macroresilience

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Archive for the ‘Moral Hazard’ Category

Implications of Moral Hazard in Banking

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In my previous post, I explained how a moral hazard outcome can come out even in the absence of explicit agent intentionality to take on more risk. This post will focus on the practical implications of the moral hazard problem in banking. Much of the below is just a restatement of arguments made in my first post that I felt needed to be highlighted. For references and empirical evidence, please refer to the earlier post.

Moral hazard can persist even if the bailout is uncertain. Even a small probability of a partial bailout will reduce the rate of return demanded by bank creditors and this reduction constitutes an increase in firm value. The implication is that there is no partial solution of the moral hazard problem. There must be a credible and time-consistent commitment that under no circumstances will there even be a partial creditor bailout.

In a simple Modigliani-Miller world, the optimal leverage for a bank is therefore infinite. Even without invoking Modigliani-Miller, the argument for this is intuitive. If each incremental unit of debt issued is issued at less than its true economic cost, it adds to firm value. In reality of course, there are many limits to leverage, the most important being regulatory capital requirements.

Increased leverage and a riskier asset portfolio are not substitutable. Most moral hazard explanations of the crisis claim that the implicit/explicit creditor protection from deposit insurance and the TBTF doctrine causes banks to “take on more risk”, risk being defined as a combination of higher leverage and a riskier asset portfolio. The above arguments show that risk taken on via increased leverage is distinctly superior to the choice of a riskier asset portfolio – Unlike increased leverage, riskier assets do not include any free lunch component.

Regulatory capital requirements force banks to choose from a continuum of choices with low leverage and risky assets combinations on one side to high leverage and “safe” assets on the other (This argument assumes that off balance sheet vehicles cannot fully remove the regulatory capital constraint). Given that high leverage maximises the moral hazard subsidy, banks are biased to move towards the high leverage, “low risk” combination. The frequent divergence between market risk-reward and ratings-implied risk-reward of course means that riskier assets will still be invested in. But they need to clear a higher hurdle than AAA assets.

High-powered incentives encourage managers/traders to operate under high leverage. Bonuses and equity compensation help align the interests of the owner and the manager.

Risk from an agent’s perspective is defined by the skewness of asset returns as well as the volatility. Managers/Traders are motivated to minimise the probability of a negative outcome i.e. maximise negative skew. This tendency is exacerbated in the presence of high-powered incentives. Andrew Lo illustrated this in his example of the Capital Decimation Partners in the context of hedge funds (Hedge fund investors of course do not have an incentive to maximise leverage without limit).

The above is a short explanation of the consequences of moral hazard that explains the key facts of the crisis – high leverage combined with an apparently safe asset portfolio of AAA assets such as super-senior tranches of ABS CDOs. Contrary to conventional wisdom, a moral hazard outcome is characterised by negatively skewed bets, not volatile bets.

The dominance of negatively skewed bets means that it is extremely difficult to detect the outcome of moral hazard by statistical methods. As Nassim Taleb explains here, a large sample size is essential. If the analysis is limited to a “calm” period, the mean as well as the variance of the distribution will be significantly misestimated. Moreover, the problem is exacerbated if one has assumed a symmetric distribution as is often the case. The “low measured variance” is easily misunderstood as a refutation of the moral hazard outcome rather than the confirmation it really represents.

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Written by Ashwin Parameswaran

January 6th, 2010 at 1:49 am

Moral Hazard: A Wide Definition

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A common objection to the moral hazard explanation of the financial crisis runs as follows: No banker explicitly factored in the possibility of a bailout into his decision-making process.

The obvious answer to this objection is the one Andrew Haldane noted:

“There was a much simpler explanation according to one of those present. There was absolutely no incentive for individuals or teams to run severe stress tests and show these to management. First, because if there were such a severe shock, they would very likely lose their bonus and possibly their jobs. Second, because in that event the authorities would have to step-in anyway to save a bank and others suffering a similar plight.

All of the other assembled bankers began subjecting their shoes to intense scrutiny. The unspoken words had been spoken. The officials in the room were aghast. Did banks not understand that the official sector would not underwrite banks mismanaging their risks?

Yet history now tells us that the unnamed banker was spot-on. His was a brilliant articulation of the internal and external incentive problem within banks. When the big one came, his bonus went and the government duly rode to the rescue. The time- consistency problem, and its associated negative consequences for risk management, was real ahead of crisis. Events since will have done nothing to lessen this problem, as successively larger waves of institutions have been supported by the authorities.”

Bankers did not consciously take on more risk. They took on less protection against risk, particularly extreme event risk.

But this too is an unnecessarily limited definition of moral hazard. Moral hazard can persist without any explicit intention on the part of the agent to behave differently.

Spontaneous Order

It is not at all necessary that each economic agent is consciously aware of and is trying to maximise the value of the moral hazard subsidy. A system that exploits the subsidy efficiently can arise by each agent merely adapting to and reacting to the local incentives and information put in front of him. For example, the CEO is under pressure to improve return on equity and increases leverage at the firm level. Individual departments of the bank may be extended cheap internal funding and told to hit aggressive profitability targets without using capital. And so on and so forth. It is not at all necessary that each individual trader in the bank is aware of or working towards a common goal.

Nevertheless, the system adapts in a manner as if it was consciously directed towards the goal of maximising the subsidy. In other words, a Hayekian spontaneous order could achieve the same result as a constructed order.

Natural Selection

The system can also move towards a moral hazard outcome without even partial intent or adaptation by economic agents given a sufficiently diverse agent strategy pool, a stable environment and some selection mechanism. This argument is similar to Armen Alchian’s famous paper arguing for the natural selection of profit-maximising firms.

The obvious selection mechanism in banking is the principal-agent relationship at all levels i.e. shareholders can fire CEOs, CEOs can fire managers, managers can fire traders etc. If we start out with a diverse pool of economic agents pursuing different strategies, only one of which is a high-leverage,bet-the-house strategy, sooner or later this strategy will outcompete and dominate all other strategies (provided that the environment is stable).

In the context of Andrew Haldane’s comment on banks’ neglect of risk management, banks that would have invested in risk insurance would have systematically underperformed their peer group during the boom. Any CEO who would have elected to operate with low leverage would have been fired a long time before the crisis hit.

To summarise, moral hazard outcomes can and indeed did drive the financial crisis through a variety of channels: explicit agent intentionality, adaptation of agents to local incentives or merely market pressures weeding out those firms/agents that refuse to maximise the moral hazard free lunch.

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Written by Ashwin Parameswaran

January 1st, 2010 at 8:30 pm

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

The Role of Discretion in Financial Regulation

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Steve Waldmann’s recent post explains why giving financial regulators discretion in choice of policy is almost always a bad idea. In his words:

“An enduring truth about financial regulation is this: Given the discretion to do so, financial regulators will always do the wrong thing.”

The reason of course is the time consistency problem . The temptation for the regulator and central bank to use their “discretion” to bail out the banks is overwhelming. The market will correctly equate a discretionary regulatory environment to be a bailout-prone one. As Lacker and Goodfriend observed in their paper on central bank lending policies in times of crisis:

“The problem with adding variability to central bank lending policy is that the central bank would have trouble sticking to it, for the same reason that central banks tend to overextend lending to begin with. An announced policy of constructive ambiguity does nothing to alter the ex post incentives that cause the central banks to lend in the first place.”

But what about the alternative? Would a regulatory environment that is written in stone perform any better? Most likely it would not – regulations that are written in stone suffer from Goodhart’s Law. The clearer and more detailed the regulation, the easier it is for market participants to arbitrage it.

Goodhart’s Law is the reason why algorithm-based technology services such as Google and Digg prefer to keep their algorithm private and opaque. However, as we’ve discussed above, discretion and opacity is not an option in financial regulation.

So how do we avoid arbitrage without having to resort to discretion and ambiguity in the regulatory framework? Goodhart’s Law is applicable only when we focus on intermediate targets that we presume are good proxies for our objective. The answer is to shift focus from intermediate proxy indicators of excessive risk, such as executive compensation or capital requirements, to the ultimate objective itself.

But is this even achievable? For example, Google and Digg have no option but to focus on a reasonable accurate proxy. The same may be true for financial regulation.

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Written by Ashwin Parameswaran

December 25th, 2009 at 1:34 pm

The Chicago Pit on Negatively Skewed Bets

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The Chicago pit has a saying that captures exactly the perils of entering into a negatively skewed bet:

“Traders who sell volatility eat like chickens and shit like elephants.”

Taleb has shown that negatively skewed bets are tempting enough even when we’re risking our own capital. The moral hazard problem and the resultant cheap leverage makes the trade a no-brainer for a bank.

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Written by Ashwin Parameswaran

December 16th, 2009 at 5:20 pm

Volcker on Financial Innovation

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In a discussion in the WSJ, Paul Volcker had this to say about the impact of financial engineering:

“Now, I have no doubts that it moves around the rents in the financial system, but not only this, as it seems to have vastly increased them.”

This is an important and often overlooked point. Financial innovation has led to a significant increase in the rents that the financial sector is able to extract from the rest of the economy. Moreover, much of this increased rent is extracted from the taxpayer.

As I discussed earlier in more detail, incomplete markets kept the moral hazard genie inside the bottle. Financial innovation such as CDS and synthetic CDOs arose primarily to make markets more complete and enable the financial sector to maximise the rents that it could extract from the explicit/implicit guarantee of the state. The solution to the problem is not better regulation but the removal of the guarantee.

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Written by Ashwin Parameswaran

December 15th, 2009 at 5:56 pm

Fix The System, Don’t Blame The Individuals

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Quoting from John Sterman’s authoritative book on system dynamics,

” A fundamental principle of system dynamics states that the structure of the system gives rise to its behavior. However, people have a strong tendency to attribute the behavior of others to dispositional rather than situational factors, that is, to character and especially character flaws rather than the system in which these people are acting. The tendency to blame the person rather than the system is so strong psychologists call it the “fundamental attribution error” (Ross 1977). In complex systems, different people placed in the same structure tend to behave in similar ways. When we attribute behavior to personality we lose sight of how the structure of the system shaped our choices. The attribution of behavior to individuals and special circumstances rather than system structure diverts our attention from the high leverage points where redesigning the system or government policy can have significant, sustained, beneficial effects on performance (Forrester 1969, chap.6; Meadows 1982). When we attribute behavior to people rather than system structure the focus of management becomes scapegoating and blame rather than the design of organizations in which ordinary people can achieve extraordinary results. ” (page 28-29)

Sterman’s comment is especially relevant to the current debate on reforming and regulating our financial system. It is misguided to focus on greedy bankers and incompetent or compromised regulators. Bankers and regulators are merely adapting to the incentives presented to them by our current economic and political system.

In fact, the real question is why so few economic actors indulge in fraud or milking taxpayer guarantees when they have every incentive to. After all, choosing not to play the game means accepting lower returns if one’s a shareholder and accepting lower bonuses and possibly even being fired for underperformance if one’s a manager or a trader.

The answer is that our ethics prevent us from exploiting the situation. But our ethical standards do not remain constant. They can and will erode if a perverse system is in place for too long. This gradual erosion of ethical standards is the real risk we face if we do not reform our system and fix the incentives. We may not realise this until it’s already too late and reversing this process and rebuilding ethical standards and trust in an economic system will be no easy task.

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Written by Ashwin Parameswaran

December 4th, 2009 at 3:19 pm

Negatively Skewed Bets and Fraud: Reconciling the “Control Fraud” and “Moral Hazard” explanations of the S&L crisis

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Commentators still disagree on the  role of fraud in the S&L crisis. Economists usually deny the importance of fraud and attribute the losses to “honest” risk-taking whereas criminologists such as William Black[i] highlight the role of systematic “control fraud”. But are these arguments incompatible with each other? I argue that the differences stem from an erroneous and incomplete understanding of the moral hazard issue.


According to the conventional moral hazard explanation [ii], S&Ls took on increasingly risky gambles and failed. However, it only makes sense to take on high risk 50-50 gambles if the owners of the S&L held diversified portfolios in which the individual S&L was not an outsized component. Else, the strategy of maximising the volatility of the asset portfolio is not optimal. Instead, the S&L owner’s optimal strategy is to maximise the probability of a positive outcome (i.e. maximise negative skewness). As increased leverage does not come at a commensurately increased cost due to deposit insurance, negative skewness can be maximised without compromising on the expected return [iii].

Akerlof and Romer [iv]pointed out that the evidence on the S&L crisis was consistent not with increased risk-taking but with “looting” i.e. fraud. In their words,

“many economists still seem not to understand that a combination of circumstances in the 1980s made it very easy to loot a financial institution with little risk of prosecution. Once this is clear, it becomes obvious that high-risk strategies that would pay off only in some states of the world were only for the timid. Why abuse the system to pursue a gamble that might pay off when you can exploit a sure thing with little risk of prosecution?”

Fraud represents a negatively skewed payoff provided that there is “little risk of prosecution”. Agents’ preference for negatively skewed payoffs makes fraud an attractive strategy. Any effective fraud-prevention strategy must increase the risk of prosecution to be successful i.e. the negative skewness must be reduced.


The moral hazard explanation also breaks down in cases where the S&L owner was also the CEO and manager of the firm. Quoting from Akerlof and Romer again,

“A crucial change in the regulations in the 1980s made it possible for a single person to own a thrift or for a parent company to own a thrift as a subsidiary. As one would expect, abusive strategies are easier to implement when ownership is concentrated and managers are tightly controlled by owners. In fact, this is why bank regulators had enforced rules prohibiting concentrated ownership until the 1980s. There were other thrifts with widely dispersed ownership and serious divergences between the interests of managers (who wanted to keep their jobs and reputations) and owners (who would have made much more money if the managers had looted their institutions).”

In this respect, S&L owners acted more like managers on high-powered incentive contracts than owners. Their equity investment in the S&L was usually minimal given the high leverage.  The dividend they could extract from the S&L before it went bankrupt could be equated to the bonuses paid to bankers in the current environment. One man ownership may have aligned managerial and owner interests in a normal firm but in an insolvent S&L with access to insured funds, it was an open invitation to engage in fraud.  As William Black noted,

“The leading law-and-economics text asserts that this is the ideal structure because it ensures managers’ fidelity to shareholders’ interests. This is one of  the areas where the field’s lack of knowledge of fraud has embarrassed it, for William Crawford had it exactly right: the best way to rob a bank is to own it. The person with the greatest incentives to engage in fraud is the CEO owner of a failing firm.”


To summarise, the control fraud theories favoured by William Black and Calavita, Pontell and Tillman[v] are not inconsistent with the moral hazard explanation.  S&L owners were incentivised to take on negatively skewed bets, fraud being one possibility if the possibility of prosecution is minimal. But the pervasiveness of the crisis still needed the fuel of deposit insurance. As Calavita, Pontell and Tillman put it, “selective application of the principles of free enterprise laid the foundation for risk-free fraud” and  “bad men and women took advantage of bad policies”[vi].

The key difference compared to the current crisis is that managers do not need to resort to fraud. More complete markets mean that there is an essentially unlimited supply of extremely negatively skewed bets.



[i] W. K Black, The best way to rob a bank is to own one: how corporate executives and politicians looted the S&L industry (Univ of Texas Pr, 2005).

[ii] R. C Merton, “An application of modern option pricing theory,” Journal of Banking and finance 1 (1977): 3–11.

[iii] subject to regulatory capital requirements.

[iv] G. A. Akerlof et al., “Looting: The economic underworld of bankruptcy for profit,” Brookings Papers on Economic Activity (1993): 1-73.

[v] K. Calavita, H. N Pontell, and R. Tillman, Big money crime: Fraud and politics in the savings and loan crisis (Univ of California Pr, 1999)

[vi] Ibid., p. 11,19

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Written by Ashwin Parameswaran

December 1st, 2009 at 4:56 pm

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