Section1-Energy Commodities Intro

Section 1: Energy Commodities Basics

Glen Swindle

20 March 2012

c© Glen Swindle: All rights reserved

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Outline

What makes energy commodities different?

Pricing and Delivery

Forward Yields

Macro Perspective

Hedging and Common Structures

Themes

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What makes energy commodities different?High Volatility

Realized volatility for a price series p(n) is defined as:[250

∑n

R2(n)

] 12

where R(n) = log[

p(n)p(n−1)

]For commodities we have used the first traded contract (defined shortly)

GT10 volatility was proxied by the product of duration and change in yield.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100

0.1

0.2

0.3

0.4

0.5

0.6

0.7Historical Vols

SPXEURGC1GT10WTI

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 20100

0.2

0.4

0.6

0.8

1Historical Vols Normalized by WTI Vol

SPXEURGC1GT10

3 / 43


High Volatility

Does this really matter?

Options markets exist for energy commodities that can be used to hedge

vol exposures.

Returns statistics for NYMEX crude oil (WTI) and natural gas(NG):

First contract and the rolling 12 month (”cal”) strip

1 and 10 day intervals

Statistic WTI 1st Month WTI 1Y NG 1st Month NG 1Y

Std Dev (1 Day) 0.024 0.020 0.035 0.022p1,99 (1 Day) 0.067 0.053 0.093 0.059

Std Dev (10 Day) 0.073 0.059 0.107 0.069p1,99 (10 Day) 0.228 0.172 0.272 0.180

Table: Returns Statistics (2000-2010)

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High Volatility: Deal Pricing

Suppose you are purchasing an energy asset, for example:

A set of oil or natural gas production fields.

An efficient power generation asset.

In these (and many other cases) the value is approximatelylinear in the price of the underlying commodity.

During the course of two weeks one can expect:

A 6-7% change in value

p1,99 of nearly 20%

For the acquirer paying say a billion dollars, as well as for thelenders supporting such an activity, a 20% change in valuewould be highly problematic.

Simply converging on an acquisition price with suchunderlying volatility can be challenging.

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High Volatility: Colateral

Whether exchange traded or OTC, hedging activities areusually accompanied by colateral posting requirements.

High volatility in the underlying requires significant availabilityof cash and/or letters of credit (LCs) .

High volatility amplifies mismatches in colateral posting terms.

Example: Retail energy companies

Provide commodities to retail end-users (who typically are not margined)

Hedge this native short position via standard futures or OTC swaps

markets (which are margined)

This mismatch in credit support can result in lethal colateral calls in

highly volatile times.

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What makes energy commodities different?High Volatility: Colateral

The following plots shows the rolling cal strip for NYMEX WTI, NGand PJM power prices.

PJM is a power market in the eastern U.S. and the largest power market

in North America

The colateral calls against entities with long energy hedges put on

in mid-2008 were onerous.

2007 2008 2009 2010 20110

50

100

150

$/Ba

rrel

WTI

2007 2008 2009 2010 20110

5

10

15

$/M

MBt

u

NYMEX NG

2007 2008 2009 2010 20110

50

100

150

$/M

Wh

PJM Peak

Figure: Rolling Calendar Strips

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What makes energy commodities different?”Specialness”

Another relevant feature is that energy commodities arealways going ”special.”

”Special” is a term borrowed from bond markets in whichparticular bonds that are ”cheapest to deliver” (CTD) into afutures contract trade at a premium due to limited supply

0 5 10 15 20 250

0.005

0.01

0.015

0.02

0.025

0.03

0.035

Duration(Y)

Yield

Yield Versus Duration: 15Jan2009

10Y Futures CTD

Long Bond Futures CTD

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”Specialness”

For commodities supply/demand variations are far moreextreme than in other markets resulting in breakdowns of”typical” relationships—i.e. specialness.

Specialness in commodities is either temporal or locational.

A single commodity delivered at two different times orlocations can behave functionally as two entirelydifferent assets.

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What makes energy commodities different?Temporal Specialness

The following figure shows a sample NYMEX NG forwardcurve.The periodicity (and non-monotone) prices are due toseasonal variations in demand.The winter months trade special to the summer months.This increases the dimensionality of risk management;

Limited effectiveness using front month contracts to hedge winter

exposures.

2010 2011 2012 2013 2014 2015 20165.5

6

6.5

7

7.5

8

Forw

ard

Price

($/M

MBt

u)

NYMEX NG Forward curve: 25−Jan−2010

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What makes energy commodities different?Temporal Specialness

Spot price behavior shows short time-scale ”specialness.”The term ”spot price” refers to the price for delivery of the commodity for

delivery ”now.”

The following shows daily spot prices and spot returns forHenry Hub natural gas.

Henry Hub is the location underpinning the NYMEX NG.

Note that daily returns in excess of 500% are not uncommon.

2000 2002 2004 2006 2008 20100

5

10

15

20

$/M

MBt

u

Henry Hub Spot Prices

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011−3

−2

−1

0

1

2

3x 10

4

%

Annualized Returns (%)

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Locational Specialness

The figure shows historical daily spot prices for Henry Huband for TETM3, a delivery location in the northeast.

The middle figure shows the spot basis price, which is thedifference between TETM3 and the benchmark Henry Hubprices.

The bottom figure is the price ratio.

While TETM3 is typically premium to Henry Hub due totransportation costs, of particular note are the substantialpremia in spot prices that can arise due to high demand andlow supply on occasional days in the winter.

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Locational Specialness

1998 2000 2002 2004 2006 2008 20100

20

40

60

$/M

MBt

uSpot Prices

Henry HubTETM3

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

10

20

30

$/M

MBt

u

Spot Basis

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

2

4

6

TETM

3 / H

H

Spot Ratio

13 / 43


Specialness

These phenomena described apply at even shorter time scalesin power: daily, hourly and even sub-hourly.

A commodity for delivery at a particular time and location canexhibit dramatically different price dynamics from the samecommodity deliverable at a different time and location, evenwhen the times and locations are seemingly ”close.”

The set of tradables (swaps and options) available to aportfolio manager is often far smaller than the number ofways that a commodities portfolio can go special.

A major theme of this course is to elaborate on gap betweenrisks that can be hedged and risks that are often embedded incommodities businesses.

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Basic Terms

The pricing of a commodities trade requires specification of:

The underlying commodity

When and where will the commodity delivered/referenced

The price to be paid for the commodity

The notional quantity

The mechanics of delivery/settlement

Credit / Margining:

OTC contracts: specific margining provisions in ISDAs or related energy

specific credit docs.

Futures: Exchange traded with daily margining / mark-to-market.

For futures settlement has occurred implicitly through daily

margining.

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Examples

WTI Crude CME/NYMEX (Futures)

Notional 1000 barrels delivered anytime in the contract month

Specific grades of crude (adjusted for value) delivered at Cushing, OK

Natural Gas CME/NYMEX (Futures)

Notional 10,000 MMBtus delivered ratably over the contract month

Delivery location: Henry Hub, LA

Gas Daily Swap (OTC)

Buyer will pay seller $5.20 per MMBtu for 10,000 MMBtu’s per day of

natural gas in Dec 2011

Seller will pay buyer the average Gas Daily Index at Henry Hub for the

delivery month.

Settlement is 10 business days after the last flow date.

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Physical Versus Financial

Physical transactions (forwards and some futures) involvedelivery of the commodity at a specified location.

Financial transactions (swaps) involve cash settlement basedupon a benchmark price index prevailing at the time ofanalogous physical delivery.

In a physical transaction no reference to an underlying price index is

required.

Delivery is often assumed to be ratable (uniform volume) over a specified

interval.

The third example is a financial transaction.

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Notional

The notional quantity of a transaction is often defined interms of flow rate (per day or per hour) as opposed to a totalnotional.

A market standard for delivery quantity is often referred to asa ”lot”.

For natural gas a lot is 10,000 MMBtus.

For crude oil a lot is 1000 barrels.

In the third example:

The total notional would be 310,000 MMBtus.

This would be articulated as ”one lot a day” or more succinctly as

”one-a-day” on a trading desk.

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Notation

We will denote the forward price observed at time t fordelivery at time T by F (t,T ).

In the case of a delivery interval, this will be replaced byF (t,T ,T + S) where [T ,T + S ] defines delivery interval overwhich ratable (uniform) delivery of the commodity is assumed.

In cases where the delivery interval is a contract month m wewill abbreviate notation along the lines of Fm(t) or F (t,Tm).In the third example F (0,Tm) = $5.20 .

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Notation

In practice the delivery interval is treated as a discrete set ofdelivery days for the purpose of pricing and operations.

Note that:

Fm(t) =1

Tm+1 − Tm

∫ Tm+1

Tm

F (t,T )dT (1)

There is no discounting here as settlement usually occurs onthe same date in the following month.

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Spot Prices

The floating price in the third example is often referred to a”spot price”, which is the price for ”immediate” delivery.

A spot price is in almost all situations technically a forwardprice with a delivery time very close to the present.

Formally the spot prices is represented by F (t, t)

In practice, the price is usually established slightly before thedelivery time, rendering the distinction between spot andforward somewhat arbitrary.

In the case of natural gas, trading for delivery on day d occurs on day

d − 1 which is when the index print is established.

For power the spot price can be set a day before, hour before or

immediately at delivery.

For coal in which logistics and shipment are an issue, ”spot” can refer to

a time-lag between trade date and delivery measured in weeks or months.

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Basic Facts about Forwards

The unit value of a long position in a forward contract at timet struck at time t = 0 is given by:

V (t,F (t,T )) = d (t, τ) N [F (t,T )− F (0,T )] (2)

where τ denotes the settlement time, N the notional and d()the discount factor.

Deltas for forwards are discounted notionals:

∆ ≡ ∂V

∂F (t,T )= d (t, τ) N (3)

For a futures contract the unit ∆ is the undiscounted notionalN due to daily margining.

22 / 43



Swaps and forwards often trade as strips.

The term strip refers to a set of adjacent months.

Except at short tenors, commodities usually trade as strips.

Seasonal strips are a collection of commodity specific adjacent months.

Calendar strips to the months in a calendar year. ”Cal12”, for example,

refers to the delivery period consisting of the twelve months comprising

the year 2012.

Strips typically trade at a single fixed price, even thoughindividual contract prices can vary significantly.

23 / 43



The fair-value of the strip m ∈ {M1, . . . ,M2} must satisfy:

M2∑m=M1

Nm [Fm − K ] d (t, τm) = 0

where:

τm are the settlement times

Nm denotes the monthly notionals (which in general are different due to

day count.

Therefore the fixed price for the strip is:

K =

∑M2m=M1

NmFmd (t, τm)∑M2m=M1

Nmd (t, τm)

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Options

Mechanics varies by commodity.

Common Themes

Options mechanics tend to mirror conventions for futures andswaps.Expiration can result in either financial settlement or physicalpositions.Expiry is usually ”close” to the contract month.

”MxN” options markets where expiry can be M units of time before

delivery at N are not traded.

Multiple Time Scales

Typically markets support options that exercise into monthly

exposure or into annual (cal strip) exposure.

For power daily options are commonly traded.

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Forward Yields

Backwardation and Contango

Backwardation: Forward price decreases with tenor(associated with supply stress).

Contango: Forward price increases with tenor (associated withsupply excess).

The following figures shows snapshots of forward curves forWTI and NG.

Note the variations in regime, including mixed states ofcontango and backwardation

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Forward YieldsSnapshots

WTI forward curve at a variety of dates:Note the range of prices as well as the changes in the monotonicity

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 201640

50

60

70

80

90

100

$/BBl

WTI Forward Curves

05−Jan−200605−Jan−200707−Jan−200805−Jan−200905−Jan−201005−Jan−2011

27 / 43

Forward YieldsSnapshots

NG forward curve at a variety of dates:Note:

The seasonality superimposed on macro trends.

The breakdown from the WTI price levels in recent years.

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 20214

5

6

7

8

9

10

11

12

$/MMB

tu

NG Forward Curves

05−Jan−200605−Jan−200707−Jan−200805−Jan−200905−Jan−201005−Jan−2011

28 / 43

Forward Yields

The Carry Formalism

Forward curves can be viewed as yield curves.

Forward yield:

y(t,T ,T + S) =1

Slog

[F (t,T + S)

F (t,T )

]The forward yield annualized rate implied by borrowing to buythe commodity at time T and sell it at time T + S .

Negative forward yields imply that market participants arewilling to pay a premium for earlier delivery

This is effectively lending at negative rates.

This happens when supply is contrained.

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Forward YieldsThe Carry Formalism

Yields often exhibit extreme values.

The following is the WTI forward curve and forward yield forS = one month in early Jan2009.

2009 2010 201135

40

45

50

55

60

65

70

Forw

ard P

rice (

$/Barr

el)

WTI Forward curve: 15−Jan−2009

2009 2010 20110

50

100

150

200

250

Yield

(%)

WTI Forward Yields: 15−Jan−2009

30 / 43


Seasonality yields negative forward yields consistently forseasonal commodities.

2010 2011 2012 20135.5

6

6.5

7

7.5

Forw

ard P

rice (

$/MMB

tu)NYMEX NG Forward curve: 25−Jan−2010

2010 2011 2012 2013−150

−100

−50

0

50

100

Yield

(%)

NYMEX NG Forward Yields: 25−Jan−2010

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Forward Yields

The Carry Formalism

For purely financial assets the presence of decreasing forwardcurves presents an apparent arbitrage opportunity.

Why not short the commodity at the high prices andrepurchase at the low prices?

The answer is that you can, but that the lender of thecommodity, being fully aware of the term structure will chargeaccordingly.

In practice this deal structure, referred to as a ”park-and-loan”usually involves repo in the easy direction, namely buying inthe cheaper months and storing to the expensive months.

How does one address this specialness?

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Forward Yields

The Carry Formalism

Case 1: Investment commodity with no storage costs:

F (t,T ) = F (t, t)er(t,T )(T−t)

or more generally:

F (t,T ) = F (t,S)er(t,S ,T )(T−S)

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Forward Yields

The Carry Formalism

Case 2: Investment commodity with storage costs:

F (t,T ) = F (t, t)e [r(t,T )+q(t,T )](T−t)

where q(t,T ) denotes the instantaneous cost of storage.

Given that q(t,T ) ≥ 0 this would result in contango beingobserved almost universally; a statement at odds with thefacts.

The cost of storage is not exogenous.

Storage owners will charge what the market will bear

The cost of storage is in reality a function of forwards and volsas opposed to an input.

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Case 3: For a consumption commodity all we can state withcertainty is that:

F (t,T ) ≤ F (t, t)e [r(t,T )+q(t,T )](T−t).

Rationale: One can always buy the commodity at the spotprice and ensure storage to delivery at T .

Convenience Yield: Solely for the comfort of an seeingequality, this is often rewritten as:

F (t,T ) = F (t, t)e [r(t,T )+q(t,T )−η(t,T )](T−t).

All that can be ascertained from market data is q − η, which

makes the above representation more form over substance.

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Recall the forward yields for WTI shown shortly afterinception of the credit crisis:

2009 2010 20110

50

100

150

200

250

Yield

(%)

WTI Forward Yields: 15−Jan−2009

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Forward YieldsEffects of Inventory

Inventory levels and forward yields are intimately coupled.High forward yields (contango) incentives owners of storage to

inject—this occurs when there is a surplus.

Negative forward yields (backwardation) encourages withdrawals—during

times of scarcity.

The following figure shows OECD crude oil stocks.

2002 2004 2006 2008 20103700

3800

3900

4000

4100

4200

4300

4400

Millio

ns of

Barr

els

OECD Crude Oil Invetory

37 / 43

Forward YieldsEffects of Inventory

This figure shows the forward yield between the first two calstrips of the WTI forward curve yield versus inventory levels.

3700 3800 3900 4000 4100 4200 4300 4400−25

−20

−15

−10

−5

0

5

10

15

20

25WTI 1st/2nd Cal Strip Carry Versus Inventory

Millions of Barrels

Annu

alize

d Ca

rry (%

)

Backwardation (Carry<0)

Contango (Carry>0)

38 / 43

Forward YieldsEffects of Inventory: Forward Yields

Incentives: the huge credit-crisis contango resulted in amassive increase in the use of VLCCs store oil and refinedproducts.The figure shows the result outside of the Port of Singaporeduring Jan2009.

39 / 43

Forward Yields

Effects of Inventory: Benchmarks

The high dimensional nature of energy commodities requiresbenchmark pricing.

Prices of an array of products are referenced as a spread(basis) to ”liquidity centers.”

For crude oil the dominant global benchmarks are WTI andBrent.

In recent years there has been a massive decoupling of WTIfrom global crudes due to build-up of PADD2 (mid-U.S.)crude oil inventory.

This has resulted in serious concerns about the viability ofWTI as a benchmark.

40 / 43

Forward YieldsEffects of Inventory: Benchmarks

2005 2006 2007 2008 2009 2010 20115

6

7

8

9

10

11x 10

4

000s

Bbl

PADD2 Inventory

2005 2006 2007 2008 2009 2010 2011−5

0

5

10

15

20

USD/

Bbl

Brent−WTI 2nd Nearby

41 / 43

Forward YieldsEffects of Inventory: Benchmarks

This figure shows the scatter of the Brent/WTI basis versusPadd2 inventory.

5 6 7 8 9 10 11

x 104

−4

−2

0

2

4

6

8

10

12

14

16

000s Bbl

USD/

Bbl

Brent/WTI 2nd Nearby (Weekly Average) versus PADD2

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Conclusion

Summary

High volatility impacts deal valuation, hedging and creditexposure/capital requirements.

High dimensionality is an inherent feature of energy marketsrequiring benchmark pricing/hedging and often resulting in”residual incompleteness.”

Viewed as yield curves, energy forward curves can exhibit verylarge yields of both signs.

Inventory effects are a significant driver of forward yields (andconversely).

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Section1-Energy Commodities Intro

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