From hiring to product pricing, businesses make countless decisions that affect their performance. Yet there’s one very important factor that they can’t control - the weather.

Certainly, farmers depend on Mother Nature to make a profit. But so too does an electric utility that faces an unusually mild summer or a city government that has to pay an unprecedented snow removal bill.

Until fairly recently, there was little that individual companies or government bodies could do to reduce their exposure to such risk. They could take out insurance policies against inclement weather, but these usually only kick in during relatively infrequent, catastrophic events. What the market didn’t have was a way to hedge against smaller fluctuations.

That all changed when the first weather derivative was traded over-the-counter in 1997. Such contracts - consisting of futures as well as options based on those futures - provide businesses with a safety net in case seasonal climate conditions adversely affect their operations.

It didn’t take long for the market to respond in a big way. In 1999, the Chicago Mercantile Exchange (CME) began listing weather-related products, providing a more fluid market for such transactions. Today, several billion dollars of these derivatives are traded each and every year, both over-the-counter and on through the exchange. They’ve become a crucial risk management tool for energy companies, insurance firms, governments and even pension funds.

Deconstructing a Derivative

The market offers derivatives that cover a whole range of factors, from snowfall and frost to rain and hurricanes. And through CME, parties can buy or sell contracts of varying duration - weekly, monthly or seasonal - for dozens of cities around the world.

To understand how a weather derivative works, let’s look at one of the most common types: temperature-based contracts. What these futures and options do is enable the buyer with a “long” position to benefit if the weather is more extreme than normal. So how do traders measure that, exactly? In this case, it comes down to the number of heating degree days (HDD) or cooling degree days (CDD) over a given time period.

A heating degree day is the difference between the average daily temperature and a base temperature - usually 65 degrees Fahrenheit (18 degrees Celsius). If the average temperature for January 15 is 25 degrees in a particular city, it’s using 40 heating degree days. The figure is important because it serves as a proxy for how much energy is needed to heat homes, offices and other properties. By extension, the HDD level for all of January is the sum of heating days within the month.

As one might expect, a cooling degree day is just the opposite. If the average temperature at a location is 85 degrees on July 6, it represents 20 cooling days (85 degrees – 65 degree base temperature). However, in Europe and Asian cities, CME uses the Cumulative Average Temperature (CAT) rather than cooling days for the summer months.

The strike price, therefore, is a specific number of heating or cooling degree days in a particular city. CME lists contracts for 24 metropolitan areas in the U.S., as well as numerous cities in Canada, Europe, Japan and Australia. If the number of heating or cooling days surpasses the strike price, the owner of a call option receives a cash payout.

Figure 1

A table showing heating degree day futures contracts listed on the Chicago Mercantile Exchange.



Source: First Enercast Financial

Calculating Payouts

Determining the potential payout of a derivative is fairly straightforward. Each temperature-based contract has a specific dollar amount per HDD or CDD (if it’s a rain derivative, the dollar amount correlates to each inch of precipitation). Simply multiply this number by the number of heating or cooling days in excess of the strike price.

Payout (call option) = Dollars per unit * [HDD or CDD value - strike price]

As an example, let’s look at Millview University, a fictitious institution just outside of Chicago. Each year, the school has to pay utility bills for dozens of buildings on its campus. So to safeguard against an unusually harsh winter, it buys a HDD call option for the month of January.

The contract has a strike price of 600 heating days, but Chicago ends up experiencing 750 because of a particularly fierce cold snap. With the unit amount of $500 acting as the multiplier, Millview ends up getting $75,000, less the amount of its premium.

Payout = $500 * (750 – 600) = $75,000

Of course, there’s a risk for those taking a long position on these derivatives. If the payout is zero or doesn’t cover the full cost of the premium, the party incurs a loss. In this sense, it’s no different than taking out an insurance policy. You won’t necessarily come out ahead, but you’re glad it’s there if you really need it.

For every long position on an option, there’s always a party betting against adverse weather by writing (selling) a call or buying a put contract. In some cases, these are entities that want a hedge, not against severe weather, but rather against mild conditions. A heating oil retailer, for instance, makes less money if winter isn’t particularly chilly. If may decide to purchase a HDD put, which pays out if the number of heating days is below the strike price.

Alternatively, those “shorting” the weather could be speculators who think the rest of the market is biased toward severe weather. If they sell a call option that’s never triggered, they pocket the premium.

The Challenge Of Valuation

With most derivatives, the underlying asset, whether it’s a stock or a bushel of corn, is tradable. And because the value of the asset is known, it’s relatively easy to put a price tag on futures and options contracts. But nobody sells warm temperatures or rainfall, so placing bets on the weather is murkier terrain.

Before deciding if a derivative makes sense, a business has to figure out two primary questions. The first is what weather outcomes they should expect for, say, rain or cooling degree days. It might seem fairly easy to come up with an average using historical data, but even this gets tricky. For example, is a 30-year index of CDD values a good predictor of the upcoming summer, or is shorter-term data a better gauge?

In addition, the organization has to figure out what impact a particular weather outcome will have on its financial performance. Therefore, the most successful market participants are those that manage to build statistical models that answer these questions accurately. Large energy companies, for example, may have analysts on staff or hire outside firms to help value contracts appropriately.

Figure 2

The following chart shows a simple pricing model for a put option based on cooling degree days (shown on horizontal axis). If the number of cooling degrees surpasses the strike value, the owner may not be able to recoup the amount of the premium.



The Bottom Line

To date, energy-related businesses and insurance firms have been the dominant players in the weather derivatives market. However, there are signs that such contracts will continue to grow among other industries affected by climate, from tourism and restaurants to agricultural firms. By using derivatives strategically, such businesses can ensure that an unusual bout of weather doesn’t translate into major losses.


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