Electricity/power

The electricity market (often described in the USA as the power market) is very
different for one fundamental reason: both storage and transportation are incredibly
expensive.10 Let us briefly describe the nature of the power market from a trading
and risk management perspective.
First, like many products, electricity demand varies significantly throughout the
day, week and year. However, electricity has the same properties as a highly perishable
product in that not only must supply meet demand, but production must meet
demand minute by minute. The result of this unique attribute is that the market
must keep a significant amount of idle capacity in place for start-up when the
demand is there and shut-down when demand recedes. In some cases, this is a
generation station that is already running, ready to meet anticipated customer
demand. In other cases it is plant that may only be asked to start up once every few
years. Typically a local market (or grid system) will keep 15–20% more plant capacity
than it expects to use on the highest hour of demand during a normal year. This will
often represent over double the average demand.
This, coupled with the physical challenges of transporting electricity,11 leads to a
general position of over-supply combined with short periods when the normally idle
plant needs to run. At such peak times, when all the capacity on the system is
needed, spot market prices12 will rise dramatically as plant owners will need to
recover not only their higher cost of running but also their capital costs in a relatively
short period of time. This is exacerbated by the fact that electricity generation is one
of the most capital-intensive industries in the world.
The forward market will, of course, smooth this by assigning probabilities to the
likelihood of the high prices. Higher probabilities are obviously assigned during the
periods when demand is likely to be at a peak and this will generally only occur
during two or three months of the year. In the USA this is generally in the summer.
Thus unless there is a huge over-supply the summer prices will be significantly
higher than the rest of the year. When there is a potential shortage prices will be
dramatically higher, as was seen in the Cinergy market in late June 1998 where
daily prices that trade most of the year at $30/MWh increased to $7000/MWh.
It is these important market characteristics that lead to the extreme seasonality,

jumps, spikes and mean reversion that will be discussed below in the section on
Market Risk. Given the extreme nature of these factors trying to capture them on
one term structure or convenience yield is extremely difficult.
Despite this price uncertainty, a forward market for electricity has developed along
a standard commodity structure. In fact seven exchange contracts, reflecting the
regional nature of power, currently exist at Palo Verde, California/Oregon Border
(COB), Entergy, Cinergy (NYMEX), TVA, ComEd (CBOT) and Twin Cities (M. Grain
Exchange) and PJM. The forward curves for Cinergy is shown in Figure 18.2 compared
to the Henry Hub gas curve.
Figure 18.2 Forward curves for Cinergy compared to the Henry Hub gas curve. (Source: Citizens
Power,June 1999)
Some standard options are traded at the most liquid hubs. These tend to be ‘strips’
of daily European calls based on monthly blocks. However, the bid/ask on such
products are often wide and the depth of liquidity very limited.
Forward curve price discovery – the problems with power
Let us focus on two major differences in power:
Ω Storage First, you have virtually no stack and roll storage arbitrage. In other
words, since you cannot keep today’s power for tomorrow there is no primary
‘arbitrage’ linkage between today’s price and tomorrow’s. There are, of course,
many secondary links. The underlying drivers are likely to be similar – demand,
plant availability, fuel costs, traders’ expectations and general market environment.
But as you move forward in time, secondary links break down quickly and
so does the price relationship. Figure 18.3 shows the forward correlation between
an April contract and the rest of the year. As you can see, almost no relationship
exists between April and October and most of the relationship has evaporated
once you are beyond one month. In other words, the October Cinergy contract
has no more relationship with the April contract than, say, an oil, gas or even
interest rate market.
Ω Transportation Second, you have limited ‘hub basis’ arbitrage. Since there are
numerous logistical limitations on moving electricity it is difficult to arbitrage
between many of the power markets within the USA (never mind internationally).
Even hubs that are relatively close show large variations in the spread between
prices. Figure 18.4 shows some of the correlations between major power hubs in
the USA. Rather than thinking of them as one market, it is more accurate to view
the power market as at least twelve (the final number of hubs is still being
determined by the marketplace) independent markets with some but often little
relationship.
Once you put all these factors together you see a picture similar to the one a global
risk managers in a big bank will have experienced, a huge number of independent
products that need to be combined for risk purposes. Instead of having one forward
curve for US Power, we have up to eighteen independent months for twelve independent
markets, in other words 216 products. This brings both the curse of lack of
liquidity and data integrity for each product and, on the positive side from a risk
perspective, diversity.
Forward curves up to 24 months are traditionally built using daily trader/broker
marks for monthly peak/off-peak prices, with the breakdown, where necessary, into
smaller time periods (down to an hourly profile) using historical prices adjusted for
normal weather conditions. Prices beyond two years are significantly less liquid and
where information is available bid/ask spreads can increase significantly. Forward
price curves (and volatility curves) beyond 24 months thus need to be created through
more of a mark to model rather than mark to market process. As noted above, using
a model to connect price quotes inevitably involved a number of assumptions about
how the market behaves. In power, this involves not just fitting a serious of different
price quotes together, but also filling in the gaps where price quotes are not available.
The price structure will have to make certain model assumptions based on historical
observation about seasonality and the year-to-year transition process. Models
can be bought (such as the SAVA forward curve builder) or, more often, built inhouse.
However, given the developing nature of the market this still tends to be a
relatively manual process to ensure all the relevant market information can be input
into the curve and minimize the error terms.
It needs to be remembered that in making assumptions about the structure of the
curve in this process to estimate the fair value of a transaction that the forward
curve, while objective, unbiased and arbitrage-free, may be unreliable given the
incomplete data sets. Throughout the process it is thus necessary to estimate the
impact of such assumptions and modeling or prudency reserves are likely to need to
be applied against the fair value under these circumstances. The collection of market
data with an illiquid market also becomes a major operational issue with a need to
continuously verify and search for independent data. 534

Gas forward curve

Price discovery in gas is not as transparent as in the oil market. The transport and
storage capabilities of the gas market is relatively inflexible compared to the oil
market. The market is also more regional7 than the oil market, with international
trade being restricted by pipeline costs and LNG (liquefied natural gas) processing
and transport costs.
The US gas trading market (although probably the most developed in the world) is
much more fragmented than in the oil market with a large number of small producers,
particularly at the production end. Given the inability to hedge through vertical
integration or diversity this has resulted in a significant demand for risk management
products. The market after the deregulation in the 1980s and early 1990s has been
characterized by the development of a very significant short-term market. This sets
prices for a thirty-day period during what is known as ‘bid week’.8 The prices
generated during this ‘bid week’ create an important benchmark9 against which
much of the trading market is based.
The futures contracts in gas have been designed to correspond with the timing of
bid week, the largest and most developed contract being known as Henry Hub. This
has been quoted on NYMEX since 1990, supports a strong options market and
extends out three years on a relatively liquid basis. Basis relationships between
Henry Hub and the major gas-consuming regions within the USA are well established
and, in the short term, fairly stable. The OTC market supports most basis locations
and a reasonable option market can be found for standard products. It is worth
noting that, credit aside, in energy the value of the futures market and the OTC
forward market is the same, albeit the delivery mechanisms are different. This is
true because there is no direct correlation to interest rates and the EFP (Exchange
for Physical) option imbedded in the futures contract.
In gas, storage costs play a critical role in determining the shape of the forward
curve. A variety of storage is employed from line pack (literally packing more gas
molecules into the pipe) to salt caverns and reservoirs (gas can be injected and
extracted with limited losses) and the pricing and flexibility of the different storage
options varies significantly.
As a general rule, the gas market stores (injects) during seven or eight ‘summer’
months and extracts during the winter months. Significant short-run price movements
occur when this swing usage is out of balance. In these circumstances gas
traders will spend much of the time trying to predict storage usage against their
demand estimations it order to determine what type of storage will be used during
the peak season and thus help set the future marginal price.
Like the oil market, the gas markets exhibit mean reversion, and are subject to
occasional jumps due to particular ‘events’ such as hurricanes shutting down
supplies. But most importantly, despite this storage, gas remains significantly more
seasonal in nature than most of the oil market.

Basis trading from Henry Hub plays a vital part in the market with differentials to
the major consumption zones being actively traded in the OTC market. These basis
prices are less stable than those seen in the oil market given the more constrained
transport infrastructure and volatility in demand. As a result, the monitoring of these
basis relationships under normal and extreme conditions becomes critical.
Risk managers should be very wary of basis traders or regional traders marking
their books against a contract in a different region such as Henry Hub who are
seen to have large ‘book’ profits based on future positions. There have been a
number of instances where such regional traders have had their positions wiped
out overnight when the correlations have broken down under extreme market conditions.
In other words, you need to ensure that the higher volatility or ‘spike potential’
in less liquid regional markets compared to a large liquid hub has been reflected
in the pricing.
Historical ‘basis’ positions may also fundamentally change as the pipeline positions
change. For instance, the increasing infrastructure to bring Canadian gas to the
Chicago and North US markets could significantly change the traditional basis
‘premium’ seen in these markets compared to Henry Hub.
While most trades up to three years are transacted as forward or future positions
an active swap market also exists, particularly for longer-term deals where the
counter-parties do not want to take on the potential risks associated with physical
delivery. These index trades are generally against the published Inside FERC Gas
Market Report Indices although Gas Daily and other publications are also used
regularly. It is necessary to be aware that indices at less liquid points may not be
based on actual transaction prices at all times, but may be based on a more
informal survey of where players think the market is. This may lead to indices being
unrepresentative of the true market. 531

The oil market

Crude oil can come from almost any part of the world and the oil market, unlike gas
and power, can be described as a truly global market. The principal production
regions can be generally grouped into the following: North Sea (the most notable
grade being Brent), West Africa, Mediterranean, Persian Gulf (notably Dubai), Asia,
USA (notably WTI), Canada and Latin America. Each region will have a number of
quality grades and specifications within it, in particular, depending on their API
gravity2 and sulfur content.

In Europe the benchmark crude product is North Sea Brent while in the USA it is
often quoted as WTI. WTI is the principal product meeting the NYMEX sweet crude
specifications for delivery at Cushing (a number of other qualities can also be
deliverable, although many non-US crudes receive a discount to the quoted settlement
price). The other major crude product is Dubai, representing the product
shipped from the Persian Gulf.
Each of these three products will trade in close relation to each other, generally
reflecting their slightly different qualities and the transport cost from end-user
markets, all three markets reflecting the overall real or perceived supply/demand
balance in the world market. Other crude specifications and delivery points will then
trade some ‘basis’ from these benchmark prices.
As well as the three crude products noted above, the oil market encompasses the
refined products from crude oil. While thousands of different qualities and delivery
points world-wide will ultimately result in hundreds of thousands of different prices,
in Europe and North America these can generally be linked back to a number of
relatively strong trading hubs that exist, notably:
Product type Principal hubs
Crude Brent/Cushing/Dubai
Unleaded NWE3/New York/Gulf Coast
Gas Oil/No. 2 Oil NWE/New York Harbor
Heavy Fuel Oil/No. 6 Oil NWE/New York Harbor/Far East
In addition, the rest of the barrel, propane, butane, naphtha and kerosene trade
actively, but are more limited in terms of their relevance to the energy complex.
Within the various product ranges prices are quoted for particular standard grades.
For instance, No. 6 oil (also known as HFO or residual oil) can be segmented to 1%,
2.2%, 3% and 3.5% sulfur specifications. Each have their own forward curves and
active trading occurs both on the individual product and between the products. The
market has developed to the point where NYMEX lists not only option prices but also
Crack Spread Options (the option on the spread between the products).4
Like its other energy counterparts most of the trading is done in the OTC ‘brokered’
market that supports most of the commonly traded options, swaps and other
derivative structures seen in the financial markets. Derivatives are particularly useful
in oil compared to other energy products given the international nature of the product
and the relationship between the overall oil complex. For instance, if we take an
airline company, this needs a jet fuel hedge that reflects the weighted average cost
of its physical spot fuel price purchases in different parts of the world. At the same
time it would like to avoid any competitive loss it might experience from hedging out
at high prices. This would be complex (and unnecessary) to achieve physically, but
relatively straightforward to hedge using a combination of different swaps and
average price options, which can be easily linked to currency hedges.
Another common swap is the front-to-back spread, or synthetic storage. This
allows the current spot price to be swapped for a specified forward month. It should
be noted that this relationship may be positive or negative, depending on market
expectations. Locational swaps are also very common, providing a synthetic transport
cost. Such swap providers in this market (and all energy markets), however, need to
be very aware of both the physical logistics and the spot market volatility.
Crack spreads and Crack spread options are used to create synthetic refineries.

The 3:2:1 crack spread that is traded in NYMEX is a standard example of this linking
the prices of crude, heating oil and gasoline.
In oil, the majority of swap transactions are carried out against Platt’s indices that
cover most products and locations, although a number of other credible indices exist
in different locations. For instance, CFD’s (Contracts for Differences) are commonly
traded against ‘dated’ Brent, the price for physical cargoes loading shortly and a
forward Brent price approximately three months away.
While such derivatives are easy to construct and transact against the liquid hubs
they have their dangers when using them to hedge physical product at a specific
delivery point. Specific supply/demand factors can cause spreads between locations
and the hubs to change dramatically for short periods of time before they move back
into equilibrium. For example, extreme weather conditions can lead to significant
shortages in specific locations where imports are not possible leading to a complete
breakdown of the correlation between the physical product and the index being used
to hedge. In other words you lose your hedge exactly when you need it. A risk
manager must look carefully at the spreads during such events and the impact on
the correlations used in VaR and Stress tests. They should also understand the
underlying supply/demand conditions and how they could react during such extreme
events.
It should also be noted that oil products are often heavily taxed and regulated on
a state and national basis which can lead to a number of legal, settlement and
logistical complexities. Going hand in hand with this is the environmental risks
associated with storage and delivery, where insurance costs can be very substantial.
Ever-changing refinery economics, storage and transportation costs associated
with the physical delivery of oil are thus a significant factor in pricing which results
in the forward curve dynamics being more complex than those seen in the financial
markets. As a result the term structure is unpredictable in nature and can vary
significantly over time. Both backwardation5 and contago6 structures are seen within
the curve, as is a mean reversion component. Two components are commonly used
to describe the term structure of the oil forward curve: the price term structure,
notably the cost of financing and carry until the maturity date, and the convenience
yield. The convenience yield can be described as the ‘fudge factor’ capturing the
market expectations of future prices that are not captured in the arbitrage models.
This would include seasonal and trend factors.
Given the convenience yield captures the ‘unpredictable’ component of the curve,
much of the modeling of oil prices has focused on describing this convenience yield
which is significantly more complex than those seen in the financial markets. For
instance, under normal conditions (if there is such a thing), given the benefit of
having the physical commodity rather than a paper hedge, the convenience yield is
often higher than the cost of carry driving the market towards backwardation.
Fitting a complex array of price data to a consistent forward curve is a major
challenge and most energy companies have developed proprietary models based on
approaches such as HJM to solve this problem. Such models require underlying
assumptions on the shape of the curve fitting discrete data points and rigorous
testing of these assumptions is required on an ongoing basis.
Assumptions about the shape of the forward market can be very dangerous as MG
discovered. In their case they provided long-term hedges to customers and hedged
them using a rolling program of short-term future positions. As such they were
exposed to the spread or basis risk of the differential between the front end of the
market (approximately three-month hedges) and the long-term sales (up to ten years).
When oil prices in 1993 fell dramatically they had to pay out almost a billion dollars
or margin calls in their short-term positions but saw no offsetting benefit from their
long-term sales. In total they were reported to have lost a total of $1.3 billion by
misunderstanding the volatility of this spread.
Particularly in the case of heating oil, significant seasonality can exists. Given the
variation in demand throughout the year and storage economics, the convenience
yield will vary with these future demand expectations. This has the characteristic of
pronounced trends, high in winter when heating oil is used, low in summer and a
large random element given the underlying randomness of weather conditions.
The oil market also exhibits mean reversion characteristics. This makes sense,
since production economics show a relatively flat cost curve (on a worldwide basis
the market can respond to over- and under-supply and that weather conditions (and
thus the demand parameters) will return to normal after some period.
In addition, expected supply conditions will vary unpredictably from time to time.
Examples of this include the OPEC and Gulf War impacts on perceived supply risks.
Such events severely disrupt the pricing at any point leading to a ‘jump’ among the
random elements and disrupting both the spot prices and the entire dynamics of the
convenience yield. I will return to the problem of ‘jumps’ and ‘spikes’ later in this
chapter. 529

The energy forward curve

Energy forward curves generally exhibit certain common characteristics; notably,
forward curves in the USA are based upon a wheel and spoke design. A small number
of strong trading hubs exist that, relative to the remaining parts of the market, are
very liquid. In addition, liquidity has been enhanced by the formation of exchangebased
contracts (in particular NYMEX and the IPE) as well as OTC (over-the-counter)
trading.
The currently developed trading hubs do not represent a product that all the
buyers and sellers want, but a particular quality and delivery point that can set a
transparent and ‘unbiased’ benchmark that the industry can price around. Trading
away from these hubs are normally done on ‘basis’. In other words, premiums or
discounts are paid depending on the differential value of the product compared to
the hub product. This differential may reflect a higher or lower transport cost, quality
or locational supply/demand conditions.

Development of alternative approaches to risk in the energy markets

In response to this market price uncertainty, many oil companies modified traditional
investment analysis approaches to include scenario analysis rather than forecasting
analysis as well as starting to lever off their hedging and trading operations. The use
of a scenario approach in investment decisions was an early indication that even oil
majors accepted that they could not predict future price movements with any
certainty.
Meanwhile the financial engineers on Wall Street were solving the same issue from
another direction, notably the development and refinement of the derivative pricing
models using quantitative approaches. Option pricing models through the 1980s
began by stripping out the observable forward markets from market uncertainty.
Although relatively straightforward in nature, these models facilitated a key move
away from a fundamental analysis approach and allowed the application of some
proven statistical concepts to the markets, most notably the measure of market
uncertainty through the use of volatility estimators.
With the exception of a small group of specialized oil traders, the energy markets
were much slower than the financial markets in embracing these quantitative
approaches. The reasons for this are many and begin to signal many of the risk
management issues associated with energy, notably: . . . energy markets are immature
and often still partly regulated, complex in their interrelationships (both between
products and regional delivery points), constrained by lack of storage, subject to
large seasonal swings, mean reversion, subject to large investment cycle issues,
delivered products tend to be very complex in nature . . . and the list goes on. On a
continuum the complexity increases exponentially as we move from the money
markets to the oil market to the gas market to the electricity markets.
In the last few years an increasing number of practitioners and academics have
began to take on the challenge of developing and modifying quantitative approaches
for the energy markets. The reason for this is simple: while the complexity is much
higher in these markets, the underlying assumption in the quantitative models that
the future is essentially random rather than predictable in nature is particularly
relevant to an increasingly commoditized energy sector. The quantitative approach
is also particularly useful when aggregating a diverse book like an energy portfolio.
For instance, Value-at-Risk (VaR) allows us to aggregate separate oil, gas and power
books daily on a consistent basis. It is difficult to do this without applying a statistical
approach.
The development of risk management professionals within the energy sector has
also accelerated as energy companies have developed their commodity trading experience
and embraced the middle-office concept. An independent middle office is
particularly important in the energy sector given the complexity of the markets. A
combination of market knowledge, a healthy dose of skepticism and a control culture
focused on quantifying the risks provides an essential balance in developing markets
with little historical information and extreme volatility.
Each of the three principal risk management areas – market risk, counterparty
credit risk and operational risk – are relevant to an energy business. There is not
enough space in one chapter to describe the markets themselves in any detail so I
shall focus primarily on those parts of the markets that impinge on the role of the
risk manager. In addition, the examples used will relate primarily to the power
markets, in particular in the USA. This is not to imply that this is the most important
market or the most developed, but quite simply because it provides useful examples
of most of the quantitative problems that need to be addressed by risk management
professionals within energy companies, whether based in Houston, London or
Sydney.

Background

Risk management has always been at the forefront of those within the energy industry
and indeed those within government and other regulatory bodies setting energy
policy. From OPEC to nationalized generation and distribution companies, the risks
associated with movements in energy prices have been keenly debated by both
politicians and industry observers. As such, assessing the risks associated with the
energy markets is not a new phenomenon. However, the recent global trend to shift
the risk management of the gas and power markets from regulated to open markets
is radically changing the approach and tools necessary to operate in these markets.
Energy price hedging in oil can be traced back to the introduction of the first
heating oil contracts on NYMEX in 1978 and the development of oil derivative
products in the mid-1980s, in particular with the introduction of the ‘Wall Street
Refiners’ including the likes of J. Aron and Morgan Stanley who developed derivative
products such as ‘crack’ spreads which reflected the underlying economics of refineries.
While the traditional risk management techniques of oil companies changed
radically in the 1970s and 1980s the traditional model for managing gas and power
risk remained one of pass through to a captive customer group well into the 1990s.
In gas and electricity, regionalized regulated utility monopolies have traditionally
bought long-term contracts from producers and passed the costs onto their retail
base. The focus was on what the correct costs to pass through were and what
‘regulatory pact’ should be struck between regulators and the utilities. Starting with
a politically driven trend away from government ownership in the 1980s and early
1990s, this traditional model is now changing rapidly in the USA, Europe, Australia,
Japan and many other parts of the world.
Apart from the underlying shift in economic philosophy, the primary driver behind
the change in approach has been the dramatic price uncertainty in the energy
markets. Large price movements in the only unregulated major energy market, oil,
left utilities with increasing uncertainty in their planning and thus an increasing
financial cost of making incorrect decisions. For instance, the worldwide move by
utilities towards nuclear power investments as a means to diversify away from the
high oil prices in the 1970s led to significant ‘above market’ or stranded costs for
many utilities.

Energy risk management

This chapter focuses on the challenges facing a risk manager overseeing an energy
portfolio. It sets out a general overview of the markets as they relate to risk management
and the risk quantification and control issues implicit in an energy portfolio.
The energy markets are extremely intricate, rich in multiple markets, liquidity
problems, extreme volatility issues, non-normal distributions, ‘real’ option pricing
problems, mark-to-model problems, operational difficulties and data management
nightmares. The market, to use the academic understatement, is complex and
challenging but most of all it is extremely interesting. In particular, this chapter will
focus on the challenges in the electricity market, which is by far the largest market
within energy1 and exhibits most of the problems faced by energy risk managers,
whether in power or not.