The JP Morgan Caper

by Jerry O’Driscoll   

J.P. Morgan Chase & Co., one of the nation’s leading banks, revealed that a London trader racked up trading losses reportedly amounting to $2.3 billion over a 15-day period. The losses averaged over $150 million per day, sometimes hitting $200 million daily. The bank states the trades were done to hedge existing risks.

How did this happen and what are the lessons? The two questions are related.

It appears the individual traded on the basis of observed relationships among various derivative indices. The relationships broke down. Such a breakdown has been at the heart of a number of spectacular financial collapses, notably that of Long-Term Capital Management in 1998 and a number during the financial meltdown of 2007-08.

In short, there is nothing new in what happened. Yet financial institutions permit their traders to make the same kind of dangerous bets. In a Cato Policy Analysis, Kevin Dowd and three co-authors examined some of the technical problems with standard risk models utilized by banks.  It is an exhaustive analysis and I commend it to those interested. The analysis goes to the question of how these losses happened.

Now to the lessons.

Major financial institutions continue to take on large risks. Why? The trades made by Morgan ostensibly were to hedge the bank’s exposure to events in Europe. That implies, of course, that risky investments had already been put in place (since they then needed to be hedged). Additionally, the risks were so complex that even a highly skilled staff (which Morgan certainly employs) could not successfully execute hedges on them.


If ordinary market forces were at work, these institutions would shrink to a size and level of complexity that is manageable. Ordinary market forces are not at work, however. As discussed on this site before, public policy rewards size (and the complexity that accompanies it). Major financial institutions know from experience they will be bailed out when they incur losses that threaten their surivival. Morgan’s losses do not appear to fall into that category, but they illustrate how bad incentives lead to bad outcomes.

Large financial institutions will continue taking on excessive risks so long as they know they can off-load the losses on taxpayers if needed. That is the policy summarized as “too big to fail.” Banks may be too big and complex to close immediately, but no institution is too big to fail. Failure means the stockholders and possibly the bondholders are wiped out. Until that discipline is reintroduced (having once existed), there will be more big financial bets going bad at these banks.

Changing the bailout policy will not be easy because of the time inconsistency problem. Having bailed out so many companies so many times, the federal government cannot credibly commit in advance not to do so in the future. (Think of Lehman.)

What to do in the meantime? The Volcker Rule was a modest attempt to rein-in risk taking. Industry lobbying has hopelessly complicated the rule and delayed its issuance. Morgan’s CEO, James Dimon, asserted the London trades would not have violated the rule. If true, it suggests to me that an even stronger rule needs to be in place.  Various suggestions have been made to address excessive risk taking by financial firms. It is time to take them more seriously.


14 thoughts on “The JP Morgan Caper

  1. Credibility was lost when bailouts occurred. Credibility will be restored when a couple of big banks are allowed to fail and are not bailed out. Ironically, credibility is undermined by continuing interventions like the Volcker Rule which indicate that the pols are not ready to let go.

  2. Jerry O’Driscoll–
    Re “Various suggestions have been made to address excessive risk taking by financial firms.”
    The only reason this trade appears to be “excessive risk taking” is that it went wrong. Before the event there was no way to know that. It is only ex post that the risk looks bad.

  3. @Chidem,

    As I made clear, the trades needed to be made to hedge risks already on the books. So, senior management came to the realization that they had taken on excessive risk.

    Further, as I stated in my post, the trades failed for reasons similar trades have failed in the past (e.g., LTCM). They assume a stability of relationships that cannot be relied on. One facet of the problem, emphasized in the Kevin Dowd, et al., Policy Analysis is that the VAR models are flawed and systematically underestimate risk.

    Why the systematic inattention to risk?

  4. There’s an old “can’t lose” betting algorithm. You bet $1 on the toss of a coin. If heads, you win $1 and you’re done. If you lose you bet $2 on the next toss, and if you win you’ve recovered the $1 you lost and won $1, and you’re done. If you lose you double up, and you keep doubly up until you get a heads, when you will recover your losses and win $1.

    The “law of averages” says you are certain to get a heads eventually, so you can’t lose.

    Is that right?

    Isn’t that what these “hedging” bets are doing?

    Except that the algorithm isn’t “can’t lose”. Occasionally you would end up betting $1M on the chance of winning a net $1, and something will prevent you doing it. (Your bank, your boss, common sense?…). It isn’t eliminating or hedging ANY risk. It’s just trading a small frequent loss and for a rare enormous loss.

    Isn’t that what these ‘hedging” bets are doing. The idea that they are “hedging” or in any way reducing risk is fraudulent. They are “hiding” the risk, not hedging it.

  5. As rules are imposed, and “protected” entities grow larger and larger, eventually the “protecting” entity itself (here, the government) comes to be at risk, as it already has in this case.

    When THAT fails (and it will), matters will shrink – with catastrophic speed – down to a microscopic manageable size. Lethal gunfights over a can of beans will routinely claim dozens of victims.

    But it WILL be manageable, to those with the most ammunition – and luck.

  6. Maybe the risk management would be safer with a different technique or a nicer distribution or with fractals… maybe it’s just that you can’t quite know the future precisely enough to hedge against such complex scenarios.

  7. So much for mathematical modeling of human behavior. An expensive lesson they could have learned from the Austrians for free.

  8. Gerry,
    I question whether your policy advice – “that an even stronger rule needs to be in place” – follows so neatly from the J.P. Morgan matter. Part of the problem is that such rules as exist regarding proprietary trading add further layers of complexity without addressing the question of moral hazard and TBTF. In the regulartory system in place and the still unsettled regulations coming out Dodd-Frank, we should expect excessive risk-taking and retardation in adaption by financial institutions. Expanding the scope and severity of rules seems a path strewn with lots of pitfalls and unintended consequences.

    And what kind of rule would you suggest?

  9. It is very diificult to come up with second-best policies to address the moral hazard generated by bank bailout policies. But I see zero chance of ending them in the near future.

    Paul Volcker started with a simple point. There is no earthly justification for banks with FDIC-insured deposits to engage in trading securities for their own account. That is an inherently risky activity wth no connection to traditional banking. While, in theory, it could be safely conducted, it is the heart of what I’ve called casino banking.

    I’ve written more ont his topic since this posting and it will be forthcoming. In the meantime, I again recommend the Dowd piece, which details why banks trading activities are so problematic.

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