macroresilience

resilience, not stability

Archive for the ‘Complete Markets’ Category

Inequality and Moral Hazard Rents in the Financial Sector

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A recent study by Kaplan and Rauh (h/t Tyler Cowen) confirms what a lot of us suspected anyway: the dominance of Wall Street (bankers, hedge fund managers etc) at the very top end of the income distribution. The presence of bankers at the top end of the income distribution is not surprising – A large portion of this blog has been devoted to the subject of how banks extract significant rents from the implicit and explicit support provided to them by the central bank. It is not surprising then that a significant proportion of these rents flows directly to bank employees. But as Megan McArdle notes, this does not explain the significant presence of hedge fund managers in this list. After all, hedge fund managers do not directly benefit from any state guarantees, implicit or explicit.

The SuperStar Effect?

It is clearly possible that there are many “superstars” in the hedge fund universe who generate genuine alpha and deserve their fat paychecks. But then the question arises as to why the prevalence of such superstars has increased so dramatically in recent times. One explanation may be the increased completeness of markets in the last quarter century which enables hedge fund managers to express a much more diverse range of market views in an efficient and low-cost manner. But this must surely be negated by the reduced supply of easy arbitrage opportunities and the increased competition amongst hedge funds.

Hedge Funds as an Indirect Beneficiary of Moral Hazard “Rents”

Megan McArdle rightly dismisses the role of tax policy on pre-tax compensation of hedge fund managers. But just because hedge funds do not directly benefit from a state guarantee doesn’t mean that central bank policy towards the banking sector is irrelevant in determining their returns. For example, in my post analysing the possible strategy that Magnetar followed in its CDO investments, I observed that Magnetar essentially chose a trade with a positively skewed distribution. As I noted then, it is not a coincidence that Magnetar chose the other side of the trade that was preferred and executed in significant size by bank traders i.e. severely negatively skewed bets such as the super-senior tranche. As I have discussed many times, this demand for negative skewness is driven by the specific dynamics of the moral hazard problem in banking, often exacerbated by the principal-agent problems that exist even between different levels in banks. Therefore, the “alpha” that Magnetar generated would likely not have existed if it were not for the skewed incentives faced by bankers which in turn were driven by the rents they could extract from the state guarantees provided to them.

Economic Rents flow to the Strong

The example of Magnetar merely illustrates a more general principle that is often ignored: the ultimate beneficiary of any economic rent may be far removed from its initial beneficiary. The final distribution of rents is determined by many factors, most critically the competitive dynamics of the industry in question. In the context of our financial sector, the rents flow initially to the banks but are ultimately distributed between bank shareholders, employees, creditors and their clients/counterparties. The specifics of this distribution depends upon the bargaining power of each group and crucially the bargaining power of each group is uncertain and dynamic. So at the height of the economic boom when both equity and debt capital were cheap and plentiful, it is likely that a large portion of the rents was captured by employees, clients and counterparties such as Magnetar. Correspondingly, during the comparatively uncompetitive banking environment that emerged post the bankruptcy of Bear Stearns and Lehman, more of the rents could flow to the capital holders.

It is instructive to examine a couple of instances where the differing competitive dynamics result in dramatically different distributions of the rents flowing from socialized finance. The same moral hazard argument that I have made repeatedly for the banking systems in the United States and the United Kingdom applies in an even stronger fashion to the banking system in Germany which is dominated by a multitude of state-backed institutions. Yet Germany is one of the most unprofitable banking markets in the world – the ultra-competitive nature of the market means that almost all the rents flow out of the banking sector to their clients (depositors and borrowers such as the formidable Mittelstand).

Fix the System, Don’t Blame The Individuals

I have used the language of games and intentional agent adaptation above but the same outcome could easily arise simply via the various groups reacting to local incentives or even via selection mechanisms arising from principal-agent dynamics – Indeed I have argued that active deception on the part of economic agents is unlikely to be selected for. All of which which implies something that I have repeatedly emphasised on this blog: Fix the system, don’t blame the individuals.

The increased completeness of markets means that banks and hedge funds can implement almost any payoff they desire. Attempts to make markets less complete are futile and any attempts to do so can and will be subverted by economic agents. In such an environment, the system will evolve to a state  which maximises the rent extracted from “insurance commitments” by the central bank or other state agencies. To deny this is to assume that economic agents are omniscient as well as angelic. Even angelic agents who only possess knowledge of their local incentives rather than the bigger picture will act no differently from what I’ve sketched out above – An economic system that demands such omniscience on the part of its agents contradicts the very essence of a decentralised market economy.

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Written by Ashwin Parameswaran

September 23rd, 2010 at 11:48 am

Maturity Transformation and the Yield Curve

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Maturity Transformation (MT) enables all firms, not just banks to borrow short-term money to invest in long-term projects. Of course, banks are the most effective maturity transformers, enabled by deposit insurance/TBTF protection which discourages their creditors from demanding their money back all at the same time and a liquidity backstop from a fiat currency-issuing central bank if panic sets in despite the guarantee. Given the above definition, it is obvious that the presence of MT results in a flatter yield curve than would be the case otherwise (Mencius Moldbug explains it well and this insight is implicit as well in Austrian Business Cycle Theory). This post tries to delineate the exact mechanisms via which the yield curve flattens and how the impact of MT has evolved over the last half-century, particularly due to changes in banks’ asset-liability management (ALM) practices.

Let’s take a simple example of a bank that funds via demand deposits and lends these funds out in the form of 30-year fixed-rate mortgages. This loan if left unhedged exposes the bank to three risks: Liquidity Risk, Interest Rate Risk and Credit Risk. The liquidity risk is of course essentially unhedgeable – it can and is mitigated by for example, converting the mortgage into a securitised form that can be sold onto other banks. But the gap inherent in borrowing short and lending long is unhedgeable. The credit risk of the loan can be hedged but often is not, as compensation for taking on credit risk is one of the fundamental functions of a bank. However, the interest rate risk can be and often is hedged out in the interest rate swaps market.

Interest Rate Risk Management in Bank ALM

Prior to the advent of interest rate derivatives as hedging tools, banks had limited avenues to hedge out interest rate risk. As a result, most banks suffered significant losses whenever interest rates rose. For example, after World War II, US banks were predominantly invested in fixed rate government bonds they had bought during the war. Martin Mayer’s excellent book on ‘The Fed’ documents a Chase banker who said to him in reaction to a Fed rate hike in 1952 that “he never thought he would live to see the day when the government would deliberately make the banking system technically insolvent.” The situation had not changed much even by the 1980s – the initial trigger that set off the S&L crisis was the dramatic rise in interest rates in 1981 that rendered the industry insolvent.

By the 1990s however, many banks had started hedging their duration gap with the aim of mitigating the damage that a sudden move in interest rates could do to their balance sheets. One of the earlier examples is the case of Banc One and the HBS case study on the bank’s ALM strategy is a great introduction to the essence of interest rate hedging. More recently, the Net Interest Income (NII) sensitivity of Bank of America according to slide 35 in this investor presentation is exactly the opposite of the typical maturity-transforming unhedged bank – the bank makes money when rates go up or when the curve steepens. But more importantly, the sensitivity is negligible compared to the size of the bank which suggests a largely duration-matched position.

In the above analysis, I am not suggesting that the banking system does not play the interest carry trade at all. The FDIC’s decision to release an interest rate risk advisory in January certainly suggests that some banks are. I am only suggesting that if a bank does play the carry trade, it is because it chooses to do so and not because it is forced to do so by the nature of its asset-liability profile. Moreover, the indications are that many of the larger banks are reasonably insensitive to changes in interest rates and currently choose not to play the carry game ( See also Wells Fargo’s interest rate neutral stance ).

What does this mean for the impact of MT on the yield curve? It means that the role of the interest rate carry trade inherent in MT in flattening the yield curve is an indeterminate one. At the very least, it has a much smaller role than one would suspect. Taking the earlier example of the bank invested in a 30-year fixed rate mortgage, the bank would simply enter into a 30-year interest rate swap where it pays a fixed rate and receives a floating rate to hedge away its interest rate risk. There are many possible counterparties who want to receive fixed rates in long durations – two obvious examples are corporates who want to hedge their fixed rate issuance back into floating and pension funds and life insurers who need to invest in long-tenor instruments to match their liabilities.

So if interest rate carry is not the source of the curve flattening caused by MT, what is? The answer lies in the other unhedged risk – credit risk. Credit risk curves are also usually upward sloping (except when the credit is distressed) and banks take advantage by funding themselves at a very short tenor where credit spreads are low and lending at long tenors where spreads are much higher. This strategy of course exposes them to the risk of credit risk repricing on their liabilities and this was exactly the problem that banks and corporate maturity transformers such as GE faced during the crisis. Credit was still available but the spreads had widened so much that refinancing at those spreads alone would cause insolvency. This is not dissimilar to the problem that Greece faces at present.

The real benefit of the central bank’s liquidity backstop is realised in this situation. When interbank repo markets and commercial paper markets lock up as they did during the crisis, banks and influential corporates like GE can always repo their assets with the central bank on terms not available to any other private player. The ECB’s 12-month repo program is probably the best example of such a quasi-fiscal liquidity backstop.

Conclusion

Given my view that the interest rate carry trade is a limited phenomenon, I do not believe that the sudden removal of MT will produce a “smoking heap of rubble” (Mencius Moldbug’s view). The yield curve will steepen to the extent that the credit carry trade vanishes but even this will be limited by increased demand from long-term investors, most notably pension funds. The conventional story that MT is the only way to fund long-term projects ignores the increasing importance of pension funds and life insurers who have natural long-tenor liabilities that need to be matched against long-tenor assets.

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Written by Ashwin Parameswaran

April 4th, 2010 at 5:54 am

Notes on the Evolutionary Approach to the Moral Hazard Explanation of the Financial Crisis

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In arguing the case for the moral hazard explanation of the financial crisis, I have frequently utilised evolutionary metaphors. This approach is not without controversy and this post is a partial justification as well as an explication of the conditions under which such an approach is valid. In particular, the simple story of selective forces maximising the moral hazard subsidy that I have outlined is dependent upon the specific circumstances and facts of our current financial system.

The “Natural Selection” Analogy

One point of dispute is whether selective forces are relevant in economic systems. The argument against selection usually invokes the possibility of firms or investors surviving for long periods of time despite losses i.e. bankruptcy is not strong enough as a selective force. My arguments rely not on firm survival as the selective force but the principal-agent relationship between investors and asset managers, between shareholders and CEOs etc. Selection kicks in much before the point of bankruptcy in the modern economy. In this respect, it is relevant to note the increased prevalence of shareholder activism in the last 25 years which has strengthened this argument. Moreover, the natural selection argument only serves as a more robust justification for the moral hazard story that does not depend upon explicit agent intentionality but is nevertheless strengthened by it.

The “Optimisation” Analogy

The argument that selective forces lead to optimisation is of course an old argument, most famously put by Milton Friedman and Armen Alchian. However, evolutionary economic processes only lead to optimisation if some key assumptions are satisfied. A brief summary of the key conditions under which an evolutionary process equates to neoclassical outcomes can be found on pages 26-27 of this paper by Nelson and Winter. Below is a partial analysis of these conditions with some examples relevant to the current crisis.

Diversity

Genetic diversity is the raw material upon which Darwinian natural selection operates. Similarly, to achieve anything close to an “optimal” outcome, the strategies available to be chosen by economic agents must be sufficiently diverse. The “natural selection” explanation of the moral hazard problem which I had elaborated upon in my previous post, therefore depends upon the toolset of banks’ strategies being sufficiently varied. The toolset available to banks to exploit the moral hazard subsidy is primarily determined by two factors: technology/innovation and regulation. The development of new financial products via securitisation, tranching and most importantly synthetic issuances with a CDS rather than a bond as an underlying which I discussed here, has significantly expanded this toolset.

Stability

The story of one optimal strategy outcompeting all others is also dependent on environmental conditions being stable. Quoting from Nelson and Winter: “If the analysis concerns a hypothetical static economy, where the underlying economic problem is standing still, it is reasonable to ask whether the dynamics of an evolutionary selection process can solve it in the long run. But if the economy is undergoing continuing exogenous change, and particularly if it is changing in unanticipated ways, then there really is no “long run” in a substantive sense. Rather, the selection process is always in a transient phase, groping toward its temporary target. In that case, we should expect to find firm behavior always maladapted to its current environment and in characteristic ways—for example, out of date because of learning and adjustment lags, or “unstable” because of ongoing experimentation and trial-and-error learning.”

This follows logically from the ‘Law of Competitive Exclusion‘. In an environment free of disturbances, diversity of competing strategies must reduce dramatically as the optimal strategy will outcompete all others. In fact, disturbances are a key reason why competitive exclusion is rarely observed in ecosystems. When Evelyn Hutchinson examined the ‘Paradox of the Plankton’, one of the explanations he offered was the “permanent failure to achieve equilibrium” . Indeed, one of the most accepted explanations of the paradox is the ‘Intermediate Disturbance Hypothesis’ which concludes that ecosystem diversity may be low when the environment is free of disturbances.

Stability here is defined as “stability with respect to the criteria of selection”. In the principal-agent selective process, the analogous criteria to Darwinian “fitness” is profitability. Nelson and Winter’s objection is absolutely relevant when the strategy that maximises profitability is a moving target and there is significant uncertainty regarding the exact contours of this strategy. On the other hand, the kind of strategies that maximise profitability in a bank have not changed for a while, in no small part because of the size of the moral hazard free lunch available. A CEO who wants to maximise Return on Equity for his shareholders would maximise balance sheet leverage, as I explained in my first post. The stability of the parameters of the strategy that would maximise the moral hazard subsidy and accordingly profitability, ensures that this strategy outcompetes all others.

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Written by Ashwin Parameswaran

March 13th, 2010 at 5:22 am

The “Theory of the Second Best” and the Financial Crisis

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Much of the debate regarding the causes of the financial crisis ignores the fact that we live in a “second best” world. The “Theory of the Second Best” states that in a world that is far from a textbook “free market”, any move towards the theoretical free market optimum does not necessarily increase welfare.

Our current financial system is clearly far from a free market. The implicit and explicit guarantee to bank creditors via deposit insurance and the TBTF doctrine is a fundamental deviation from free market principles. On the other hand, derivatives markets are among the least regulated markets in any sector.

This second-best, hybrid nature of our financial system means that any discussion of the crisis must be strongly empirical in nature. Deductive logic is essential but a logical argument with incomplete facts can be made to fit almost any conclusion. So the Keynesians blame the free market and deregulation, the libertarians blame government action and the behavioural economists blame irrationality. But no one stops to consider any facts that don’t fit their preferred thesis.

The key conclusion of my work is that it is the combination of the moral hazard problem driven by bank creditor guarantees and the deregulated nature of key components of the financial system that caused the crisis. This is not a new argument. The argument for regulation itself rests on the need to protect the taxpayer in the presence of this creditor guarantee. The Fed recognised this argument as early as 1983. As John Kareken noted, “Deregulation Is the Cart, Not the Horse”. The growth of the CDS and other derivatives markets was not a problem by itself. It caused damage by enabling the banks to maximise the value of the free lunch derived from the taxpayer. The same could be said for bank compensation practices.

If re-regulation could work, then I’d be in favour of it. But I don’t think it can. As I’ve discussed before (1,2,3), almost any regulation will be arbitraged away by the banks. The only regulations that may be difficult to arbitrage are blunt and draconian regulations which will dramatically reduce the efficiency of the system. Even then, the odds of arbitrage are not low enough.

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Written by Ashwin Parameswaran

December 28th, 2009 at 12:31 pm

Complete Markets and the Principal-Agent Problem in Banking

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In an earlier note, I discussed how monitoring and incentive contracts can alleviate the asymmetric information problem in the principal-agent relationship. Perfect monitoring, apart from being impossible in many cases, is also too expensive. As a result, most principals will monitor to the extent that the expense is justified by the reduced incentive mismatch. In most industries, this approach is good enough. The menu of choices available to an agent is usually narrow and the principal only needs to monitor for the most egregious instances of abuse.

In fact, this was the case in banking as well until the advent of derivatives. Goodhart’s Law by itself does not guarantee arbitrage by the agent – the agent also needs a sufficiently wide menu of choices that the principal cannot completely monitor or contract for.

As discussed in an earlier note, agents in banking have a strong incentive to enter into bets with negatively skewed payoffs. The limiting factor was always the supply of such financial instruments. For example, supply of AAA corporate bonds has always been limited. Securitisation and tranching technology increased this limit substantially by using a diverse pool of credits with a lower rating to produce a substantial senior AAA tranche. But the supply was still limited by the number of mortgages or bonds that were available.

The innovation that effectively removed any limit on the agent’s ability to arbitrage was the growth of the CDS market and the development of the synthetic CDO. As the UBS shareholder report notes:

“Key to the growth of the CDO structuring business was the  development of the credit default swap (”CDS”) on ABS in June 2005 (when ISDA published  its CDS on ABS credit definitions). This permitted simple referencing of ABS through a CDS. Prior to this, cash ABS had to be sourced for inclusion in the CDO Warehouse.”

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Written by Ashwin Parameswaran

December 28th, 2009 at 9:18 am

A “Rational” Explanation of the Financial Crisis

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There is widespread disagreement amongst commentators as to the underlying causes of the 2008-2009 financial crisis. The most contentious topic is the role of market irrationality and ignorance in fuelling the preceding boom. In the note below, I construct a “rational” thesis that explains all the key facts of the financial crisis without relying on irrational behaviour or ignorance on the part of agents or the market. The thesis focuses solely on the economic incentives facing the various players and crucially, the interaction of these incentives with government policies.


To summarise the key arguments,

  • Implicit/Explicit protection of bank creditors increases the optimal leverage of bank balance sheets.
  • The maximum/optimal leverage can be achieved by investing in “safe” assets such as AAA-rated securities.
  • The principal-agent problem within banks exacerbates the moral hazard of creditor protection. Access to cheap leverage incentivises agents to take on bets with negatively skewed payoffs, not volatile payoffs.
  • Apart from regulatory capital, supply of  “safe” assets was the prime constraint on leverage until recently. More complete markets  have weakened this supply constraint.


“Optimal” Leverage for Banks


The Economist asks why banks are so averse to raising equity and correctly identifies the role of the implicit/explicit guarantee enjoyed by bank creditors. The role of deposit insurance in raising the “optimal leverage” of a bank was identified in 1977[i] by Robert Merton who priced the deposit insurance contract as a put option on the value of the bank’s assets.[ii]

The role of deposit insurance is easily explained via the logic of the Modigliani-Miller theorem. M&M Proposition 1 essentially states that the capital structure is irrelevant in determining the total value of the firm. In other words, it is the size of the pie that matters, not how you slice it up[iii]. In the presence of explicit/implicit debt guarantees, one of the key conditions required for the proposition to hold is violated: the size of the pie is no longer fixed when the capital structure is changed[iv].


Merton’s analysis of deposit insurance can be re-stated and extended as follows:

The value of the firm increases with increased leverage and increased riskiness of the asset pool in the following idealised scenario:

  • M&M assumptions hold[v]
  • No bank capital regulations
  • Explicit insurance premium is below the true economic cost of protection
  • Non-negative probability of full/partial protection of uninsured creditors: Even a small probability of bailout of uninsured creditors causes such creditors to demand a lower rate of return and therefore increases the “size of the pie”.


Limits to Leverage: Bank Capital Regulations

Regulatory capital requirements ensure that infinite leverage is not feasible[vi]. Risk-weighted capital requirements usually mean that the bank can choose from a continuum of risk-leverage combinations with high risk assets and low leverage on one side and low risk assets and high leverage on the other. Moreover till 2004, SEC’s net capital rule limited the debt-to-net capital ratio of investment banks to 12:1.


The evidence on the increased leverage of both commercial and investment banks is clear but there is no evidence that the asset profile became markedly riskier. After all, weren’t most of the losses suffered on super-senior tranches of CDOs? These tranches were supposed to be even safer than a  AAA bond! Many argue that the low risk asset profile of banks proves that moral hazard and bank employee incentives did not cause the financial crisis[vii]. Any explanation of the crisis needs therefore to explain this phenomenon of higher leverage combined with apparently “lower” risk assets rather than an alternative combination of more risky assets and a lower leverage.


The explanation is simple: if the bank can issue debt at a “subsidised” rate due to the protection of bank creditors by the state, then increased leverage increases the value of the firm i.e. the size of the pie. It is quite literally a free lunch courtesy of the government. Each extra dollar borrowed increases the free lunch available to the stockholders and managers of the firm. Once we understand that increased leverage increases the size of the pie, then regulatory capital requirements based on risk-weighted assets almost necessitate the choice of “lower risk” assets that help maximise absolute leverage.


The Principal-Agent Problem exacerbates the Moral Hazard problem


Many studies conclude  that agent/manager risk-aversion counteracts the risk-seeking preference of the stockholders[viii]. Bebchuk and Spamann[ix] accept this thesis but argue that the increased high-powered incentives offered to senior management in the form of stock and stock options aligns stockholder and senior management interests in favour of increased risk-taking. This analysis ignores

  • the incentive structure agents in banking work under.
  • the wide variety of distributional choices agents possess.
  • the impact of cheap leverage on agent choices.
  • accounting methodology of bonds/loans in banks.
  • Knowledge asymmetry between principals and agents
  • Principal-agent problems within banks i.e. between different layers of management or between management and traders.


  • Incentive structures in banking are characterised by high-powered incentives including significant annual cash bonuses and restricted stock compensation and risk of termination based on absolute and comparative evaluation versus other agents.

  • Agent risk-aversion is usually analysed in the context of a choice between symmetrical bets of varying volatility. This is too simplistic – agents choose not only the volatility of the distribution they operate under but also its higher moments, most notably its skewness. In fact, the dominant assets on bank balance sheets are bonds or loans.  The primary risk characteristic of the returns distributions of bonds and loans is not their volatility but their skewness. Specifically, bonds and loans are negatively skewed bets with a high probability of a small profit and a low probability of a significant loss on default. The “safer” the loan, the more asymmetric the payoff i.e. AAA bonds have a much more asymmetric risk-reward profile than junk bonds[x].

    The combination of high-powered incentives and the ability to choose tailored payoff distributions with a given volatility and skewness means that agents in banks are faced with an incentive structure similar to hedge funds. This makes negatively skewed bets extremely attractive. Andrew Lo pointed this out in the context of hedge funds with his example of Capital Decimation Partners where a systematic strategy of shorting out-of-the-money(OTM) options has a returns distribution that is economically attractive to the fund manager as well as appearing to produce “alpha” for the investor
    [xi]. In fact, the incentive structure facing bank managers/traders is even more favourable for negatively skewed bets for two important reasons:

  • Unlike hedge funds, increased leverage is always available at a less than economic cost. Given that eliminating risk is not an option for the agent[xii], agents need to trade off between
    1. minimising the probability of loss which could lead to bankruptcy or termination by the principal.
    2. maximising the payoff under the high-powered incentive contract and achieving a sufficient return on equity for the stockholder.

Cheap leverage means that the tradeoff is no longer relevant. The very fact that leverage can be increased without a commensurate  increase in the cost of debt means that managers can increase not only expected return but also the expected probability of a positive return almost without limit.

  • Unlike the simple strategy of shorting OTM options that Andrew Lo outlines which is subject to mark-to-market swings, many of the assets on bank balance sheets are not subject to mark-to-market accounting or are only subject to mark-to-model on an irregular basis. Selling OTM options in a liquid market exposes the agent to mark-to-market swings which can in many cases eliminate the benefits of negative skewness[xiii].

  • The inherent asymmetric knowledge problem between managers/traders and stockholders means that “negatively skewed” bets are preferred by managers. The stockholder cannot distinguish between genuine alpha and a severely negatively skewed payoff chosen by the manager. Moreover, even without asymmetric information, the mere presence of true uncertainty means that the principal and the agent may both fail to distinguish between true alpha and extreme negative skewness. Taleb[xiv] identifies many reasons why severely negatively skewed bets seem to be less risky than they are.The difficulty of identifying negative skewness combined with the necessarily short time horizons on which agents are evaluated by principals means that agents who employ negatively skewed strategies are likely to be “selected” versus other agents who do not employ such strategies by their principals in any prolonged period of stability. This illustrates both why negatively skewed strategies are likely to outcompete other strategies in stable market conditions as well as why it is so difficult for agents to bet the other way. They will only do so if there is a significant mispricing and crucially if they are also convinced about the timing.

  • One solution usually employed by stockholders is to give senior management significant stock exposure so that they can monitor the junior managers whose compensation is much more tilted towards cash bonuses. In fact, the losses suffered by senior management on their stock holdings is used to argue that moral hazard and banker pay was not responsible for the crisis. This analysis ignores the fact that the principal-agent problem between top bank managers and the junior managers/traders  is equally severe[xv]. The primary reasons for this are:
    1. The over-specialisation at lower and middle levels in investment banks which means that most senior managers do not possess the adequate deep experience in all the business areas that they supervise.
    2. The rapid pace of innovation in investment banking in the recent past which has meant that managerial knowledge is frequently out of date. Many business areas may have risen to prominence so recently that managers have limited practical knowledge of them.


Limits to Leverage: Supply of Skewed Assets


Leverage is also constrained by the supply of assets with negatively skewed payoffs.  Until quite recently, supply of such assets was limited. For example, AAA corporate bonds were extremely limited in supply. In other words, the market was “incomplete”.


The explosion in CDO issuance as well as the growth of the CDS market means that the supply has increased dramatically in recent times. The fact that the CDS notional outstanding is not limited by constraints such as bond notional outstanding means that there is literally no limit to the supply of assets with any chosen skewness. Combined with the ability to issue tranched products on the back of such CDS via synthetic CDOs, any risk-reward payoff can be constructed without a supply constraint. In this manner, more “complete” markets have enabled economic players to extract more value from the implicit creditor protection.


Super-Senior Tranches: The Ideal Product


In the above framework, it is not surprising that super-senior tranches of MBS CDOs were so favoured by banks. Super-senior tranches also had the added advantage of being incidental to a fee-generating, client driven activity i.e. the origination of CDOs of which the other tranches were sold on to clients. Therefore, increasing amounts of super-senior tranches could be piled onto balance sheets in the name of facilitating client business rather than the more genuine reason of proprietary risk taking in a preferred risk-return profile.


Its worth emphasizing that super-senior tranches are not an economically viable investment for banks unless they are leveraged up significantly. To illustrate, if a bank funds at 5% and a super-senior tranche yields 50 bps above funding, then an unlevered investment in a super-senior barely pays for the bills, let alone the bonuses of employees and the return on equity demanded by stockholders. Of course, with only 1.6% of the investment coming from capital and the remaining 98.4% being borrowed (AAA tranches being 20% risk-weighted and 8% being the capital requirement for 100% risk weight), the same investment leads to a return on equity of 36.25% before expenses, bonuses etc.


This also explains why the market for super-seniors is so thin – they are not economically profitable for any other market player to hold onto as they do not have access to such high levels of leverage. The only exit option other than selling it onto another bank was to buy insurance on it but this exposes the bank to the credit risk of the counterparty. Therefore, only AAA insurers would do i.e. AIG or the monolines.


UBS’ Shareholder Report on the Write-Downs: A Case Study


This section will provide some examples to back up the propositions made above from the shareholder report prepared by UBS analysing the background and causes of their writedowns[xvi]:

  • pg 13: “The CDO desk received structuring fees on the notional value of  the deal, and focused on Mezzanine (“Mezz”) CDOs, which generated fees of  approximately 125 to 150 bp (compared with high-grade CDOs, which generated fees of  approximately 30 to 50 bp).” An example of how profitable CDOs were as a client fee business. This of course made it easier to argue that holding the super-senior tranche facilitated the profitable client business.

  • pg 13: “Key to the growth of the CDO structuring business was the  development of the credit default swap (“CDS”) on ABS in June 2005 (when ISDA published  its CDS on ABS credit definitions). This permitted simple referencing of ABS through a CDS. Prior to this, cash ABS had to be sourced for inclusion in the CDO Warehouse.” More complete markets via the introduction of the CDS on ABS meant that the supply constraint on the CDO business was removed.

  • pg 14: ” Following completion of the CDO securitization process, UBS generally sold subordinate (i.e.  lower rated) CDO tranches to external investors. In 2005, the CDO desk also sold the highest rated / AAA rated (the so called “Super Senior”) tranches of these CDOs to third party investors along with subordinate tranches. However, after the first few deals, the IB retained the Super Senior tranche of CDOs it structured on its own books. One factor influencing this change was that the CDO desk viewed retaining the Super Senior tranche of CDOs as an attractive source of profit, with the funded positions yielding a positive carry (i.e. return) above the internal UBS funding rate and the unfunded positions generating a positive spread. Further, within the CDO desk, the ability to retain these tranches was seen as a part of the overall CDO business, providing assistance to the structuring business more generally. Apart from the Super Senior positions retained by the CDO desk from its CDO structuring activities, the desk also purchased Super Senior positions from third parties to be hedged and held on UBS’s books.” Illustrates how from almost the very beginning, the super senior tranches were consciously retained by the CDO desk as an “attractive source of profit” primarily due to the low internal funding rate (cheap leverage) as well as the “unfunded” or off-balance sheet positions generating a positive spread i.e. the off-balance sheet positions did not even have to beat the already low hurdle rate of UBS’ internal funding rate. The justification that retaining the super-senior tranches was key to the structuring and origination of the CDO business is also used effectively.

  • “By the end of 2007, losses on the positions held in the CDO Warehouse plus retained pipeline positions represented approximately one quarter of the CDO desk’s losses (i.e. approximately 16% of UBS’s total Subprime Losses as at 31 December 2007).” “Losses on the Super Senior positions contributed approximately three quarters of the CDO desk’s total losses (or 50% of UBS’s total losses) as at 31 December 2007.” Clearly shows that the majority of losses were not on warehoused positions but on the “Super Senior” investments that were expected to be held on the balance sheet for longer periods.

  • “Negative Basis Super Seniors: these were Super Senior positions where the risk of loss was hedged through so-called Negative Basis (or “NegBasis”) trades where a counterparty, such as a monoline insurer provided 100% loss protection. The hedge resulted in a credit exposure towards the protection seller. As at the end of 2007, write-downs on these positions represented approximately 10% of the total Super Senior losses.” These positions were hedged with monoline insurers.

  • “Amplified Mortgage Portfolio (“AMPS”) Super Seniors: these were Super Senior positions where the risk of loss was initially hedged through the purchase of protection on a proportion of the nominal position (typically between 2% and 4% though sometimes more). This level of hedging was based on statistical analyses of historical price movements that indicated that such protection was sufficient to protect UBS from any losses on the position. Much of the AMPS protection has now been exhausted, leaving UBS exposed to write-downs on losses to the extent they exceed the protection purchased. As at the end of 2007, losses on these trades contributed approximately 63% of total Super Senior losses.” The most interesting of the super-senior holdings are the AMPS which were delta-hedged with a small proportion of the underlying. This of course ignores the volatility and correlation exposure of the super-senior tranche and only hedges against very small moves as UBS found out. These positions were responsible for a large percentage of the losses. But the question arises: why did the CDO desk choose such an imperfect hedging strategy which was almost no better than holding the position unhedged?

  • pg 19-20: “UBS’s Market Risk framework relies upon VaR and Stress Loss to set and monitor market risks at a portfolio level.” “In the context of the CDO structuring business and Negative Basis and AMPS trades, IB MRC relied primarily upon VaR and Stress limits and monitoring to provide risk control for the CDO desk. As noted above, there were no Operational limits on the CDO Warehouse and throughout 2006 and 2007, there were no notional limits on the retention of unhedged Super Senior positions and AMPS Super Senior positions, or the CDO Warehouse.”
    “MRC VaR methodologies relied on the AAA rating of the Super Senior positions. The AAA rating determined the relevant product-type time series to be used in calculating VaR. In turn, the product-type time series determined the volatility sensitivities to be applied to Super Senior positions. Until Q3 2007, the 5-year time series had demonstrated very low levels of volatility sensitivities. As a consequence, even unhedged Super Senior positions contributed little to VaR utilisation.” pg 30-31: “Once hedged, either through NegBasis or AMPS trades, the Super Senior positions were VaR and Stress Testing neutral (i.e., because they were treated as fully hedged, the Super Senior positions were netted to zero and therefore did not utilize VaR and Stress limits). The CDO desk considered a Super Senior hedged with 2% or more of AMPS protection to be fully hedged. In several MRC reports, the long and short positions were netted, and the inventory of Super Seniors was not shown, or was unclear. For AMPS trades, the zero VaR assumption subsequently proved to be incorrect as only a portion of the exposure was hedged as described in section 4.2.3, although it was believed at the time that such protection was sufficient.” “Incomplete capture of risk attributes by risk control: The risk reports for this business reported notionals (but after netting) and credit deltas. The presentation of the risk on a credit delta basis overlooked the fact that there was only 2-4% (sometimes more) protection on Mezzanine RMBS. MRC did not seek to expand the monitoring framework to capture other dimensions of the risk, such as gamma (i.e., the absolute change in the delta of an option when the price of the underlying asset moves).”
    The above is less a criticism of the VaR methodology and the various deficiencies of risk management in UBS than it is an illustration of how serious the principal-agent problem is between senior managers and the business areas. It is clear that the AMPS strategy was solely constructed to attain a zero VaR exposure. It is inconceivable that the CDO desk genuinely believed that the position had no risk. However, their managers and risk managers clearly did not question this. Indeed it is quite possible that senior management only focused on the VaR number and not on the actual risk dynamics of the desk’s position.

In the above note, I have argued that the moral hazard explanation focusing on the implicit/explicit protection given to bank creditors fits all the facts of the crisis, especially when considered along with the principal-agent problem and the increasingly complete financial markets. Two objections that can still be raised to the above are:

  • Given the significant losses suffered by stockholders in the past, why don’t stockholders walk away from the industry and deny it funding?
  • Doesn’t the thesis explain too much? After all, will the same dynamics not have played out albeit on a smaller scale just because of agent preferences for negative skewness and more complete markets?

The answer to the two questions is connected. Principal-agent problems and conflicts between the interests of shareholders, managers and creditors are inherent in each organisation to some degree but usually, the stakeholders develop ways to mitigate such problems. If no such avenues for mitigation are feasible, they always retain the option to walk away from the relationship.

This dynamic changes significantly in the presence of a “free lunch” such as the one provided by creditor protection. In such a case, not walking away even after suffering losses is an entirely rational strategy. Each stakeholder has a positive probability of capturing part of the free lunch in the future even if he has not been able to do so in the past. In fact, shareholder optimism may well be proven correct if significant compensation restrictions are imposed on the entire industry and this increases the share of the “free lunch” flowing to them.


[i] R. C Merton, “An application of modern option pricing theory,” Journal of Banking and finance 1 (1977): 3–11. http://www.people.hbs.edu/rmerton/analytic derivation of cost of loan guarantees.pdf

[ii] A simple application of the Merton Model

[iii] Merton Miller’s explanation of the theorem,” Say you have a pizza, and it is divided into four slices. If you cut it into eight slices, you still have the same amount of pizza.” http://arnoldkling.com/econ/saving/corpfin.html

[iv] 1. M. Rubinstein, “Great Moments in Financial Economics: II. Modigliani-Miller Theorem,” Journal Of Investment Management 1, no. 2 (2003). http://leeds.colorado.edu/uploadedFiles/_Documents/Centers_of_Excellence/Burridge_Center/RubinsteinHistoryofModigliani-Miller.pdf : An excellent discussion of M&M and the assumptions needed for both propositions to hold

[v] ref Rubinstein paper above

[vi] Some would argue that off-balance-sheet vehicles and OTC derivatives remove the regulatory capital constraint.

[vii] See for example Jeffrey Friedman http://causesofthecrisis.blogspot.com/2009/10/real-bank-pay-scandal.html

[viii] D. Hirshleifer and A. V Thakor, “Managerial conservatism, project choice, and debt,” The Review of Financial Studies 5, no. 3 (1992): 437–470.

[ix] L. A. Bebchuk, H. Spamann, and P. Hall, “Regulating Bankers’ Pay.” http://www.law.harvard.edu/programs/olin_center/papers/pdf/Bebchuk_641.pdf

[x] The negative skewness of many asset profiles but especially that of banks, monoline insurers etc means that the simplified Merton model may not be appropriate to model the valuation of the different components of the capital structure.

[xi] A. W Lo, “Risk management for hedge funds: Introduction and overview,” Financial Analysts Journal 57, no. 6 (2001): 16–33.http://www.alphasimplex.com/pdfs/RiskMgmtForHF.pdf

[xii] i.e. the agent cannot limit his activities to merely exploiting the “charter value” of the bank.

[xiii] It is relevant that in Andrew Lo’s example of the Capital Decimation Partners, the OTM options sold are of a very short tenor (less than three months). This means that there is significant time decay which mitigates the mark-to-market impact of a fall in the underlying. On the other hand, loans/bonds are of a much longer tenor and if they were liquidly traded, the negative mark-to-market swings would make the negative skew superfluous for the purposes of the agent who would be evaluated on the basis of the mark-to-market and not the final payout. The obvious example is a vanilla CDS contract.

[xiv] N. N Taleb, “Bleed or Blowup? Why Do We Prefer Asymmetric Payoffs?,” The Journal of Behavioral Finance 5, no. 1 (2004): 2–7.

[xv] An example amongst quants http://finextra.com/fullstory.asp?id=20697

[xvi] http://www.ubs.com/1/ShowMedia/investors/releases?contentId=140331&name=080418ShareholderReport.pdf

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Written by Ashwin Parameswaran

November 6th, 2009 at 2:40 pm