more conservative stance arguing that the zone of validity of credit risk models caps out at 1:15 or 1:20 confidence levels but I am reasonably confident that 1:25 defines the upper boundary of where credit risk models tend to find their limits. Each bank can makes its own call on this aspect of risk calibration.
Inside this zone of validity, credit risk models coupled with stress testing and sensitivity analysis can be applied to generate a reasonably useful estimate of expected losses and capital impacts. There is of course no guarantee that the impacts will not exceed the estimate, that is why we have capital. The estimate does however define the rough limits of what we can claim to “know” about our risk profile.
The “expected versus unexpected” distinction is all a bit abstract – why does it matter?
Downturn loss is part of the risk reward equation of banking and manageable, especially if the cost of expected downturn losses has already been built into credit risk spreads. Managing the risk is easier however if a bank’s risk appetite statement has a clear sense of:
exactly what kind of expected downturn loss is consistent with the specific types of credit risk exposure the risk appetite otherwise allows (i.e. not just the current exposure but also any higher level of exposure that is consistent with credit risk appetite) and
the impact this would be expected to have on capital adequacy.
This type of analysis is done under the general heading of stress testing for both credit risk and capital adequacy but I have not often seen evidence that banks are translating the analysis and insight into a specific buffer assigned the task of absorbing expected downturn losses and the associated negative impact on capital adequacy. The Cyclical Buffer I have outlined in this post offers a means of more closely integrating the credit risk management framework and the Internal Capital Adequacy Assessment Process (ICAAP).
What gets you into trouble …
“It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so”
Commonly, possibly mistakenly, attributed to Mark Twain
This saying captures an important truth about the financial system. Some degree of volatility is part and parcel of the system but one of the key ingredients in a financial crisis or panic is when participants in the system are suddenly forced to change their view of what is safe and what is not.
This is one of the reasons why I believe that a more transparent framework for tracking the transition from expected to truly unexpected outcomes can add to the resilience of the financial system. Capital declines that have been pre-positioned in the eyes of key stakeholders as part and parcel of the bank risk reward equation are less likely to be a cause for concern or trigger for panic.
The equity and debt markets will still revise their valuations in response but the debt markets will have less reason to question the fundamental soundness of the bank if the capital decline lies within the pre-positioned operating parameters defined by the target cyclical buffer. This will be especially so to the extent that the Capital Conservation Buffer provides substantial layers of additional buffer to absorb the uncertainty and buy time to respond to it.
Calibrating the size of the Cyclical Buffer
Incorporating a Cyclical Buffer does not necessarily mean that a bank needs to hold more capital. It is likely to be sufficient to simply partition a set amount of capital that bank management believes will absorb the expected impact of a cyclical downturn. The remaining buffer capital over minimum requirements exists to absorb the uncertainty and ensure that confidence sensitive liabilities are well insulated from the impacts of that uncertainty.
But first we have to define what we mean by “THE CYCLE”. This is a term frequently employed in the discussion of bank capital requirements but open to a wide range of interpretation.
A useful start to calibrating the size of this cyclical buffer is to distinguish:
An economic or business cycle; which seems to be associated with moderate severity, short duration downturns occurring once every 7 to 10 years, and
Every bank makes its own decision on risk appetite but, given these two choices, mine would calibrated to, and hence resilient against, the less frequent but more severe and longer duration downturns associated with the financial cycle.
There is of course another layer of severity associated with a financial crisis. This poses an interesting challenge because it begs the question whether a financial crisis is the result of some extreme external shock or due to failures of risk management that allowed an endogenous build up of risk in the banking system. This kind of loss is I believe the domain of the Capital Conservation Buffer (CCB).
There is no question that banks must be resilient in the face of a financial crisis but my view is that this is a not something that should be considered an expected cost of banking.
Incorporating a cyclical buffer into the capital structure for an Australian D-SIB
Figure 2 below sets out an example of how this might work for an Australian D-SIB that has adopted APRA’s 10.5% CET1 “Unquestionably Strong”: benchmark as the basis of its target capital structure. These banks have a substantial layer of CET1 capital that is nominally surplus to the formal prudential requirements but in practice is not if the bank is to be considered “unquestionably strong” as defined by APRA. The capacity to weather a cyclical downturn might be implicit in the “Unquestionably Strong” benchmark but it is not transparent. In particular, it is not obvious how much CET1 can decline under a cyclical downturn while a bank is still deemed to be “Unquestionably Strong”.
The proposed Cyclical Buffer sits on top of the Capital Conservation Buffer and would be calibrated to absorb the increase in losses, and associated drawdowns on capital, expected to be experienced in the event of severe economic downturn. Exactly how severe is to some extent a question of risk appetite, unless of course regulators mandate a capital target that delivers a higher level of soundness than the bank would have chosen of its own volition.
In the example laid out in Figure 2, I have drawn the limit of risk appetite at the threshold of the Capital Conservation Buffer. This would be an 8% CET1 ratio for an Australian D-SIB but there is no fundamental reason for drawing the lone on risk appetite at this threshold. Each bank has the choice of tolerating some level of incursion into the CCB (hence the dotted line extension of risk appetite). What matters is to have a clear line beyond which higher losses and lower capital ratios indicate that something truly unexpected is driving the outcomes being observed.
What about the prudential Counter-Cyclical Capital Buffer?
I have deliberately avoided using the term”counter” cyclical in this proposal to distinguish this bank controlled Cyclical Buffer (CyB) from its prudential counterpart, the “Counter Cyclical Buffer” (CCyB), introduced under Basel III. My proposal is similar in concept to the variations on the CCyB being developed by the Bank of England and the Canadian OFSI. The RBNZ is also considering something similar in its review of “What counts as capital?” where it has proposed that the CCyB should have a positive value (indicatively set at 1.5%) at all times except following a financial crisis (see para 105 -112 of the Review Paper for more detail).
My proposal is also differentiated from its prudential counter part by the way in which the calibration of the size of the bank Cyclical Buffer offers a way for credit risk appetite to be more formally integrated with the Internal Capital Adequacy Process (ICAAP) that sets the overall target capital structure.
Incorporating a Cyclical Buffer into the target capital structure offers a means of more closely integrating the risk exposure and capital adequacy elements of a bank’s risk appetite
A breach of the Cyclical Buffer creates a natural trigger point for reviewing whether the unexpected outcomes was due to an unexpectedly large external shock or was the result of credit exposure being riskier than expected or some combination of the two
The role of the Capital Conservation Buffer in absorbing the uncertainty associated with risk appetite settings is much clearer if management of cyclical expected loss is assigned to the Cyclical Buffer
One of the traditional arguments for higher common equity requirements is that it increases the shareholders’ “skin in the game” and thereby creates an incentive to be more diligent and conservative in managing risk.
This principle is true up to a point but I believe more common equity mostly generates this desirable risk management incentive when the extra skin in the game (aka capital) is addressing a problem of too little capital. It is much less obvious that more capital promotes more conservative risk appetite for a bank that already has a strong capital position.
In the “too little” capital scenarios, shareholders confronted with a material risk of failure, but limited downside (because they have only a small amount of capital invested), have an incentive to take large risks with uncertain payoffs. That is clearly undesirable but it is not a fair description of the risk reward payoff confronting bank shareholders who have already committed substantial increased common equity in response to the new benchmarks of what it takes to be deemed a strong bank.
Abstract: The paper evaluates the impact of macroprudential capital regulation on bank capital, risk taking behaviour, and solvency. The identification relies on the policy change in bank-level capital requirements across systemically important banks in Europe. A one percentage point hike in capital requirements leads to an average CET1 capital increase of 13 percent and no evidence of reduction in assets. The increase in capital comes at a cost. The paper documents robust evidence on the existence of substitution effects toward riskier assets. The risk taking behavior is predominantly driven by large and less profitable banks: large wholesale funded banks show less risk taking, and large banks relying on internal ratings based approach successfully disguise their risk taking. In terms of overall impact on solvency, the higher risk taking crowds-out the positive effect of increased capital.
I have only skimmed the paper thus far and have reservations regarding how they measure increased risk. As I understand it, the increased riskiness the analysis measures is based on increases in average risk weights. It was not clear how the analysis distinguished changes in portfolio riskiness from changes in the risk weight measure. That said, the overall conclusions seem intuitively right.
Claudio Borio at the BIS wrote an interesting paper exploring the “financial cycle”. This post seeks to summarise the key points of the paper and draw out some implications for bank stress testing (the original paper can be found here). The paper was published in December 2012, so its discussion of the implications for macroeconomic modelling may be dated but I believe it continues to have some useful insights for the challenges banks face in dealing with adverse economic conditions and the boundary between risk and uncertainty.
Key observations Borio makes regarding the Financial Cycle
The concept of a “business cycle”, in the sense of there being a regular occurrence of peaks and troughs in business activity, is widely known but the concept of a “financial cycle” is a distinct variation on this theme that is possibly less well understood. Borio states that there is no consensus definition but he uses the term to
“denote self-reinforcing interactions between perceptions of value and risk, attitudes towards risk and financing constraints, which translate into booms followed by busts. These interactions can amplify economic fluctuations and possibly lead to serious financial distress and economic disruption”.
This definition is closely related to the concept of “procyclicality” in the financial system and should not be confused with a generic description of cycles in economic activity and asset prices. Borio does not use these words but I have seen the term “balance sheet recession” employed to describe much the same phenomenon as Borio’s financial cycle.
Borio identifies five features that describe the Financial Cycle
It is best captured by the joint behaviour of credit and property prices – these variables tend to closely co-vary, especially at low frequencies, reflecting the importance of credit in the financing of construction and the purchase of property.
It is much longer, and has a much larger amplitude, than the traditional business cycle – the business cycle involves frequencies from 1 to 8 years whereas the average length of the financial cycle is longer; Borio cites a cycle length of 16 years in a study of seven industrialised economies and I have seen other studies indicating a longer cycle (with more severe impacts).
It is closely associated with systemic banking crises which tend to occur close to its peak.
It permits the identification of the risks of future financial crises in real time and with a good lead – Borio states that the most promising leading indicators of financial crises are based on simultaneous positive deviations of the ratio of private sector credit-to-GDP and asset prices, especially property prices, from historical norms.
And it is highly dependent of the financial, monetary and real-economy policy regimes in place (e.g. financial liberalisation under Basel II, monetary policy focussed primarily on inflation targeting and globalisation in the real economy).
Macro economic modelling
Borio also argues that the conventional models used to analyse the economy are deficient because they do not capture the dynamics of the financial cycle. These extracts capture the main points of his critique:
“The notion… of financial booms followed by busts, actually predates the much more common and influential one of the business cycle …. But for most of the postwar period it fell out of favour. It featured, more or less prominently, only in the accounts of economists outside the mainstream (eg, Minsky (1982) and Kindleberger (2000)). Indeed, financial factors in general progressively disappeared from macroeconomists’ radar screen. Finance came to be seen effectively as a veil – a factor that, as a first approximation, could be ignored when seeking to understand business fluctuations … And when included at all, it would at most enhance the persistence of the impact of economic shocks that buffet the economy, delaying slightly its natural return to the steady state …”
“Economists are now trying hard to incorporate financial factors into standard macroeconomic models. However, the prevailing, in fact almost exclusive, strategy is a conservative one. It is to graft additional so-called financial “frictions” on otherwise fully well behaved equilibrium macroeconomic models, built on real-business-cycle foundations and augmented with nominal rigidities. The approach is firmly anchored in the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) paradigm.”
“The purpose of this essay is to summarise what we think we have learnt about the financial cycle over the last ten years or so in order to identify the most promising way forward…. The main thesis is that …it is simply not possible to understand business fluctuations and their policy challenges without understanding the financial cycle”
There is an interesting discussion of the public policy (i.e. prudential, fiscal, monetary) associated with recognising the role of the financial cycle but I will focus on what implications this may have for bank management in general and stress testing in particular.
Insights and questions we can derive from the paper
The observation that financial crises are based on simultaneous positive deviations of the ratio of private sector credit-to-GDP and asset prices, especially property prices, from historical norms covers much the same ground as the Basel Committee’s Countercyclical Capital Buffer (CCyB) and is something banks would already monitor as part of the ICAAP. The interesting question the paper poses for me is the extent to which stress testing (and ICAAP) should focus on a “financial cycle” style disruption as opposed to a business cycle event. Even more interesting is the question of whether the higher severity of the financial cycle is simply an exogenous random variable or an endogenous factor that can be attributed to excessive credit growth.
I think this matters because it has implications for how banks calibrate their overall risk appetite. The severity of the downturns employed in stress testing has in my experience gradually increased over successive iterations. My recollection is that this has partly been a response to prudential stress tests which were more severe in some respects than might have been determined internally. In the absence of any objective absolute measure of what was severe, it probably made sense to turn up the dial on severity in places to align as far as possible the internal benchmark scenarios with prudential benchmarks such as the “Common Scenario” APRA employs.
At the risk of a gross over simplification, I think that banks started the stress testing process looking at both moderate downturns (e.g. 7-10 year frequency and relatively short duration) and severe recessions (say a 25 year cycle though still relatively short duration downturn). Bank supervisors in contrast have tended to focus more on severe recession and financial cycle style severity scenarios with more extended durations. Banks’s have progressively shifted their attention to scenarios that are more closely aligned to the severe recession assumed by supervisors in part because moderate recessions tend to be fairly manageable from a capital management perspective.
Why does the distinction between the business cycle and the financial cycle matter?
Business cycle fluctuations (in stress testing terms a “moderate recession”) are arguably an inherent feature of the economy that occur largely independently of the business strategy and risk appetite choices that banks make. However, Borio’s analysis suggests that the decisions that banks make (in particular the rate of growth in credit relative to growth in GDP and the extent to which the extension of bank credit contributes to inflated asset values) do contribute to the risk (i.e. probability, severity and duration) of a severe financial cycle style recession.
Borio’s analysis also offers a way of thinking about the nature of the recovery from a recession. A moderate business cycle style recession is typically assumed to be short with a relatively quick recovery whereas financial cycle style recessions typically persist for some time. The more drawn out recovery from a financial cycle style recession can be explained by the need for borrowers to deleverage and repair their balance sheets as part of the process of addressing the structural imbalances that caused the downturn.
If the observations above are true, then they suggest a few things to consider:
should banks explore a more dynamic approach to risk appetite limits that incorporated the metrics identified by Borio (and also used in the calibration of the CCyB) so that the level of risk they are willing to take adjusts for where they believe they are in the state of the cycle (and which kind of cycle we are in)
how should banks think about these more severe financial cycle losses? Their measure of Expected Loss should clearly incorporate the losses expected from business cycle style moderate recessions occurring once every 7-10 years but it is less clear that the kinds of more severe and drawn out losses expected under a Severe Recession or Financial Cycle downturn should be part of Expected Loss.
A more dynamic approach to risk appetite get us into some interesting game theory puzzles because a decision by one bank to pull back on risk appetite potentially allows competitors to benefit by writing more business and potentially doubly benefiting to the extent that the decision to pull back makes it safer for competitors to write the business without fear of a severe recession (in technical economist speak we have a “collective action” problem). This was similar to the problem APRA faced when it decided to impose “speed limits” on certain types of lending in 2017. The Royal Commission was not especially sympathetic to the strategic bind banks face but I suspect that APRA understand the problem.
How do shareholders think about these business and financial cycle losses? Some investors will adopt a “risk on-risk off” approach in which they attempt to predict the downturn and trade in and out based on that view, other “buy and hold” investors (especially retail) may be unable or unwilling to adopt a trading approach.
The dependence of the financial cycle on the fiscal and monetary policy regimes in place and changes in the real-economy also has potential implications for how banks think about the risk of adverse scenarios playing out. Many of the factors that Borio argues have contributed to the financial cycle (i.e. financial liberalisation under Basel II, monetary policy focussed primarily on inflation targeting and globalisation in the real economy) are reversing (regulation of banks is much more restrictive, monetary policy appears to have recognised the limitations of a narrow inflation target focus and the pace of globalisation appears to be slowing in response to a growing concern that its benefits are not shared equitably). I am not sure exactly what these changes mean other than to recognise that they should in principle have some impact. At a minimum it seems that the pace of credit expansion might be slower in the coming decades than it has in the past 30 years.
All in all, I find myself regularly revisiting this paper, referring to it or employing the distinction between the business and financial cycle. I would recommend it to anyone interested in bank capital management.