This Is the End


Markets, Risk and Human Interaction

October 23, 2009

Why Do Bankers Make So Much Money?

October 23, 2009
A tenet of economics is that in competitive markets there are no economic rents. That is, people get fairly paid for their efforts, their capital input, and for bearing risk. They are not paid any more than is necessary as an incentive for production. In trying to understand the reason for the huge pay scale within the finance industry, we can either try to justify the pay level as being a fair one in terms of the competitive market place, or ask in what ways the financial industry deviates from the competitive economic model in order to allow economic rents.
Do the banks operate in a competitive market?
No one expects competitive levels of compensation when there are deviations from a competitive market. In what ways might the banks – and here I mean the largest banks and those banks that morphed over the past year from being investment banks – fall away from the model of pure competition?
One way is through creating inefficiencies to keep competitive forces at bay. Banks can do this, for example, by constructing informational asymmetries between themselves and their clients. This gets into those pages of small print that you see in various investment and loan contracts. What we might call gotcha clauses and what the banks call revenue enhancers. And it also gets into the use of complex derivatives and other “innovative products” that are hard for the clients to understand, much less price.
Another way is to misprice risk and push it into other parts of the economy. The fair economic payoff increases with the amount of risk taken. If a bank takes on more risk it should get a higher expected payoff. If the bank can get paid as if it is taking on risk while actually pushing the risk onto someone else, then it will start to pull in economic rents. The use of innovative products comes up again in this context. They provide a vehicle for the banks to push risk to others at a less than fair price. Or, they can push the risk onto the taxpayers by hiding the risk and then invoking the too-big-to-fail protections when it comes to be realized. The current “heads I win, tails you lose” debate centers precisely on this point.
A third, and most obvious reason banks might not be economically competitive entities is the organization of the industry. There are barriers to entry. No one can just decide to set up a major bank. And there are constraint in the amount of business any one bank can do. As we have seen with Citigroup, there finally are diseconomies of scale – after a point the communication and management issues make the bank less efficient and more prone to crisis. If there is fixed supply, then the banks can push up the price of their services. The crisis over this past year has made matters worse. If you are one of those still standing, you are a beneficiary of that crisis, which has choked off the supply even further.
Are the workers getting paid fairly for their efforts?
An alternative to the idea that the industry is not competitive is that the industry really is competitive and those who are getting these outsized paychecks are being fairly compensated for their efforts. This comes back to the term we hear bandied about in conversations on banker compensation: talent.
There is no denying there are many smart people in the banking industry. (Though I think from a social welfare standpoint, we might have done better if some of those physicist and mathematicians that populate the ranks of the banks had found greener pastures in, say, the biological sciences). But I don’t buy the notion that there are so many who have the level of talent that justifies tens and even hundreds of million in compensation. I think this level of compensation, and the notion of talent behind it, is the result of the inherent uncertainty in the financial enterprise, one that makes it very difficult to assess talent. Indeed, I think the invocations of talent for money producers in finance are akin to those that, in times past, were set aside for the mystical powers of saints and witches.
Far more than other fields of endeavor, it is difficult in finance to tell if someone is good or lucky. A top trader or hedge fund manager might have a Sharpe Ratio of 1.0 or 2.0. But that Sharpe Ratio is nothing less that a statement that if you get a hundred people trading, a few will do well just by luck. (And it doesn’t matter if that Sharpe Ratio occurred over the period of one year or twenty – though the greater sample size helps, it is still the same point in terms of statistical inference, so a long track record does not get you away from this problem).
How does this tie in with saints and witches? People want certainty, and if they can’t get the certainty they want from the empirical, they fall back on superstition and witchcraft, or at least they used to way back when. In some medieval village, a priest prayed and a supplicant was healed. The odds that the supplicant would have healed spontaneously was whatever it was, but there was more of a sense of certainty to feel that it was the manifestation of healing power.
There were false saints and true saints. The difference between them became manifest over time by how frequently the prayers were answered with affirmative results. Not that any saint had to bat a thousand. Sometimes there were understandable, exogenous circumstances that inhibited the saint’s healing talents from being operative, most commonly a lack of righteousness on the part of the supplicant, occasionally an inevitability, a higher power that overshadowed that of the saint. Maybe the will of God, maybe an unknown, evil curse.
I hope the analogy is apparent. And there is a related one, an analogy to Pascal's Wager. The bank should wager that the talent of its star employee exists, because it has much to gain over time if it does, while if it does not exist, the bank will lose little in expected terms. And in a competitive world, it is even worse if they incorrectly let the talent go for lack of proper compensation, because then some competitor will pick it up.

October 11, 2009

We Need Open Derivative Models

October 11, 2009
Before I knew anything about the finance industry, if someone had thrown out the name “Blackrock” I would have conjured up a scene from the Wild West, a cattle rancher hiring a gunslinger to roust out the sheep farmers and take control of the town. But now, of course, I know that BlackRock is a financial behemoth with $1.5 trillion in assets under management -- soon to be over $2 trillion due to its purchase of Barclay’s asset management business. But of more note than its asset footprint is the mantle BlackRock is gradually assuming as the arbiter of value.

BlackRock won a set of contracts to provide analytics for the New York Fed’s trillion dollar mortgage-backed purchase program. Now, BlackRock may end up with an NAIC contract to analyze the mortgage-backed securities in insurers’ portfolios.

I do not mean to diminish BlackRock’s laudable role in assisting in many ways with the financial crisis – coming forward when a number of other large firms demurred. But as one contract is piled on another, their models will become the standard for pricing mortgages, complex derivatives and structured products. Unlike the money management business, which is competitive and relatively transparent, this is a monopoly ready for the making. A monopoly because the more institutions, industry associations and regulatory bodies that employ their services, the more they become the de facto standard. Over time, auditors, clients and equity holders – perhaps even regulators – will start saying, “Well, it is nice to see what your internal models have to say about your portfolio value, but we want your portfolio benchmarked using the BlackRock model.” A BlackRock seal of approval; BlackRock, the JD Powers of portfolio quality.

Here are the problems with this:

First, of course, is the well-known issue of allowing a private enterprise to have monopoly control of a utility – in this case a de facto replacement of the rating agencies (not a bad thing in itself) by putting one firm in the position of providing the benchmark pricing of financial products. Second, there are natural conflicts of interest given that BlackRock is also the asset manager for the New York Fed’s Maiden Lane portfolios and has raised over half a billion in private capital to purchase legacy securities as part of PPIP. (Though I should add that BlackRock is aware of this issue and has stated the firm has strict internal controls preventing any valuation services from being gamed by its investment arm. Which should make us all feel a lot better).

But the most critical problem is that its approach is at variance with the broadly held view that we need to have transparency in the derivatives markets because, unlike, say, RiskMetrics, BlackRock does not share the specifications of the models it employs. We don’t really know what these models are doing. Valuations based on a black-box BlackRock model, or, for that matter, anyone else’s black box model, do not get us the transparency we need. I don’t care what a trading desk uses for its decision making, but when it comes to valuations that carry beyond the firm, we need to be able to see and critique the models that are being used. If a model is to become a standard, if it is going to be used for regulatory or other benchmarking purposes, it should be transparent and subject to peer review.

Which gets to a simple point: If we want to go down the path of standardized valuation and comparability in these complex portfolios, we need open derivatives models. One thing we should have learned from the rating agency debacle is that even if we put aside the issues of monopoly power and conflict of interest, we cannot stop with having the proprietor of such models say, “Trust me, I know what I’m doing.”