Energy & Energy Derivatives & Energy Risk Management  Last revised: March 02, 2002

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Basis Risk in the Petroleum Market (7/28/00)

Dear Dr Risk i´m having trouble building the forward curve for fuel oil singapure 380 and rotterdam 3,5%. The first problem is that this information is not available anywhere but asking the banks for it ... can i imply the forward curve from the WTI futures/NYMEX or the brent futures from IPE? how can I estimate the correlation betwen the crude and the bunker and may I supose the term structure is similar to the fuel oil? as I read the other day .. energy derivatives is the Wild west of derivatives :) Andre

Dear Andre Dr. Risk's first impulse is always to ask why you want to do this in your case, build those forward curves. The reason can shape the choice of method and data. It could even lead to dropping the whole exercise. It's happened before. How do you want to use those forward curves? How finely granular does this curve have to be?

Dr. Risk was tempted to take your word about the problems with getting forward price data for those high sulfur fuel oils, Singapore 380 CST and Rotterdam 3.5% S. While those grades are not among the more esoteric, building a forward curve in energy products is typically a challenge, except maybe in a few contracts with relatively active exchange-traded futures contracts, such as WTI or Brent. 

However, Dr. Risk thought that the Singapore Monetary Exchange might have a Singapore 380 CST contract. A visit to shows clearly only a Brent crude futures contract. Strangely, other sources namely, Derivatives Strategy & Tactics from a few years back, and state clearly that SIMEX has a High Sulfur Fuel Oil futures contract. Apparently, that contract has gone off to contract heaven.  Dr. Risk has not fully resolved this point at publication time.

The swap prices at "BunkerWorld" take you part of the way to the forward curve you want. Peter Crumbine of Sempra Energy Trading Inc. explains that the prices on this page show "the forward market offers as reported by Sempra Energy Trading. In other words, they are an indication of the prices at which you can fix future bunker costs." "Six months" ("One year") indicates the swap price for the period that includes the next six (twelve) full months. As of the middle of August 2000, that would be Sep 00 - Feb 01 (Sep 00 - Aug 01). "Balance 2000" is the swap price for the the remaining full months through 12/31/2000. As of the middle of August 2000, that would be Sep 00 - Dec 00. "Calendar 2001" is the swap price for Jan 01 - Dec 01.

Any model that implies the Singapore 380 CST or Rotterdam 3.5% S forward curve from either the NYMEX's WTI futures curve or the IPE's Brent futures curve is bound to be crude, to put it mildly and without intending the pun. The connection between the two curves is subject to a great deal of basis risk, stemming from location, the difference between the crude and the product (the crack spread), the issue of sulfur content, etc. Dr. Risk doesn't know the purpose to which you wish to put your forward curve, but is not optimistic. 

You can estimate the correlation between bunker and crude by getting some time series data and doing some time series analysis. One thing complicating your analysis is that neither bunker nor crude is a simple time series. Apparently, you want to find the correlation of price changes for corresponding pairs of points on the curve, e.g., one-month, two-month, etc. – Dr. Risk


Building the forward power curve (9/28/99)

Dear Dr Risk – We're big players in the power industry, including hydroelectric. How do you develop a forward price for a commodity like electricity which has no storage capability (so that the usual carryover pricing methodology does not apply), and which has known monthly price patterns, e.g., prices are highest in August and January/February, but high prices (above average) in August does NOT imply high prices in September or October? – Michael

Dear Michael – Excellent question! However, if an easy and satisfactory answer were available, then you wouldn't be writing to me. I'm not a big believer in making a market by using a price from a fundamental theory. The standard approach is to use the market for price discovery. 

1. You have information from only the electricity market.

The first thing to note is that you can't use the theory of cash-and-carry arbitrage to develop a forward price if you don't have the cash price or at least one another forward price. You don't develop the essential cash price or other forward price from some fundamental theory. You simply look it up in the market. Then, in some markets you can compute the rest of the forward curve from it by adding or subtracting the cost of carry. That assumes, of course, that at least one speculator is carrying the inventory. 

The second thing to note is that electricity in August is different from electricity in September. In fact, electricity on 10/8/99 from 1:00 to 2:00 p.m. is different from electricity during any other hour of that day, and the market can make the distinction.  Converting a sizable amount of electricity from one time to another is not practical, ordinarily. Thus, ordinarily,  nobody can or does do cash and carry arbitrage. To price each of these different commodities (power during different months or different hours), you would need a market price for each. It could be today's cash price for a certificate that entitled the owner to electricity in a particular month, or it could be a forward or futures price. It could also be a pair of option prices, because by put-call parity we can design a portfolio containing a long call and a short put to be equivalent to a forward contract. 

If I were you, wanted to know the term structure of forward prices for electricity, and wasn't satisfied with available, public market data, then I might consider auctioning some of the electricity on a regular basis.

2. You can use information from another market.

Suppose that you know the constant that relates cubic feet of natural gas to electricity prices, and suppose that the natural gas market is liquid. Then you might suppose that each electricity forward price is proportional to the corresponding NG price. Some power market makers have used this approach. Of course, since Dr. Risk isn't an electricity specialist, he could only say that the practicality of this method is an empirical question. 

3. You can store electricity

To what degree can you let water pile up behind dams, or let the water level fall to move electricity from one month to the next? If this is a substantial practice, then cash-and-carry arbitrage may hold. – Dr. Risk



"Not the last word in pricing and hedging energy products, but a good place to start the conversation. – Dr. Risk"


Derivatives DictionaryTM  Terms and definitions relating to energy are below. The main Derivatives DictionaryTM is here

Definition: Originally, a coal-bin on a steamship. Later, by analogy, a shipboard fuel tank for marine diesel fuel.
Comment: Some of the Titanic's crew were responsible for shoveling coal in the coal bunker from one side of the ship to the other to maintain it's trim. 
bunker oil
Definition: A residual (q.v.) fuel oil, used for marine diesel engines, power generators, and industrial boilers and furnaces.
Examples: Bunker C, Singapore 380.
Comment: Bunker "C" is the thickest and stickiest of residual fuel oils, black, and looking and smelling like asphalt sealing compound. Lighter  grades of bunker -- Bunker "A" and "B" – were once widely available, but are no longer. 
centistoke (CTS) 
A unit of viscosity, used for defining crude oil grades. 
CIF price
The CIF price includes cost, insurance, and freight charges, whereas the FOB price (q.v.) excludes them. 
crack spread
The price spread between the crude oil price and some specific amount of a product (e.g., gasoline, heating oil, or fuel oil) price. 
The acronym for centistokes (q.v.). 
FOB price
The FOB price excludes cost, insurance, and freight charges, whereas the CIF price (q.v.) includes them. 
8/28/00 Independent System Operator (ISO)
A regional power grid operator.  
8/28/00 ISO
Independent System Operator (q.v.). 
8/28/00 learning on the ties
Unilaterally borrowing from a power grid, ordinarily during a peak period, and repaying later, ordinarily during an off-peak period. The idea is to take expensive power and repay cheap power, making the spread. 
Example: Cinergy did this in July 1999, with no apparent penalty
Source: Rebecca Smith and John J. Fialka, "Electricity Firms Play Many Power Games That Jolt Customers," Wall Street Journal, 8/4/00.
The acronym for the New York Mercantile Exchange. 
Definition: Examining the physical record to gather data on hurricanes that predate the historical record. 
Application: "Combining the data on the past 3,500 years from several of their sites, the investigators conclude that a category 4 or 5 hurricane batters the Gulf Coast every 300 or so years. In other words, there's about a 0.3 percent chance each year that the region will see a storm like the one that razed Galveston in 1900 – or something even stronger."
Source: John Travis, "Hunting Prehistoric Hurricanes; Storm-tossed sand offers a record of ancient cyclones," Science News 157, 5/20/00, p.
What remains from crude oil after removing the more valuable products, such as diesel, gasoline, kerosene, and naphtha. 
sour crude
Definition: Crude oil that has a high sulfur content. The minimum level varies, depending on who's defining, but 2.5% sulfur by weight is high enough by any standard. 
Application: A high sulfur content leads to a high rate of emission of the pollutant, sulfur dioxide. 
spark spread
Definition: A long position in electrical power and short position in fuel (typically natural gas) that simulates the profit from operating a power plant (e.g., a gas turbine generator). The heat rate (q.v.) determines the size of the short position in fuel. 
Example: Long one megawatt of forward power and short 10 million Btus of forward natural gas, indicating a heat rate of 10 MBtu/MwH. If the price of power went from $30 to $33 per MwH and the price of gas from $2.50 to $2.75 per MBtu, then the profit from the position would be $0.50 = $3.00 - 10 x $0.25 per MwH. 
Application: A speculator might want to bet that operating a power plant with a specific heat rate during some period would be more profitable than others anticipate, so he might put on the spark spread in the futures markets. 
Pricing: In the futures markets the initial value of a spark spread is zero, and one's daily profit is the change in the the obvious linear combination of futures prices over the trading day. In the forward markets the value of the spark spread is the present value of the linear combination of current forward prices, minus the present value of the linear combination of the forward prices at the time the trade went on. 
Risk Management: The spark spread could be a tool for managing the risk of owning a power plant. 
spark spread option
Definition: An option on a specific spark spread (q.v.).  
Example: The option to be long one megawatt of power and short 10 million Btus of natural gas, indicating a heat rate of 10 MBtu/MwH. If the price of power were $30 per MwH and the price of gas $2.50 per MBtu, then the profit from the position would be $5 = $30 - 10 x $2.50 per MwH, and the option would be in the money, hence its owner would exercise it. If the price of power were $30 per MwH and the price of natural gas $3.15 per MBtu, then the profit would be -$1.50, and the owner would not exercise it. Analogously the owner of a gas turbine power plant with a heat rate of 10 MBtu/MwH would not exercise it. 
Application: A speculator might want to bet that operating a power plant with a specific heat rate during some period would be profitable, so he might buy the spark spread in the futures markets. 
Pricing: A first pass approximation of the spark spread option would be a Margrabe option or a variant with a nonzero strike. The biggest danger of this is the extraordinarily instability over time of the prices of electrical power and natural gas. 
Risk Management: The spark spread option could be a tool for managing the risk of owning a power plant. 
sweet crude
Definition: Crude oil that has a low sulfur content. The maximum level varies, depending on who's defining, but 0.42% sulfur by weight is the cutoff for the NYMEX Light, Sweet Crude Oil Contract. 
Application: A low sulfur content leads to a low rate of emission of the pollutant, sulfur dioxide.
swing option
Definition: An option that contains an embedded quantity option. 
Example: A call option on electrical power might give the holder the right to buy a total of five or fewer megawatts of power during the 1:00 to 2:00 p.m. time slot on all the days during August 2000. The holder might have to exercise his option in units of one megawatt. Thus, he could buy five megawatts on a day of his choice, one megawatt on any five days  of his choice, etc.
Application: An urban power retailer might anticipate heavy demand during hot weather, because of customers running their air conditioners. So he might buy a swing option to have a market source for power to meet demand. 
Pricing: One way to price this option would be with a recursive binomial tree. A swing option for one megawatt in chunks of one megawatt is simply an American option on one megawatt of power. A swing option on two megawatts in chunks of one megawatt is an American option on (a) one megawatt of power plus (b) an American option on one megawatt of power, etc. This recursive calculation can become extremely time consuming, requiring the use of tricks to get a price within a useful time period. 
Risk Management: The swing option is a tool for managing quantity risk. 
West Texas Intermediate (WTI)
A grade of crude oil that has its main delivery point in Cushing, OK. The spot price for WTI delivered to Cushing is the ultimate settlement price for the NYMEX (q.v.) oil futures contract.
The acronym for West Texas Intermediate (q.v.). 


Derivatives DigestTM

7/4/01 "Let there be Light." CFO (2001 July) By Tim Reason.

"The North American Electric Reliability Council (NERC) estimates [California] will see a minimum of 260 hours -- 15 hours a week--of rolling [power] outages this summer." That's assuming reduced usage in response to a 46% increase in power's price.

Power deregulation in the U.S. began in California, which screwed it up. Elsewhere, deregulation has been a non-starter. A recent survey by Booz-Allen Hamilton found that about 20% of businesses had switched and many of those didn't benefit from switching. 

Power customers who use rate analysis can cut their power costs up to ten percent by eliminating overcharges and switching to more advantageous pricing plans. Some companies save big by using their own generators during peak periods.  

Apparently, Dr. Risk isn't the only business person to find power pricing confusing. Power is a small part of our total cost, or careful analysis would be more worthwhile. A business can't make money by devoting (say) manpower worth $2000 to save $1500 on power charges.   


8/28/00 "Clinton Seeks Stepped-Up Power Probe." New York Times (2000 August 24) By Rebecca Smith and John J. Fialka.

Power prices in the San Diego market have quadrupled since last summer in some cases. blah, blah.

blah, blah.  


8/28/00 "Promise and Peril in New York Power Plan[t]s." New York Times (2000 August 14) By Kirk Johnson.

Orion Power Holdings, Inc., a Maryland corporation, bought Astoria Generating No. 2 and has proposed spending $15 million to repair it, so they would be able to deliver its 170 megawatts of power during peak periods. Given current wholesale power prices, Orion could recoup its investment in about one year, even it it never places Astoria No. 2 in production.

In other words, Astoria No. 2 (and its power production in the next year) is a real option on power. Orion is trying to be a dealer in that real option market, buying the option for $15 million plus, turning around and selling it for more, and making its profit on the spread. This option market differs from ordinary paper options, because it has a lot of baggage and grit, such as NYC politics and environmental issues.  


8/28/00 "Too Much Regulation Keeps California in the Dark." Wall Street Journal  (2000 August 8) By William P. Kucewicz.

The California Independent System Operator (Cal-ISO) board voted in early August 2000 to lower the ceiling on wholesale power prices from $500 per megawatt hour (mWh) to $250.

If Cal-ISO doesn't rescind this ceiling, we can confidently await a blackout in some part of California. The economics in a competitive market are simple. If demand were steady, then we would have some equilibrium level of power output at an equilibrium price that equalled the long run marginal cost of producing the power. If we add a peak period, then the marginal capacity for that peak period will be idle during the off-peak period. During the peak period, the marginal power plant must earn enough more than its operating cost to cover its fixed costs for the entire year. A sufficiently tight price ceiling will make this impossible. Consequently, firms in a market with a price ceiling will not meet peak demand, and we'll see non-price rationing -- such as black-outs and brown-outs. 


7/4/00 "Electricity Firms Play Many Power Games That Jolt Consumers." Wall Street Journal (2000 August 4) By Rebecca Smith and John J. Fialka.

The unregulated power market appears ripe for manipulation. 

On July 28, 1999 PECO and PPL offered most of their power at low prices, and a few smaller units at much higher prices. The wholesale market equilibrated at $935 per megawatt hour, about seven times the cost of power generation at the most expensive plant in the region. "Consumers that day ended up paying millions of extra dollars for power."

Far from being an abuse, that's the way this market is supposed to work, and it saves consumers money in the long run. It's called marginal cost pricing, and economists have proposed it since at least 1971, when I studied it in courses in the economics Ph.D. program at the University of Chicago. The idea is that the big profits on the "inframarginal" power plants during peak times encourages production of such plants, even though they may make little or no profit off-peak. 

May I point out a concept from Econ 101: If you offer power at $935 dollars a megawatt hour and somebody buys it, then either you’re the cheapest supplier or he’s not the brightest bulb in the chandelier. 

In July 1999, Cinergy surreptitiously "took enough power over a three-day period, about 9,600 megawatt hours, to light a small city for a month." It borrowed the power during the days, when it was expensive, and replaced it with power during the cool nights, when it was cheap. Cinergy made a lot of money and paid no fine or civil penalties.

It sounds as though some of the players in the unregulated power markets are playing dirty pool and hurting consumers and other utilities. However, the regulated market was one big game, and consumers were always the losers. Let's not make the rookie mistake of comparing reality invidiously with Nirvana. 



Real Power Options (Dr. Risk, 4/28/00) 

Investors who for decades have felt sophisticated for viewing power plants as streams of cash, rather than bricks, mortar, and pipes are now wondering why they are losing out the bidding for these power plants to investors who view them as call options.  An article in the Wall Street Journal provides the take-off point for an explanation. 

"Electricity markets deregulated within the past two years use the 'uniform price' method to set prices. Under that method, central dispatchers first tap generators offering to sell electricity at the lowest prices. Then ever-more-costly generating plants are utilized until enough plants are operating to satisfy demand. Power purchasers pay all bidders the price charged by the last power plant called into service.
"In many cases, that final unit will be a clunky oil-fired plant, charging a higher rate because of escalating oil prices. That means that many other generators will reap a windfall profit, for they will be paid as if they were burning oil even though most are using cheaper coal or natural gas. " (Rebecca Smith, "Northeast Faces Electricity-Price Surge; Costly Oil-Fired Plants May Drive Summer Rates," Wall Street Journal, 3/20/2000.) 

This paints the picture for Dr. Risk of a classic, monotonically non-decreasing marginal cost curve, and finally his expensive Ph.D. in economics has an application to his career as a consultant in financial engineering and risk management. Where's the option? Suppose, for simplicity that the price of power ordinarily runs between $20 and $40 per megawatt hour (MwH). The market commodity is one megawatt for one hour, e.g., from 3:00:00 p.m. to 4:00:00 p.m. You have a moderately efficient gas-fired turbine unit that can produce at the rate of as much as 1.2 MwH at a short-run marginal cost of $30 / MwH. If the market price for power is $20 / MwH, you shut down your plant and make nothing. If the spot price is S > $30, you fire up your plant and make $(S - 30) per MwH. Thus, the hourly profit of your plant is an option-like $Max(0, S-30), and it makes sense to think of your plant as a portfolio of 24 options for each day, all struck at $30. If the power price rises above $1,000 per MwH, again this summer, then the owner of this plant could really hit the jackpot. Regardless of whether you operate the plant you have the fixed cost of interest on the financing for your power plant. 

Of course, to be more realistic, you would want to have a better stochastic model for the price of power, and a better model for your marginal cost of power, which would depend on the price of natural gas. Thus, instead of being a call on megawatts of power, a power plant is an option to exchange natural gas for power a physically existing spark spread. – Dr. Risk


Swing Contract (Neal Horrell, 11/28/99) 

Contracts for the sale or purchase of energy, which provide flexibility as to quantity delivered – a swing feature or swing option – are common in the electric power, oil and gas industries. Typically, a swing option appears along with limitations on daily and cumulative amounts delivered. Energy contracts incorporated the swing feature long before the techniques to value options were developed, thus these embedded options were, as a general rule, mispriced, if priced at all.

Swing contracts are known by a variety of other names, such as base-load factor contracts, flexible nomination contracts, and take-or-pay contracts. They consist of a series of interrelated agreements to purchase an energy commodity over a prespecified period of time at a prespecified price, but at an unspecified rate between a minimum and a maximum. These contracts can also contain a number of complicating provisions that introduce path dependence: minimum and maximum load factors (cumulative or average amounts over some calendar period), take or pay (TOP) provisions, and ratchets (maximum quantity changes from day to day). Thus, unlike the typical option or swap that is “all or nothing”, these instruments have the possibility of partial exercise.

The swing contract arose from two facts about the energy industry: (1) the quantity of energy required is unknown in advance, and (2) there exists a separation between the energy producer, transmission, and end-user. The swing contract arose as a risk sharing and allocating mechanism. This type of contract originally allowed the energy producer to generate sufficient guaranteed revenue to meet debt service obligations and provide collateral (in the form of this contract) to finance development. Typically, it also allowed a purchaser to “make-up” prepaid gas.

Terms and Provisions

  • periodic delivery within a prespecified time period
    The range of the contract can have either a specific maturity (which is the current practice) or be in effect for the life of the well.
  • nominated amount 
    The nominated amount is the rate of delivery per period, which can either remain constant throughout the length of a swing period or vary based upon the last amount taken.
  • strike price
    The strike price can be either fixed at the inception of the contract or linked to a prespecified reference (plus or minus a spread). If the strike is specified in advance, this is termed full protection. If the strike floats and is set at a future date, it is called partial protection. The latter would typically be set during bid week or relative to some index.
  • swing right
    The swing amount can either be fixed to specific increments – e.g. 5 million cubic feet (MMCF) – or can be left open. The number of swings can also be limited.
  • swing types 
    A daily swing right allows the holder of the contract to change the amount of commodity that is delivered to it on the following delivery date. This will typically not affect the nominated amount. 
    - Nominated (persistent) swing right allows the holder of the contract to change the nominated amount of commodity that is delivered to it, starting the following delivery date, until expiration of the contract or until a new swing right is exercised. 
  • maximum and minimum cumulative or average amounts 
  • penalty function
    Should the total amount taken vary outside of a minimum to a maximum range, then compensation is paid to the energy supplier. This could either depend upon the then current spot price (the buyback) or be a fixed unit penalty. The buyback rule (or function) is of the form excess * (spot - strike) or deficit * (strike-spot). These functions are not necessarily constant but could be ratcheted. The fixed unit penalty is per unit amount of excess or deficient delivery.


A typical swing contract may have the following form. Producer A agrees to sell to gas pipeline company B 100 MCF per day at a fixed price for a one-month period. B has the right the day before to alter the amount it purchases by 10 MCF from the previous day’s level (the swing). However; B’s purchases cannot be less than 50 MCF nor greater than 150 MCF. In addition, B must purchase 3000 MCF over the month. 

The decisions rest entirely with company B. It should choose the purchases to maximize the value of the contract. 


The valuation of these instruments is quite complicated. This is not only because the options have American style elements, but also they have path dependence.

There are several approaches to valuation of these complex contracts. These include tree approaches, Monte Carlo simulations, and quasi-analytic approaches (closed form solutions). We are proposing the use of dynamic stochastic programming as the modeling methodology.


Electricity and VaR (Neal Horrell, 9/28/99) 

Visions of extreme weather flooded American newspapers and airwaves this summer.  Viewers saw withered crops, ruined lives and dead and dying barnyard beasts.  The death toll from the excessively hot weather in the Midwest was nearly 200 people.  Even worse, on July 30th of this year, Cinergy was forced to default on forward wholesale electricity contracts, at a loss of $73 million.  James Rogers (President and CEO) described the losses to the Wall Street Journal.  He stated that they were due to a 1% weather event.  Additionally he observed that a business is not planned around an event that has a small chance.  It is almost possible to hear the frustration in his words. 

Unfortunately, the Cinergy experience will not be unique among the regulated utilities, who must learn to play the game according to new rules. Under the regulated system, a utility was guaranteed a specific return on capital, subject to some limitations.  This approach actually encouraged the industry to take risks.  If costs rose, they would obtain rate relief.  However, if the company hedged, regulators disallow rate increases if the hedge worked.  Worse, hedging losses would pass to the shareholders.  However, the move to an unregulated environment has to a certain extent removed this possibility while at the same time it has retained the obligation of the utility to supply energy.   In effect, these companies had an option to appeal to the state public utilities commission and recoup any extreme events over time.

Regulated utilities cannot afford to ignore organizational issues. The use of the Value at Risk (VaR) has become the de facto standard for risk management within the electric utility industry. Unfortunately, there was a  failure in the communication of the limitations of VaR to some senior management.  

Additionally, there are three major methodological issues in the application of VaR and its variants. 

  1. The assumed distribution of asset returns can be wrong.  This will misestimate the probability of an event.  The traditional implementation of this approach assumed normally distributed asset returns. This is clearly not true in the electricity markets. The traditional approach underestimates the likelihood of an extreme event. 

  2. The VaR methodology assumes a stationary distribution. This may be true, but it is clear that there is a wide variation in temperature between summers.  These extreme summers demonstrate a different degree day distribution.  Electricity demand and prices usually show a major peak in the summer and a minor peak in the winter.  This requires a time varying parameter implementation. 

  3. A low probability event cannot be safely ignored.  A one- percent event happens 3-4 times per year on average.  This event also had a huge negative payoff.  The combination creates tail events with a large expected value.  The issues can be seen in a simple game.  The game is free to play.  It pays one dollar 99% of the time and costs $99 the rest of the time.  This is a fair game, yet most people would not pay it.  This is because of the high loss associated with the low probability state.  This is analogous to the extreme (low probability) event that Cinergy experienced.

The events of the summer demonstrate an undue reliance on VaR present the risk manager with a myopic view of the world.  The most prudent approach is to use VaR to provide an indication as to the daily typical operating characteristics of the firm.  However, this does not give the true picture of the situation as it ignores the extreme events.  Thus VaR is also combined with scenario analysis.  Those systems combining the two typically avoid betting the ranch.  This combination can have Jim Rogers riding high in the saddle again. – Neal Horrell


Links Links related to energy are below. Links related to other financial topics are here.

Electrical Power








Your Energy Markets Pros

Your Derivatives 'Zine energy markets professional for this issue is William Margrabe

William Margrabe

William Margrabe became an energy pro when he reviewed energy derivatives pricing models for an energy dealer, something he still does. He has produced a pricing model for options on heating and cooling degree days for one of America's largest energy companies. In 2001 he began selling selling pricing models for the spark spread (long power, short NG or WTI crude) and helping to value power plants as real options. He studied the economics of hydro-electric and fossil-fueled power plants during his economics doctoral program at the University of Chicago. You may contact him – ask him questions, suggest a topic for an essay, etc. – by sending a message to Dr. Risk

Neil Horrell

Neal Horrell, has more than five years of experience in the energy area as consultant, risk manager, and financial engineer. You may contact him – ask him questions, suggest a topic for an essay, discuss a consulting project, etc. – by sending a message to Dr. Risk, Attn: Energy Pro. 


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