
Chapter 8: Weather Risk Management | Data for Science and Society: The Second National Conference on Scientific and Technical Data | U.S. National Committee for CODATA | National Research Council

U.S. National Committee for CODATA
National Research Council
Interdisciplinary and Intersectoral Data Applications: A Focus on Environmental Observations


Weather Risk Management

Lynda Clemmons

     I am going to expand on a lot of things that Dr. Baker and Tom Karl talked about this morning as well as what Brad Leach talked about. The Weather Risk Management Association was formed last year to provide a resource for those who are impacted by the weather. We have heard various statistics bandied about. Certainly the one commented on most frequently is by Commerce Secretary Daley. He said that at least $1 trillion of the U.S. economy is impacted by the weather in some form or fashion. When you hear about Tom Karl's dollar signs as an inducement to get into a certain type of industry, $1 trillion is certainly a draw.

     Some of the earlier speakers talked about the financial weather business in bits and pieces, but they haven't really told you what it is. What we are trying to provide as an industry is financial protection from the vagaries of the weather. Whether you know exactly what the weather is going to be or not doesn't mean that you actually can influence what your remedies might be and what your expenses might be relative to that weather. There are products on the NYMEX that are an excellent source of price hedging, but are missing the volumetric component. If you are talking to people who sell weather-affected products or have product consumption that is directly related to weather, they cannot use NYMEX for a complete hedge. You have price volume revenues--all of these things being put together so that the ultimate combination for a hedge on weather or a hedge on costs is a combination of the weather product and the price product.

     I will give you a quick description of the evolution of the weather market and an update on some of the problem numbers. The first weather-indexed commodity transaction happened only 2 _ years ago. So if you don't know a lot about this marketplace, you are not really far behind. It is something that has really picked up steam very quickly. We went from one transaction in August 1997 to more than 3000 transactions as of December 1999, with one estimate that these transactions covered about $5 billion worth of risks.

     The old mindset was that an electric company, or some other entity dependent on cold weather for the winter, relied on forecasts to make sure it would get the sales of natural gas and electricity needed to meet its budget. This is especially important in a newly deregulated economy where companies are going to fight for every British Thermal Unit that possibly can be sold through their system. In order to do this, companies felt they really needed the weather to help them out.

     We have gone from this kind of mindset to something a little more complicated. For example, let's say I am an electricity trader in the southwest part of the United States, and I am interested in providing electricity to my customers. I am concerned when it is 105 degrees outside in Palo Verde, but I am only concerned about this when the price of power is spiking above $2000 per megawatt. When my customers call on that power if it is 105 degrees, I can usually supply as much as I need except when the price goes from $24 per megawatt-hour up to $1000 or $2000 per megawatt-hour. So I want to look at these sorts of products as a dual-trigger option, if you will. I want the sorts of products where we will say, "I need that call on electricity from a price perspective, but I only need that call on electricity when the temperature is soaring." That is, the temperature has to be above 100 or 105 degrees or whatever it might be that will cause your customers to start calling on an excessive amount of product from you. So by having two relatively independent triggers, you should get a less pricey product. Even though we are going to see strong correlations between energy prices and the weather, all sorts of things can happen that will make prices spike--system outages, airplanes flying into wires--things that you will pay for if you are buying a call option on energy prices alone, but that you may be able to mitigate when you say, "I only want that price protection if it is accompanied by a similar weather event."

Figure 8.1


     Figure 8.1 gives you an idea of how the financial weather market is structured. There are the end users. There is also the capital market, which is a little bit different because of the history of catastrophic weather markets, the tradition that we have of hurricane insurance, flood insurance, and the like. It seems a natural progression for a lot of the insurance companies that are starting to take a stronger look at financial products. They are looking at what weather-risk management really means, even though it is a very simple concept to think about. What you are really buying is insurance against this winter being 10 percent warmer than normal or 5 percent colder than normal. Conceptually, you know this is insurance, but to an insurance company it is a very different risk profile. These companies typically have been looking at something that happens once in a 100 years, and they are going to sell you insurance based on that once in 100-year event. We are looking at something now that happens 3 years in a row, or historically perhaps once every 4 years. This is a very different risk profile for an insurance company to try to accommodate and to try to figure out how it is going to charge you for this. What is the right risk premium associated with it? Insurance companies are learning a lot from the derivative markets about these types of risks.

     I will give you an idea of the various structures associated with financial weather markets (see Figure 8.2). The contracts are typically what you would see if you took the interest rate markets and laid them on top of the weather markets, including options, calls, and exotics. We are seeing mainly seasonal, multiyear transactions, although as the market gets more developed it is evolving to a month-by-month type of scenario, even a week-by-week scenario. Historically, forecasts had very little impact on this particular market because next week's or next month's forecast would not mean a whole lot to you if you were trading and you had positions based on next winter or the following summer. Now that these time frames are beginning to be compressed, forecasters are starting to play a bigger and bigger part. Size of transactions is actually where you take value; DD is based on degree days. One of the largest transactions we have seen involved a major utility company that said, "Every time there is a shift by 1 degree-day over the wintertime, I am affected by $500,000." Now, over the course of a 180-day winter season that may be a significant chunk of change.

Figure 8.2


     We are taking a look at all locations, domestic and international, using baskets of cities, not just individual cities. People are looking for geographical representation, not just a single location. A company might want to bring in two or three cities and try to triangulate the exposure as well. Let us think of a propane company that is hoping to make a profit by acquisition. This acquisition is going to pay off for the company if it is a very cold winter. If the winter is warm and its trucks don't have to swing around to your house and top off your tanks, the acquisition may not be such a prudent idea. Banks are now looking to provide loans to these companies where the interest rate fluctuates with winter temperatures so that if it is cold and they are actually going to be able to pay down their cost of debt because their revenues are going up, then the interest rate may go up, but if it is warm and they are going to be strapped for cash, the interest rate can go down.

     There is a set of common indices that are monitored as well (see Figure 8.3). With regard to that $5 billion worth of risk that we talked about already, most of this takes place in terms of degree-days or in terms of temperature. A lot of it, however, is increasing in rainfall and in snowfall products. With rainfall and snowfall indices, there are clearly some measurement issues with certain indicators and with some historical information. Tom Karl spoke about these issues, which we are going to have to rectify and get our arms around. I certainly appreciated Barbara Ryan's comments this morning, given that we have looked at a number of stream-flow transactions with regard to some of the major hydroelectric producers in the Pacific Northwest and other places. We also look at things such as storm activity for folks who are doing seismic graphing of suboceanic surfaces. When storms come in, the crews are going to have to pull up their lines, vacate, and go to a different spot. Do you really want the captain of a ship to have to decide between the economic viability of a project and the lives of the crew members? The world of competition is such today that this is becoming more and more commonplace. Various companies are looking for ways to make sure they have the economic hedge in place, and the only thing the captain has to worry about is maintaining the safety of his crewmembers.

Figure 8.3


     Perceived temperature, wind chill, and heat are other indices. You may have read about Coca-Cola potentially indexing the price on sodas in its machines to the outside temperature and/or humidity. This was a bit of a public relations gaffe. The company understands that the correlation certainly does exist. If you talk to sports drink manufacturers, they know that a sugar-water combination of those electrolytes is really going to build you up, and you want them more when it is humid outside as opposed to just hot. These are things that their sales results have shown, and they are trying to build on this correlation.

     Now, to come by all this anecdotal evidence, we have to make sure that you have the right data sources. We wrote to the National Climatic Data Center (NCDC) and the National Weather Service (NWS), and they have been terrific in providing data and resources. The United Kingdom's Met Office, as we have found, is changing its tune in terms of response to the marketplace. I met with a representative from the Met Office about 20 months ago, with my traditional bull-in-a-china-shop methodology and asked why the office wouldn't lower its prices regarding historical weather data and ongoing weather data. I was told that it needed to make money. The Met Office is charged with making money because the government doesn't fund it sufficiently. It has to go out to the private sector. I asked how much money was made selling these data, and it was about $2 million a year. So I asked, "What if you didn't have to do anything to make that $2 million a year? I will write you a check for $2 million. You give me access to all the data and the right to do with them what I want. The first thing I would do is I would cut the price down by about 90 percent, and I would make these data accessible to everyone. I would put them on the Internet. So, if you want your $2 million you can have that steady cash flow. I will send it to you every year. We will account for inflationary increases, and you don't have to do anything for the funding, but I want the right to go out and market those data and make what I know I can make from them by making them more accessible to other people." Somehow that struck the Met Office as wrong. Consequently we have seen a decline in pricing from the Met Office. We have seen increased accessibility to the point where the Met Office is now actually offering to be the conduit for European weather data.

     Other data sources include Environment Canada and Météo-France, who we use a little bit to leverage the Met Office into the position it is in now by saying, "Hey, we can get your data from MINITEL for around 20 p a minute," or something like that. The Spanish Met bends over backwards to tell you it will get you everything but rarely actually gets the information to you. The Germans, through Deutscher Wetterdienst, will get you information but it is riddled with holes.

     In comparing European and U.S. data, clearly the United States comes out on top in this (see Figure 8.4). The only concern we have about U.S. data really is the timeliness. Within each weather contract right now is built in a 95-day "true-up" period. This means that I will be entering into a contract with someone. Payments come up at the end of the winter, so effectively if I owe someone money I am going to make a check out to them by April 5, and 95 days later we are going to go back to the NCDC and we are going to see what changed. Historically we haven't seen a lot of change, but the fact that you have to have the added mechanism in 95 days can be a bit of a bear for the administrative process, as well as for those trying to put together a futures contract that will provide you with a hedge relative to your exposure in the market.

Figure 8.4


     I should mention that we also have seen the Japanese markets becoming very interested. They already have had a couple of transactions performed in Japan, and the Japanese have been very open with their data, happy to supply them; the same is true with the Australians. I think we will be seeing more and more transactions coming along in the Pacific.

     What are the biggest problems with regard to weather data? There are still a lot of missing data, not so much with the United States but with other countries. We have inconsistency between data from regional data centers and NCDC products. For example, if we are missing something from the NWS or the NCDC, then we have to have backup. Normally we come in at 4 or 5 in the morning to run this through the Internet, pick up all the data we need, and drop them into our spreadsheet. If these data are missing, if the computer is unavailable because of a fire in the computer room or whatever might have happened, then we go to the regional climate centers. Oftentimes we find that the data we plugged in from the regional climate center are inconsistent with what we are getting from the NCDC. So these are some issues that we have to resolve because they result in data arguments in the following weeks. Another issue is simply ease of use. We have to get all of this into standard markup language so that everyone can read the data and so that they can be transferred between one unit and another without having to write a different program for every single source that you are looking at.

     So at the end of the day, the industry needs are accurate, dependable, easily accessible, and affordable data and real-time data access. How many times have we heard that already this morning? Then, we need the ability to shorten up the verification period, take that from 95 days to hopefully something considerably less.

     Thank you for your time today.

Copyright 2001 the National Academy of Sciences