JP Morgan and Market Complexity

by James Bushnell Originally appearing in Energy Economics Exchange (UC Berkeley Haas School of Business) I’ve actually started to write this blog post several times over the last 9 months, but other things come up and I put it on the shelf. Fortunately (or not) the JP Morgan power trading story just keeps coming back , .. and back , so I keep having opportunities to finish this blog. For those not following this story, Morgan has recently settled charges with FERC that its “ creative ” bidding practices represented market abuse (or manipulation) for just over $400 million. News of these kinds of abuses, whether legal or not, always brings on search for a deeper meaning in the direction of the electricity industry. Usually this debate centers upon whether we should have deregulated power generation or not. That is a very complex question that is important, but I don’t think the Morgan story adds much weight on one side of that or the other. Even if the industry went back to the organization of the 1980s, there would still be lots of non-utility generation, and undoubtedly lots of power trading. Utilities, even regulated ones, still need to buy their power from somewhere and as they figured out about 30 years ago it usually doesn’t make sense for them to generate it all themselves. Indeed, within the Midwest ISO footprint, one of the playgrounds for Morgan’s shenanigans, there are many old-style vertically integrated utilities co-existing with other forms of ownership. What the Morgan story may say something about is the trend in US markets for increasingly complex price-setting processes. For example, the California market today is way more complex than the one Enron made infamous 12 years ago. Back then, the California power exchange took bids for price and quantity, but not much else. Today, an offer to sell power from a generation unit can contain all sorts of parameters describing what the plant can and cannot do, from the “ramp rates” to a minimum running time. All these parameters are fed into optimization routines such as mixed integer programs in which the system operator theoretically finds the “best” solution for everyone, taking all these operating constraints as given. The problem is, the “best” solution when everyone is telling the truth about their costs and capabilities can be very different than the solution when firms are strategically bidding those parameters. One aspect of this is the concept of “make-whole” payments. These are intended as a means to compensate inflexible units who may get stuck in the wrong position in order to help the market in small number of hours – like a plant that gets switched on to help meet demand in one hour but can’t be (or says it can’t be) turned off very quickly. Because it is not flexible, that plant may end up still operating (at a loss) even after the price crashes back down again. Make-whole payments are supposed to allow plants to recover these costs if market revenues are not sufficient, to avoid discouraging them from participating during the hours when they are really needed. But as the Morgan case has demonstrated, there are lots of ways strategic firms can twist the good intentions of a market operator. By overstating their costs, or their inflexibility, while at the same time “forcing” themselves into the market through low energy price bids or simply running the plant in a way the operator doesn’t expect, plants can grab lots of revenues from these payments. How did we get here? Unlike say, complex financial securities, these rules are not the concoction of investment bankers with physics training. In other words, the traders themselves did not take the lead on these designs – although they certainly put in their opinions. This is largely the work of engineers working with the market operators themselves. There was a very legitimate debate about 10 years ago about the pricing of transmission congestion. This was one of the simplifications of early electricity markets. It has been pretty widely acknowledged now that market prices needed to better reflect congestion caused by usage of a network. This is a classic “externality” (congestion imposed on other users) that was not being properly reflected by the old market rules. Fine. We fixed that. However, at the same time all sorts of smart computer scientists, electrical engineers, and operations researchers went a little crazy trying to solve every other complexity involved in generating electricity. Plants can’t just ramp up and down instantly. They can’t shut down and start up again right away. Working these kinds of costs into the pricing would lead to more “feasible” solutions that better reflect reality. The problem with this logic is that these costs, unlike transmission congestion, are all “internal” to the owners of a plant. The fact that a price solution coming out of a computer program didn’t explicitly model them didn’t mean mean that the costs were not represented in the prices. Its just that they were the problem of the plant owners, who had to figure out how to best operate their plants to meet the sales orders being produced by the market. It’s worth pointing out that, while making electricity is complicated, and marginal costs don’t look like a nice upward sloping line, this is true of a lot of other stuff also. Refining gasoline is complicated. Running an airline network is complicated. But we don’t run a single optimization program that simultaneously tries to clear the market and solve everyone’s production schedule for them. These markets run the way power markets used to. If a generator got a sale it couldn’t meet, it bought replacement power out of a spot market. If a plant ended up running in a way that lost money over the course of a day, it would change its offer price the next day so that didn’t happen again. The market software does wondrous things, and solves tremendously complicated problems. It’s probably true that having a group of plant owners try to manage these complexities in a decentralized way creates some inefficiencies. But its still garbage in – garbage out. If firms monkey with the complicated parameters that these programs are trying to accommodate, strange things can happen to prices, and especially to the types of side-payments earned by JP Morgan. The “best” solution is not always the most complicated one.

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JP Morgan and Market Complexity

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