Similarity and differences within
BANK and COMMODITY RISK MANAGEMENT
DONATO ABBATE
COMMODITY RISK MANAGEMENT
An Introduction to Commodities
Pricing Commodity Contracts
Calculating VaR for Commodities
Governance and Controls in Commodity Firms
Introduction
What is a Commodity?
A Commodity is….
• An article of commerce
• A transportable article of trade or commerce that can be bartered or sold.
• As defined in the Commodity Exchange Act,
• includes the agricultural commodities enumerated in Section 1a(4) of the
Commodity Exchange Act and all other goods and articles, except onions as
provided in Public Law 85-839 (7 USC § 13-1),
?!
Epistemology
• the word commodity came into use in English in the 15th
century, derived from the French word "commodité", similar in
meaning to "convenience" in terms of quality of services.
• The Latin root meaning is commoditas, referring variously to
the appropriate measure of something; a fitting state, time or
condition; a good quality; efficaciousness or propriety; and
advantage, or benefit
© Deloitte AG 2008
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Commodity Markets
The Rise of Commodity Trading
The earliest commodity trading took place thousands of years ago, however commodity instruments
and markets as we know them now developed in the US in the 1800’s.
• In the early 1800s, the local
farmlands and cattle industries
made Chicago a natural center for
transportation, distribution and
trading of agricultural produce.
• Gluts and shortages of these
products caused chaotic
fluctuations in price.
• A market emerged enabling trade
in "to arrive" or "cash forward"
contracts to protect grain
merchants from price volatility.
~400 BC
• The origins of futures
trading can be traced
to Ancient Greek and
Phoenician
civilizations
Source: Wikipedia
© Deloitte AG 2008
~1800
1848
• Chicago Exchange trades more than 70% of
its Futures contracts on its "Globex" trading
platform.
• It accounts for over 45.5 Billion dollars of
nominal trade (over 1 million contracts)
every single day in "electronic trading"
• Now commodity futures, options and other
derivatives are traded
• Trading was originally in
forward contracts
• The first futures contract
was written on corn, on
March 13, 1851.
1851
1865
• Forward contracts became standard,
however, most forward contracts weren't
honored by both the buyer and the
seller!
• In 1848, the Chicago Board of Trade
(CBOT), became the world's first
modern futures exchange.
-4-
• In 1865,
standardized
futures
contracts were
introduced.
1874
2006
• The Chicago Produce
Exchange was
established in 1874 and
renamed the Chicago
Mercantile Exchange
(CME)
Commodity Markets
Major Commodity Markets
Commodity markets are
markets where raw or primary
products are exchanged.
Major Futures Exchange
Table 1.6
Major Futures Exchanges in the World for 2003
EXCHANGE
Eurex (Germany)
Chicago Mercantile Exchange (USA)
Chicago Board of Trade (USA)
Euronext-Liffe (Netherlands)
Mexican Derivatives Exchange (Mexico)
Bolsa de Mercadorias e Futuros (Brazil)
New York Mercantile Exchange (USA)
Tokyo Commodity Exchange (Japan)
London Metals Exchange (UK).
Korea Stock Exchange (South Korea)
Sydney Futures Exchange (Australia)
National Stock Exchange of India (India)
SIMEX (Singapore)
International Petroleum Exchange (UK)
OM Stockholm (Sweden)
Tokyo Grain Exchange (Japan)
New York Board of Trade (USA)
Bourse de Montreal (Canada)
MEFF Renta Variable (Spain)
Tokyo Stock Exchange (Japan)
Total Top 20 2003 Futures Volume
Source: Futures Industry Association.
© Deloitte AG 2008
2003 Volume
(Futures Only)
668,650,028
530,989,007
373,,669,290
273,121,004
173,820,944
113,895,061
111,789,658
87,252,219
68,570,154
62,204,783
41,831,862
36,141,561
35,356,776
33,258,385
22,667,198
21,084,727
18,822,048
17,682,999
17,109,363
15,965,175
Top 20 %
Volume
24.55
19.49
13.72
10.03
6.38
4.18
4.10
3.20
2.52
2.28
1.54
1.33
1.30
1.22
.83
.77
.69
.65
.63
.59
2,723,882,242
100%
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The Organized Exchange
Not-for-Profit Organization Structure
• Members hold exchange memberships
or seats that allow them to:
•Trade on the exchange
•Have a voice in the exchange’s
operation
For-Profit Organization Structure
• Members receive shares or stocks.
• Demutualize
Commodity Markets
Clearinghouses
Buyer
Seller
Obligations without a clearinghouse
Obligations with a clearinghouse
Buyer
Clearinghouse
Table 1.7
Major
Futures
Clearing
Organizations
Major Futures Clearing Organizations
Clearinghouses
• Guarantee that the traders will honor their
obligations (solves issues of trust).
Seller
Clearinghouse
Affiliated Exchanges
The Clearing Corporation (CCorp)
US Futures Exchange and the
Merchants Exchange of St. Louis
Chicago Mercantile Exchange
Clearinghouse
Chicago Mercantile exchange
With clearing link to CBOT
• Each exchange uses a futures
clearinghouse.
Kansas City Board of Trade Clearing
Corporation
Kansas City Board of Trade
Energy Clear Corporation
Exempt Commercial Markets
• Clearinghouses may be part of a futures
exchange (division), or a separate entity.
MGE Clearinghouse
Minneapolis Grain Exchange
NYMEX Clearinghouse
New York Mercantile Exchange
New York Clearing Corporation
New York Board of Trade
The Options Clearing Corporation
OneChicago, NQLX, & option
exchanges
• Each trader has obligations only to the
clearinghouse, not to other traders.
• Due to 2000 CFMA, clearing
arrangements vary across industries.
• Clearinghouses are “perfectly hedged” by
maintaining no futures market position of
their own.
The London Clearinghouse
Exempt Commercial Markets and OTC
markets
Sources: The CFTC web site, www.cftc.gov.
© Deloitte AG 2008
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Terminology
Example Commodities
Alternatively Traded Commodities
Traditional, Exchange Traded Commodities
Agricultural (Grains,
and Food and Fiber)
Corn
CBOT
Oats
Rough Rice
Soybeans
Soybean Meal
Soybean Oil
Wheat
Cocoa
Coffee
Cotton
Sugar
CBOT
CBOT
CBOT
CBOT
CBOT
CBOT
NYBOT
NYBOT
NYBOT
NYBOT
Precious metals
Gold
Platinum
Palladium
Silver
Other
CBOT
NYMEX
NYMEX
CBOT
• Rubber
• Palm Oil
• Wool
• Poly
• Propolyne
Livestock & Meat
Lean Hogs
Agricultural
Products
CME
Pork Bellies
CME
Live Cattle
CME
Feeder Cattle
CME
Industrial metals
Energy
Copper
LME
Light, Sweet Crude
Lead
LME
Brent Crude
Zinc
LME
Tin
LME
Ethanol
Aluminum
LME
Natural Gas
Aluminum alloy
LME
Heating Oil
Nickel
LME
Gulf Coast Gasoline
Recycled steel Rotterdam
RBOB Gasoline
Propane
Uranium
© Deloitte AG 2008
NYMEX
ICE
CBOT
NYMEX
NYMEX
NYMEX
NYMEX
NYMEX
NYMEX
-7-
• Fresh Flowers
• Cut Flowers
• Melons
• Lemons
• Tung Oil
• Gum Arabic
• Pine Oil
• Xanthan
• Milk
• Tomatoes
• Grapes
• Eggs
• Potatoes
• Figs
Rare metals
• Germanium
• Cadmium
• Cobalt
• Chromium
• Magnesium
• Manganese
• Molybdenum
• Silicon
• Rhodium
• Selenium
• Titanium
• Vanadium
• Wolframite
• Niobium
• Lithium
• Indium
• Gallium
• Tantalum
• Tellurium
• Beryllium
Minerals and
Materials
• Asphalt
• Aggregate
• Arsenic
• Borax
• Boron
• Gypsum
• Asbestos
• Chlorine
• Fluoride
• Cement
• Sulfuric
• Acid
• Carbon
• Dioxide
• Flourspar
• Bromine
• Titanium
• Dioxide
Terminology
Basic market terms
Some Starting Price Terminology
Cash / Spot Price
Present delivery price of a given commodity being traded on the spot market.
Settlement Price
Average price at which a contract trades, calculated at both the open and close of each trading day. Used to determine
margin requirements.
Forward Price
Agreed upon price of an asset in a forward contract.
Date terminology
Pricing
Date
Prompt
Date
Trade
Date
0
T
Date on which the
contract is priced
© Deloitte AG 2008
Date on which the
transaction occurs
Date on which the buyer of an option will
buy or sell the underlying commodity if the
option is exercised
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Terminology
Market Situation
Contango vs. Backwardation
Contango
2,000.00
Formally, it is the situation where, and the
amount by which, the price of a commodity
for future delivery is higher than the spot
price, or a far future delivery price higher
than a nearer future delivery.
•
means a downward sloping forward curve
(as in an inverted yield curve): one says
that the forward curve is "in
backwardation" (or sometimes:
"backwardated").
Formally, is described as, the situation
where, and the amount by which, the price
of a commodity for future delivery is lower
than the spot price, or a far future delivery
price lower than a nearer future delivery.
© Deloitte AG 2008
10
Ja
n
09
Ja
n
08
Ja
n
07
Ja
n
06
Ja
n
05
1,500.00
Backwardation
•
F o rw a rd p ric e
Ja
n
•
describe an upward sloping forward curve
(as in the normal yield curve). One says
that such a forward curve is "in contango"
(or sometimes "contangoed").
Forward Price
•
F o rw a rd C u rv e A lu m in u m
M o n th
Notable examples of backwardation include:
•
Crude oil.
•
Copper circa 1990, apparently arising from market
manipulation by Yasuo Hamanaka of Sumitomo
Corporation.
•
NYMEX traded natural gas (May 2007).
•
FX: The Australian dollar, priced in Japanese yen
terms (AUD/JPY), 2006: Australian dollar bonds
pay much more interest at every point in the yield
curve than Japanese yen bonds
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Terminology
Futures Vocabulary
Margin and Settlement
Cash or m/sec deposited by investor with his/her broker
•
Initial Margin: funds required in a commodity account when a position either long (bought) or
sold (short) is established.
Initial Margin Call: margin call issued when a new position is taken.
•
Maintenance Margin
When margin reaches a minimum maintenance level, the trader is required to bring the
margin back to its initial level. The maintenance margin is generally about 75% of the initial
margin.
•
Daily Settlement
Process by which traders are required to realize any losses in cash immediately (marked-tothe-market). The losses are usually deducted from the margin deposit.
© Deloitte AG 2008
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Terminology
Futures Vocabulary
Lot
Delivery month
• unit of trading
• defined quantity (contract size), i.e. Brent 1,000
barrels, gasoil 100 mt on the ICE
• defined quality, delivery period, etc.
• refers to the period when physical delivery
can commence or cash settlement can occur
• set at monthly intervals (each month has a
letter code)
Minimum price movement (“tick”)
Last trading day
• minimum amount by which a quotation can
move in any one price movement.
• day when trading officially ceases
• majority of open positions are closed out prior
to expiry
•Example:
• min. mvt.
• value
• physical delivery follows last trading day.
Gasoil
25 cents
$25
Ask
Bid
commitment to sell at a specified price
commitment to buy at a specified price
© Deloitte AG 2008
Brent
1 cent
$10
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COMMODITY RISK MANAGEMENT
An Introduction to Commodities
Pricing Commodity Contracts
Calculating VaR for Commodities
Governance and Controls in Commodity Firms
Pricing Commodity Contracts
Commodity Instrument Pricing - The Basics
• Commodity instruments are different from other financial assets
because (originally) a physical product was delivered as part of
exercising the instrument.
• More recently commodity instruments have been developed which are
purely financial – ‘non-delivery’ or cash only instruments, which have
commodities as underlying assets.
• Commodity instruments have become widely popular for both
speculative and hedging purposes.
Some More Terminology
• The future date is called the delivery date or final settlement date.
• The futures price is the price which is agreed to buy or sell an asset at in
the future, without putting up any money now.
• The price of the underlying asset on the delivery date is called the
settlement price.
• The spot price of a commodity is the price at which the good can be sold
for immediate delivery
Characteristics of Commodity
Instrument Contracts
• (Most )short and long positions of
commodities contracts (with
delivery) match 1:1.
• Some commodities have seasonal
swings in price
• increases in price does not indicate
profit opportunities, the price can
rise and any rate lower than
(storage cost + interest rate)
Forward Price Formula
The forward price is given by:
where
F
is the forward price to be paid at time T
x
e
is the exponential function ( for calculating compounding interests)
r
is the risk-free interest rate
q
is the cost-of-carry
S(t) is the spot price of the asset
is a dividend which is guaranteed to be paid at time ti where 0 < ti < T.
Di
© Deloitte AG 2008
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A simplified form gives the
Forward price at time t.
(no dividends or cost-ofcarry)
Pricing Commodity Contracts
Future and Forward contracts
Future / Forward contracts
Futures
Forwards
What it Is:
What it Is:
An agreement to buy or sell an asset at a preagreed future point in time, for a pre-agreed
price.
Also an agreement to buy or sell an asset at a
pre-agreed future point in time, for a pre-agreed
price, however no money or goods change hands
until the maturity of the contract.
Everyday, the contract is Marked to Market
Characteristics:
Characteristics:
• OTC contract (phone)
• Standardized contract traded on an exchange
• Customised contract
• Initial and variation deposits (margins) required
• Fixed price
• In most cases, physical delivery may occur.
Standard delivery location and period
• Liquid
• Standard contract
• No counterparty risk
• No commission
• No margin deposit requirement.
• Pricing formula
• Flexible delivery location and period
• Illiquid
• Counterparty risk
• Commissions paid
© Deloitte AG 2008
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Pricing Commodity Contracts
Basic Commodity Instruments - Forward Contracts
A Forward contract represents the agreement (an obligation) between two parties to buy or sell an asset at a pre-agreed
future point in time, for a pre-agreed price. No money or assets change hands until the contract reaches the final
settlement date. Forward contracts are not necessarily traded on an exchange, they may just involve an agreement
between two parties.
v( x ,t ) = e(
Contract > 0
Forward Price =
Spot Price
F(t) > F(o)
A long forward contract position is positive when the commodity
forward price is greater than the forward price at time t=0.
Forward Price
at t=0
at t=T
+$
Contract
Pay Off:
Forward
Price
= S(T) – F(o)
>0
0
<0
Time
Contract < 0 F(t) < Fo
A long forward contract is negative when the commodity forward
price is less than the forward price at time t=0
© Deloitte AG 2008
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>0
T
Pricing Commodity Contracts
Basic Commodity Instruments - Futures Contracts
A Futures contract represents the agreement (an obligation) between two parties to buy or sell an asset at a pre-agreed
future point in time, for a pre-agreed price. Everyday, following the close of trading the contract is ‘zeroed-out’ meaning
that the difference in the forward price during the day is paid out to/by the investors. The futures contract is then worth 0
at start of business the next morning. This is called ‘Marking to Market’ and requires that liquid collateral from both
parties be held by an independent intermediary. Futures are generally traded on a futures exchange.
Forward Price
at t=0
Marking to Market
Each Day Payoff
= F(t) – F(t-1)
F(t-1)
Pay Off at T:
F(T)= S(T) – F(T-1)
Forward
Price
+$
+$
0
© Deloitte AG 2008
1
-$
2
~0
3
-$
Time
(Days)
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+$
5
+$
-$
6
7
8
Pricing Commodity Contracts
Early Commodity Instruments - Black Model for Commodity European Options
The holder of a commodity option has the right but not the obligation to purchase (sell) a fixed quantity of a specific
commodity at a fixed time in the future at a specified price. European Commodity Options are exercised only at maturity
and not before hand
Valuing Commodity Options using Black 1976 Model
•
The volatility of the commodity price is estimated as constant σ²
•
The contract is valued as a function of the futures price and time
•
A riskless position can be created by taking a long position in the option and a short position in the related futures
contract with the same maturity date.
• Solving for the option value gives the European Commodity Option:
• Note compared to the typical European option solution, a factor of Fe ( − rT ) is now just F because the investment in a
futures contract is 0, therefore causing the interest rate factor to drop out of the formula.
© Deloitte AG 2008
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Pricing Commodity Contracts
Pricing American Commodity Options
American commodity options can be priced using the model developed by G. Barone-Adesi and R. E. Whaley in the paper “Efficient Analytic
Approximation of American Option Values” (1987).
Goal of the paper
There does not exist any analytic solution to the pricing of American options. Usually, finite difference
methods are used to derive prices, but they are computationally expensive. The authors of the paper
aims at providing an approximation to the price of American options on commodities which is
accurate and does not require much computational power.
Generalities on American options
• Main feature: can be exercised before maturity.
• Objective of the holder: determine the optimal exercise time.
• This optimal time depends on the movements of the stock S.
If S is high enough to make the payoff of the option be larger
than its value, then it is worth exercising.
Otherwise, holding the option is more valuable than exercising it,
therefore it is better waiting.
• The optimal exercise time is given when S touches the
exercise boundary.
© Deloitte AG 2008
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Pricing Commodity Contracts
Pricing American Commodity Options
Quadratic approximation of American Call and Put values
Assumption: The cost of carry b is a constant proportional value.
Call:
• Let us call C(S,T) the American commodity option value and c(S,T) the European one. Both satisfy the following PDE:
1 2 2
σ S VSS + bSV S − rV + Vt = 0
2
• American options are at least as expensive as European options, and sometimes more when it is likely that there will be early exercised. The
early exercise premium is defined as
ε C ( S , T ) = C ( S , T ) − c( S , T ).
• After some transformations and approximations,
Above the exercise boundary, we have
It also satisfies the PDE.
C ( S , T ) is expressed as c(S,T) + A1(S, S*,b, r,T) for S below the exercise boundary.
C (S , T ) = S − K .
• The exercise boundary is found iteratively so that the price of the American option is continuous.
Put:
• Same approach: the exercise boundary is first iteratively determined as solution of an equation expressing the continuity of the Put price.
• Then, when S is above the exercise boundary,P( S , T ) =
p( S , T ) + A2 ( S , S *, b, r , T ) and when S is below the boundary, P ( S , T ) = K − S .
Conclusion
• Accurate method, quite quick to implement and use. Only the computation of the exercise boundary is not
straightforward.
• Very general. For b=r we obtain the price of an American stock option. For b=0 and S↔F we get the price of an
American commodity futures option.
© Deloitte AG 2008
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Pricing Commodity Contracts
More accurate models for commodity options
As for pricing equity options, the basic models present several big limitations, which can be overcome by more sophisticated models.
Lognormal Brownian Motions are not accurate to model fat tail distributions.
For stock prices this is a major criticism of Black and Scholes model.
Commodity prices have the following features:
• erratic behaviour (in particular electricity) due to their non-storable
nature and dependence on physical transmission networks.
• jumps, spikes and stochastic volatility
• mean-reversion
Another challenge is the limited market data available.
Literature:
• Bernard J.T., Khlaf L., Kichian M. and McMahon S, “Forecasting Commodity Prices: GARCH, Jumps and MeanReversion”, Working Paper 2006-14, Bank of Canada.
• Higgs H. and Worthington A.C., “Stochastic price modelling of high volatility, mean-reverting, spike-prone
commodities: The Australian wholesale electricity market”, Faculty of Commerce, Papers, University of Wollongong,
2006.
• Trolle A.B. and Schwartz E.S., “Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives”, NBER
Working Paper Series, 2006.
A last feature of some commodity futures and options is seasonality. See Richer M. and Sørensen C., “Stochastic
Volatility and Seasonality in Commodity Futures and Options: The Case of Soybeans”.
© Deloitte AG 2008
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COMMODITY RISK MANAGEMENT
An Introduction to Commodities
Pricing Commodity Contracts
Calculating VaR for Commodities
Governance and Controls in Commodity Firms
Calculating VaR for Commodities
Introduction to Measuring VaR for Commodities
Although traditional VaR modeling methodologies can be used to model VaR for commodity risk, modeling commodity
risk involves taking even more aspects into consideration due to some of the particular aspects of commodity
information.
VaR
The Value at Risk (VaR) indicates the loss within a given time horizon with a
given confidence level in normal market conditions.
The main features of the VaR include:
• VaR is an absolute risk measure (risk is quantified in absolute monetary
terms, not as a deviation to some benchmarks)
• VaR is a static measure (it assumes a static portfolio during the time horizon
of the analysis)
• VaR is an asymmetric measure (it only considers events with a an adverse
impact on the P&L)
The main use of the VaR include:
• Quantification, control and forecast of the market risks of products, portfolios
or organizational units
• Quantification of the risk adjusted performance of products, portfolios or
organizational units
The main components of the VaR include:
• Time horizon, (i.e. the time period of the analysis)
• Confidence level (i.e. the probability of not surpassing the VaR value in the
given time horizon)
• Risk factors (i.e. the market factors with an impact on the portfolio)
• Methodology (i.e. the algorithm for the vaR calculation. Standard
methodologies include parametric , historical and Montecarlo).
© Deloitte AG 2008
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Special Problems in
Commodity Risk Modelling
• Collecting data from illiquid
markets
• Markets can be very volatile
and instable
• Many non-market based
factors (such as political
events, and natural disasters)
have a large effect on prices
• It is difficult to impossible to
determine correlations
between commodities
Calculating VaR for Commodities
Empirical Modelling
In order to calculate the VaR, the historical prices of the commodities are considered.
© Deloitte AG 2008
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Calculating VaR for Commodities
Empirical Modelling
From the historical returns a distribution of the returns can be built
© Deloitte AG 2008
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Calculating VaR for Commodities
VaR
© Deloitte AG 2008
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Calculating VaR for Commodities
Example
© Deloitte AG 2008
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Calculating VaR for Commodities
Key Required Information
© Deloitte AG 2008
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Calculating VaR for Commodities
Key Information Flows
© Deloitte AG 2008
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Calculating VaR for Commodities
Comparison of VaR Methodologies
© Deloitte AG 2008
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Calculating VaR for Commodities
Comparison of VaR Methodologies
© Deloitte AG 2008
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COMMODITY RISK MANAGEMENT
An Introduction to Commodities
Pricing Commodity Contracts
Calculating VaR for Commodities
Governance and Controls in Commodity Firms
Governance and Controls in Commodity Firms
Top Down Approach of Governance and Controls
Best practice governance in Energy and Utility firms follows a top down approach.
enables
enables
Board of Directors
Discusses policies
with respect to risk
assessment and risk
management.
enables
Senior managementlevel risk oversight
committee (ROC)
chaired by a chief risk
officer (CRO):
Development of
strategic policy
development and
oversight
enables
The ROC, the CRO, and
the corporate risk
department:
They are organized to
support a risk
management
framework.
influences
Governance and
controls:
Enact organizational
setup, policies, and
procedures that
support the company’s
business, establish
SoD for front, middle,
and back offices.
influences
By formalizing
processes for front,
middle, and back
offices in this structure
and implementing a
written risk
policy, helps minimize
operational risk,
including conflicts of
interest.
influences
influences
© Deloitte AG 2008
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Governance and Controls in Commodity Firms
Oversight Function
The oversight functions follow a strategic, tactical, and operational corporate hierarchy. (This chart is not intended to
depict an organizational structure, but rather to represent functional relationships and accountabilities.)
© Deloitte AG 2008
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Governance and Controls in Commodity Firms
Three Office Structure
The front, middle, and back offices - the “three-office” structure - has been patterned after that of the banking industry,
with adaptations to the intricacies of the energy industry.
Front Office
Middle Office
...executes the company’s
risk taking and risk
mitigation strategies. Frontoffice functions include deal
execution, initial capturing
and logging of a
transaction’s specific terms
and conditions, and other
transaction support roles
such as scheduling and
nominations. Executed
transactions have the
potential to expose the
company to significant
market, credit, liquidity, and
operational risk. Therefore,
an infrastructure of control
separate from that of the
front office is necessary to
monitor market participation.
Middle office functions
include assuring data
integrity through deal
validation and
confirmations, analyzing
and monitoring market and
credit risks, validating price
curves, and reporting risk
data to management, in
compliance with policies
authorized by the ROC.
© Deloitte AG 2008
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Back Office
The back office expands
the control environment
through balance sheet
maintenance
(reconciliations, accounts
receivable [A/R], and
accounts payable [A/P]),
settlements, and
financial reporting)
Governance and Controls in Commodity Firms
High-level Process Flow
© Deloitte AG 2008
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Governance and Controls in Commodity Firms
Support Functions
Support areas such as legal, internal audit, information technology, treasury, and tax play active roles in reducing the
business risk profile of a trading and marketing operation.
Legal
Internal
Audit
Legal
Legal support
support must
must be
be skilled
skilled and
and knowledgeable
knowledgeable in
in regulatory,
regulatory, contract,
contract, bankruptcy,
bankruptcy, and
and insolvency
insolvency laws.
laws. Legal
Legal support
support is
is
necessary
necessary when
when establishing
establishing new
new trade
trade agreements
agreements or
or contracts
contracts and
and resolving
resolving counterparty
counterparty non-performance
non-performance events.
events.
Legal
Legal should
should review
review trade
trade agreements
agreements and
and contracts
contracts for
for changes
changes in
in market
market practices
practices and
and applicable
applicable laws.
laws. Additionally,
Additionally,
legal
legal should
should evaluate
evaluate transactions
transactions to
to determine
determine whether
whether they
they are
are permissible
permissible under
under applicable
applicable laws
laws and
and regulations.
regulations. Legal
Legal
should
should also
also advise
advise the
the credit
credit risk
risk department
department on
on applicable
applicable bankruptcy
bankruptcy or
or insolvency
insolvency laws
laws and
and on
on the
the procedures
procedures
necessary
necessary to
to ensure
ensure enforceable
enforceable transactions
transactions and
and adequate
adequate documents.
documents.
Internal
Internal audit’s
audit’s minimum
minimum responsibilities
responsibilities in
in support
support of
of the
the trading
trading and
and marketing
marketing operations
operations include
include annual
annual financial
financial and
and
process
process audits
audits and
and reviews.
reviews. IfIf the
the ROC
ROC engages
engages outside
outside consultants
consultants to
to perform
perform process
process reviews,
reviews, reviews
reviews should
should be
be
coordinated
coordinated with
with internal
internal audit,
audit, and
and internal
internal audit
audit may
may be
be asked
asked to
to lend
lend support
support to
to those
those engagements.
engagements. Internal
Internal audit
audit
should
should conduct
conduct routine
routine audits
audits of
of trading
trading operations
operations to
to ensure
ensure compliance
compliance with
with controls,
controls, policies,
policies, and
and procedures.
procedures.
IT
Information
Information technology
technology (IT)
(IT) is
is critical
critical to
to trading
trading and
and marketing
marketing operation
operation in
in ensuring
ensuring that
that systems
systems are
are in
in place
place and
and function
function
so
so that
that transactions
transactions may
may be
be accurately
accurately captured
captured and
and reported
reported in
in aa timely
timely manner.
manner. A
A company’s
company’s IT
IT policy
policy supporting
supporting aa
trading
trading and
and marketing
marketing operation
operation must
must provide
provide for:
for: redundancies
redundancies for
for networks
networks and
and telecommunications
telecommunications failures;
failures; effective
effective
management
management of
of data
data (i.e.,
(i.e., reliable
reliable availability,
availability, integrity,
integrity, migration
migration across
across systems,
systems, development,
development, and
and maintenance
maintenance of
of tools
tools
to
to obtain
obtain and
and utilize
utilize data);
data); security
security of
of data
data and
and physical
physical location;
location; change
change control;
control; disaster
disaster recovery;
recovery; and
and business
business continuity
continuity
plans.
plans. IT
IT functions
functions should
should be
be performed
performed by
by personnel
personnel independent
independent of
of the
the front
front office.
office.
Treasury
Treasury’s
Treasury’s minimum
minimum responsibilities
responsibilities in
in support
support of
of the
the trading
trading and
and marketing
marketing operations
operations are
are cash
cash management
management activities
activities not
not
supported
supported by
by the
the back
back office.
office. Critical
Critical activities
activities include
include analyzing
analyzing the
the company’s
company’s liquidity
liquidity position
position (including
(including stress
stress testing
testing
and
and contingency
contingency planning),
planning), developing
developing interest
interest rate
rate curves,
curves, and
and hedging
hedging foreign
foreign exchange
exchange exposures.
exposures.
Tax
Tax
Tax support
support of
of aa trading
trading and
and marketing
marketing operation
operation requires
requires knowledge
knowledge of
of the
the tax
tax laws
laws of
of federal,
federal, state,
state, and
and (if
(if applicable)
applicable)
foreign
foreign governments.
governments. This
This knowledge
knowledge extends
extends beyond
beyond income
income tax
tax to
to sales,
sales, franchise,
franchise, excise,
excise, and
and other
other taxes.
taxes. Tax
Tax support
support
is
is necessary
necessary when
when seeking
seeking to
to enter
enter new
new markets
markets and
and to
to trade
trade and
and market
market new
new products,
products, including
including new
new types
types of
of financial
financial
instruments.
instruments. Tax
Tax support
support should
should determine
determine the
the effect
effect of
of changes
changes in
in tax
tax laws.
laws. This
This group
group also
also determines
determines the
the tax
tax effect
effect of
of
transactions
transactions (including
(including determining
determining the
the most
most efficient
efficient tax
tax structure
structure for
for transactions).
transactions). Tax
Tax support
support should
should also
also develop
develop
hedge
hedge identification
identification procedures
procedures that
that meet
meet tax
tax laws
laws and
and regulations.
regulations.
© Deloitte AG 2008
- 36 -
Governance and Controls in Commodity Firms
The Deal Life Cycle
The processes performed by energy trading and marketing companies center on execution, validation, risk management,
and accounting of individual transactions; together, these processes can be labeled as the life cycle of a deal.
Settlement &
Accounting Close
Reporting
Deal
Execution
Risk
Management
Deal
Validation
© Deloitte AG 2008
Each of these can be further
broken down in
• subprocesses,
• their objectives and
controls &
• key reports.
- 37 -
Governance and Controls in Commodity Firms
Risk Management – Sub Processes
Daily Risk Monitoring, price curve validation, risk control and analysis and credit risk management are considered to be
the risk management processes in the deal life cycle of a commodity firm.
Each day the middle office ensures that positions are captured
accurately and risks monitored. It begins with a review of the
risk reports to assess the activity from the previous trading
day, continues with monitoring positions, and concludes with
close-of-business lockdown to close system activity and
prepare the risk reports for processing.
Daily
Risk
Monitoring
Price curves are the primary driver of portfolio valuation, and it
is essential to ensure the accuracy of the prices. As such,
price curve validation is a key control performed by the middle
office, which should independently obtain market prices and
verify the accuracy of the forward curves for both market and
non-market years.
Price
Curve
Validation
The risk control and analysis process consists of verifying the
MTM valuation, calculating daily P&L, reconciling the P&L,
calculating risk measures such as VaR, EaR, and CFaR,
performing sensitivity analysis, performing stress testing,
analyzing liquidity risk, and calculating any other risk metrics.
Risk Control
And
Analysis
Analyze and set a limit on the amount of activity the company
is willing to transact with that counterparty, based on risk
tolerances. Later the exposure should be monitored. If there is
an overdraft, the credit department should verify and then
notify CRM and front-office senior management so that a
corrective action can be sought. Portfolio analysis is best
practice, as well.
© Deloitte AG 2008
Credit
- 38 -
Governance and Controls in Commodity Firms
Risk Management Process - Daily Risk Monitoring
Each day the middle office ensures that positions are captured accurately and risks monitored.
Objectives
• Ensure that positions are captured accurately and market risk can be continuously monitored.
• Support the best practice of segregation of duties and risk control.
Best Practices & Control
Reports
• Each morning, the middle office should verify that all overnight risk reports were
generated and review the reports for completeness, outliers, and limit violations.
• Limit violations should be communicated to the head of trading and the CRO.
• The middle office must ensure that actions are taken to become compliant with
defined limits.
• Throughout the day, the system should maintain real-time positions by
commodity, pricing point, and time period.
• Positions should be recorded in trading books and aggregated at the business
unit and corporate levels.
• Limit exposures should be monitored in real time as trading activity and curves
are updated in the system.
• Limit violation notifications should be sent to management throughout the day.
• At the close of each day’s business, the middle office should perform a
lockdown, validating the updated curves and trades, “locking down” the system,
and rolling the system date forward. The middle office should then initiate the
close-of-business risk report run (including positions, MTM, P&L, and VaR).
© Deloitte AG 2008
- 39 -
• Position reports.
• P&L reports.
• Limit compliance reports.
• MTM reports.
• VaR reports.
Governance and Controls in Commodity Firms
Risk Management Process – Price Curve Validation
Price curves are the primary driver of portfolio valuation, and it is essential to ensure the
accuracy of the prices.
Objectives
• Value transactions of the business using current market data and/or models.
• Ensure that forward price curves are reasonable and reflect reality.
• Ensure that curves are developed using sound methods approved by the middle office.
Best Practices & Control
Reports
• The middle office should validate each forward curve daily.
• Price discovery reports (broker
• Curve validation should include reviewing curves for outliers.
quotes, lectronic trading
• Validation is always performed by the middle office in both market and non-
platforms, data feeds).
market years.
• Price curve validation reports.
• Although the front office may be involved in the validation process, authority for
validation rests with the middle office.
• If the front and middle offices disagree on the price curve, it should be marked
to the price chosen by the middle office and later submitted for resolution by the
CRO or his or her assignee, with input from commercial management.
• For market years, inputs include broker quotes and transaction prices, along
with models for extrapolation and interpolation.
• For non-market years, the primary inputs are models, which should undergo
rigorous testing and assumption review.
© Deloitte AG 2008
- 40 -
• Model testing and validation
reports.
• Model user and technical
documentation.
Governance and Controls in Commodity Firms
Risk Management Process – Risk Control And Analysis
This process consists of verifying the MTM valuation, calculating and reconciling the P&L, calculating risk measures,
performing sensitivity analysis & stress testing, analyzing liquidity risk, and calculating any other risk metrics.
Objectives
• Standardize the types of risk measures and their method of calculation in a way that corresponds to industry best
practices.
• Ensure that transactions are valued appropriately & Gain an understanding of where risks concentrations lie in the
portfolio.
• Quantify the risks in the portfolio & Evaluate the profitability of an activity.
• Analyze the potential impact of changes in the market on the portfolio.
• Assess the return on the portfolio based on the amount of risk taken.
Best Practices & Control
Marking Transactions to Market
• On a daily basis and change should be adequately documented and explained by new
deals, changes in reserves, roll-off of old deals, or changes in the Greeks.
• Should be calculated on both a nominal and a PV basis.
• Data: independent sources, or in-house prices should be adequately reviewed.
Developing Market Valuation Methodology
• Appropriate bid-offer levels & Mid Market valuation should be adjusted for expected
future costs
• Choice of appropriate market-based curves
• Option pricing should include market price, volatility curves and correlation curves.
Calculating Profit and Loss
• Components of revenue should be measured regularly and in detail
• P&L should be calculated daily
• P&L should include cumulative month-to-date and year-to-date results
Measuring Market Risk
• Consistent measures and comparison against market risk limits (VaR)
• Transactions containing embedded option exposures should be measured with Greeks
• Back-testing and stress testing methodology should include various levels and
corresponding the relevant guidelines
• Reporting on a daily basis and on all different levels
• Liquidity risk and concentration risk should be managed additionally.
© Deloitte AG 2008
- 41 -
Reports
• Position reports.
• P&L reports.
• Limit compliance
reports.
• MTM reports.
• Greek exposure
reports.
• VaR reports.
Governance and Controls in Commodity Firms
Risk Management Process – Credit
The credit process can be broken into establishing credit and limits, monitoring exposure and portfolio management.
Objectives
• Establish credit tolerances for the company & Evaluate all counterparties that do business with the company and
establish appropriate limits.
• Quantify the credit risks of the portfolio & Analyze the potential portfolio impact of changes to a counterparty.
• Protect the company against credit risk for counterparties with bad credit ratings, poor payment history, or risk of
insolvency.
• Maintain credit exposures within acceptable parameters &Provide the means to react to changing market and
counterparty conditions.
• Provide a sound internal control environment, with separation of duties between the front-office creation of a deal and
the verification of the counterparty by the credit department.
Best Practices & Control
• A corporate-wide credit policy should be established and approved by the ROC. This policy
should provide guidance on risk tolerance. It should include processes for establishing and
approving limits, methods for ensuring that contracts have adequate credit protection, and
procedures for monitoring exposure, maintaining collateral, and obtaining exceptions.
• Ratings should be established for all counterparties, and appropriate limits (including
concentration limits) should be set.
• Acceptable collateral should be negotiated up front and maintained throughout the duration
of the contract.
• Before deal execution, contract terms should be reviewed and approved by corporate risk
management to ensure that the credit risk can be managed adequately.
• Master netting agreements (including margining provisions) and multilateral clearing
platforms should be used when possible to minimize credit exposure.
• Credit exposure by counterparty should be calculated and reported at least once a day.
• This should include A/R, A/P, unbilled revenues, and MTM gains and losses on all positions.
• New trades should be monitored throughout the day to ensure compliance with limits.
• Credit limit violations should be reported immediately to the CRO and the front office.
• At least twice a year, periodic reviews of limits should be performed to assess whether
changes should be made.
• News articles, bankruptcy filings, legal actions, etc., should be monitored on a daily basis for
all established counterparties.
• Appropriate credit reserves should be calculated and recorded monthly.
© Deloitte AG 2008
- 42 -
Reports
• Rating agency
reports.
• P&L reports.
• MTM reports.
• A/R aging reports.
• Credit limit
compliance reports.
• Credit VaR reports.
Governance and Controls in Commodity Firms
Overview of Process in the „Deal Life Cycle“
Processes and subprocesses across a deal flow for a typical energy trading and marketing company for front, middle and
back office.
© Deloitte AG 2008
- 43 -
Governance and Controls in Commodity Firms
Policies and Procedures
Risk Policies and Risk Control Operational Procedures are the primary governing documents.
Risk Policy
Risk Control Operational Procedures
1. Policy Introduction
2. Oversight Responsibilities and Organizational
Structure
3. General Policy Statement
• Business objectives and strategies.
• Identified risks.
• Risk controls
• Trading products and approval.
4. Market Risk Management
• Market risk identification.
• Risk measurement.
• Risk limits, monitoring, and compliance.
• Valuation and model approval.
• Risk reporting.
5. Credit Risk Management
6. Non-Commodity Risk Management
1. Front-Office Processes
2. Portfolio Design and Management
3. Middle Office Processes
• Deal validation.
• Confirmation.
• Contract administration.
• Risk reporting.
• Risk analytics.
• MTM and valuation adjustments.
• VaR.
• Greek framework.
• Stress testing.
• Other risk measures.
4. Personnel Policies and Other Responsibilities
5. Limit Structure
6. Process to authorize exceptions.
7. Credit Risk Policy, Controls, and Limits
© Deloitte AG 2008
- 44 -
THANK YOU !
"This document is confidential and prepared solely for your information. Therefore
you should not, without our prior written consent, refer to or use our name or this
document for any other purpose, disclose them or refer to them in any prospectus
or other document, or make them available or communicate them to any other
party. No other party is entitled to rely on our document for any purpose
whatsoever and thus we accept no liability to any other party who is shown or
gains access to this document.”
Deloitte AG is a subsidiary of Deloitte LLP, which is the United Kingdom member
firm of Deloitte Touche Tohmatsu (‘DTT’), a Swiss Verein, whose member firms
are legally separate and independent entities. Please see www.deloitte.ch\about
for a detailed description of the legal structure of DTT and its member firms.
© Deloitte AG 2008
- 45 -
Governance and Controls in Commodity Firms
Drilling Down – Board of Directors
The board, which has oversight responsibility for the financial health of the company, must
oversee trading and marketing operations.
Responsibilities
• Establish appropriate board committees, with formal charters and director qualifications.
• Understand trading and marketing strategies and associated risk.
• Discuss guidelines and strategic policies that govern the process by which senior management and
the ROC assess and manage risks.
• Understand the company’s risk management objectives and risk tolerances.
• Discuss a strategic risk policy that establishes an overall framework for risk management.
• Discuss the company’s major financial risk exposures and the steps management has taken to
monitor and control such exposures.2
• Establish scope and frequency for management reporting to the board.
• Review compensation policies to ensure that they are structured so as to avoid incentives for
excessive risk taking (compensation policies are typically reviewed by a compensation committee).
© Deloitte AG 2008
- 46 -
Governance and Controls in Commodity Firms
Drilling Down – Risk Oversight Committee
Membership of the ROC includes, at a minimum, the CRO, CFO, and senior management. The ROC must develop
guidelines required to implement an appropriate risk management control infrastructure.
Responsibilities
• Review and approve the risk policy and oversee enforcement by corporate risk management and the middle office.
• Ensure that risk management objectives, risk tolerances, and limits are employed throughout the organization.
• Review and approve the risk management strategy proposals around each affiliate’s business plan. Each proposal should be reviewed for
strategic fit, risk exposure monitoring, and reporting and control requirements;
• Periodically review any risk management program approved in light of recent market changes, and ensure continued compliance with its
established guidelines. (Perform a detailed review at least once a year.)
• Formulate risk management strategy and policy necessary for new product or market implementation.
• Require and review regular risk reports prepared by the corporate risk management department and/or the middle office. These must include,
but need not be limited to, the following:
• Profits and losses (P&L), both realized and unrealized.
• Open positions.
• Limit utilization.
• Status of exemptions and exceptions.
• Credit utilization.
• Periodically engage an independent audit (internal and/or external) of risk control processes and procedures.
• Understand which trading activities are accounted for using mark-to-market (MTM) accounting and which using accrual accounting.
• Approve the level (from individual trader to front-office management) at which authority to conduct trades in both MTM and accrual books
resides.
• Hold formal ROC meetings at least monthly. Standing agenda items should include, but not be limited to, current trading strategy, review of
current exposure position, control requirements/enhancements, and review of counterparty credit exposure.
• Perform an annual review of trading policies and codes of ethics. This includes review of disciplinary actions upon violation of ROC policies
and procedures.
• Review the infrastructure supporting risk management (human resources, analytical tools, reporting procedures, etc.) and ensure that it
meets the requirements for risk oversight and compliance
• Review compensation policies to ensure that they are structured so as to avoid incentives for excessive risk taking
© Deloitte AG 2008
- 47 -
Governance and Controls in Commodity Firms
Drilling Down – The CRO
The CRO is a corporate officer position independent of the front office and reports to the ExB and BoD.
Responsibilities
• Perform responsibilities delegated by the ROC.
• Conduct ROC meetings.
• Engage the ROC in discussions regarding events or developments that could expose the company to potential
losses.
• Assess risks to the company in aggregate, by business unit, and by material business activities.
• Measure and report on the company’s risk profile.
• Develop, recommend, and administer corporate risk management and /or middle-office processes and procedures.
• Research, develop, test, and implement risk measurement methodologies and models.
• Recommend to the ROC specific risk limits consistent with the company’s risk management objectives, risk
tolerance, and risk management policy.
• Provide direction to the internal audit group, facilitating independent audits of risk control processes and procedures.
• Evaluate proposed transactions with respect to their potential impact on the company’s risk profile, consistency with
risk management objectives and risk tolerance, and compliance with risk management policy.
• Develop and monitor the implementation of provisions to the risk management policy, and oversee other risk
management processes and procedures established by this policy or otherwise by the ROC.
• Report to the board of directors and the ROC on the company’s compliance with its risk policy and risk management
in accordance with the risk policy.
© Deloitte AG 2008
- 48 -
Governance and Controls in Commodity Firms
Drilling Down – Corporate Risk Management
The corporate risk management department reports to the CRO. The department is responsible for implementation of,
administration of, and compliance with the company’s risk policy and risk management processes and procedures.
Responsibilities
• Develop and review systems and controls to measure risk.
• Monitor compliance as required by the risk policy, including aggregation of risks across the company and review of
the company’s overall risk profile.
• Review and recommend market risk and credit risk limits.
• Develop risk measurement techniques.
• Review and recommend for approval, risk measurement calculation and standardized position methodologies.
• Review curve validation and stress-test results.
• Evaluate the effectiveness of the risk metrics employed.
• Oversee the model development, validation, and testing process to ensure that market and credit risks are accurately
quantified.
• Recommend operational risk and business risk assessment guidelines.
• Review business unit returns relative to expectations and to the level of risk incurred.
• Assess valuation issues and perform or review analyses on the company’s overall risks, using specialized stress
tests and scenario analyses.
• Aggregate or consolidate risk measures into enterprise-wide market risk measurement.
•This includes reviewing the effectiveness of transaction processing systems and procedures relating to risk
measurement and overseeing adherence to risk policies, procedures, and limits.
• Assess and recommend the allocation of resources necessary for risk oversight and compliance (i.e., human
resources, analytical tools, reporting infrastructure, etc.).
• Coordinate and distribute independent market fundamental analysis.
© Deloitte AG 2008
- 49 -
Governance and Controls in Commodity Firms
Drilling Down – The Market Risk Function
The market risk function ensures consistency across the company, aggregates enterprise risk positions, and
economically allocates quantitative and other analytical resources.
Responsibilities
• Review and validate valuation methodologies, curves, and assumptions and develop risk measurement techniques.
• Review the effectiveness of transaction processing systems and procedures relating to risk measurement.
• Review daily risk reports prepared by the middle office.
• Produce all enterprise-wide market risk reports.
• Perform back-testing and stress testing of risk measures such as VaR, EaR, or CFaR3 at least quarterly.
• Perform exception, variance, and risk-adjusted return on capital (RAROC) analyses.
• Oversee adherence to risk policies, procedures, and limits.
• Evaluate and recommend appropriate measurement techniques for reserves.
• Participate, as staff, to the ROC and carry out committee requests.
• Participate in new product reviews.
• Aggregate or consolidate risk measures into an enterprise-wide measurement.
• Identify, assess, and inventory market risks in all business units; advise the ROC on risk issues.
• Assess the impact of new business opportunities, (new markets, assets, strategies, etc.) on the corporate risk profile.
• Develop and distribute independent market fundamental analysis.
• Review and approve market assumptions in significant new deals.
© Deloitte AG 2008
- 50 -
Governance and Controls in Commodity Firms
Drilling Down – The Credit Risk Function
To facilitate enterprise-wide credit risk assessment, measurement, and management, and to maintain efficiency, credit
risk management is best performed at a corporate level and independently from the front office.
Responsibilities
• Review and approve counterparties and transactions before execution in order to identify, measure, and price the
associated credit risk.
• Perform due diligence on issuers of counterparty guarantees, ensuring that they meet minimum credit standards.
• Coordinate review and execution of all counterparty documents with the business unit’s contract management group
and the company’s office of general counsel; negotiate directly with counterparties to ensure that credit risk is mitigated
through contractual arrangements.
• Using internal and external information sources, monitor counterparty credit events and industry/market trends for
potentially adverse effects on the counterparty’s credit profile.
• Calculate and report to the ROC credit exposures, credit risk metrics, and other requested information.
• Report, as required by the risk policy, any credit risk limit violation, loss notification, or other exception to the limit
structure.
• Administer collateral (i.e., margins, parental guarantees, letters of credit held or given).
© Deloitte AG 2008
- 51 -
Governance and Controls in Commodity Firms
Drilling Down – The Front Office
The front office executes the company’s risk taking and risk mitigation strategies. The front office’s functions include deal
execution—buying, selling, and hedging of physical commodities or financial instruments.
Responsibilities
General
• Seek ROC approval for participation in new products, markets, or services that meet the company’s business
objectives. Understand, sign, and comply with the ROC risk policy and all other company policies, including the
company code of ethics. Maintain confidentiality of information used in trading and risk management. Report violations
of company policies. Abide by any non-compete agreements. Develop and maintain documentation outlining standard
procedures for conducting business. Set up and maintain physical contracts in the operations systems.
Trading and Asset Management
• Ensure that traders have proper knowledge and understanding of the products they are authorized to trade.
• Understand and abide by ROC trading limits, authorized product rules, and restricted activities.
• Develop trading, hedging, procurement, and marketing strategies in compliance with ROC policy and procedures.
Execute all authorized trading, hedging, and marketing transactions. Comply with all personal trading restrictions and
limitations. Arrange for the exchange of physical commodities at/on the appropriate facilities (pipelines, plants, pools,
etc.). Trade only in approved market forums (ICOs, power exchanges, electronic trading platforms, exchanges, etc.).
Communicate the operational status of appropriate facilities (pipelines, plants, pools, etc.) to the organization.
Deal Entry and Logistics
• Input transaction detail into deal-capture system in accordance with established procedures.
• Acknowledge daily trading activity. Work with the middle and back offices to resolve errors on a timely basis.
• Ensure accuracy of transaction terms (including difference between nominated and confirmed volumes) in the dealcapture system.
© Deloitte AG 2008
- 52 -
Governance and Controls in Commodity Firms
Drilling Down – The Middle Office
The middle office is responsible for maintaining the overall control environment and assessing compliance with the risk
policy. The middle office provides a significant level of control and policing of the front office’s activities
Responsibilities
Risk Control
• Confirm all appropriate transactions within established industry standards. Establish a rigorous process to insure that
confirmations are sent and reviewed pursuant to contract terms. Errors should be resolved, and changes should be
communicated to appropriate personnel on a timely basis. Validate all transaction details to the relevant risk
management systems. Foster a cooperative error-resolution effort between front, middle, and back offices. Maintain
appropriate transaction detail and acknowledgement records. Develop and maintain documentation outlining standard
procedures for conducting business. Routinely check trader authority and reconcile that authority with the appropriate
external counterparties, exchanges, brokers, etc. Lead and/or support risk systems and infrastructure development
efforts. Provide staff support to the ROC. Maintain risk systems. Monitor compliance with policies, guidelines, and
limits; report violations. Identify weaknesses and opportunities for enhancement in the control environment;develop
solutions and implementation strategies. Approve and manage the trading book structure designed to accomplish both
front- and back-office objectives. Monitor and ensure the appropriateness of intra-book trades.
Risk Analysis
• Provide daily report of risk exposures (e.g., P&L positions and change drivers) to the ROC. Perform periodic backtesting and stress testing. Calculate MTM and risk metrics such as VaR, EaR, and CFaR of portfolios on a daily basis.
Analyze and explain changes in the portfolio. Calculate and monitor position Greeks.
Valuation
• Validate and model forward curves for all commodity exposures (market analysis). Access market quotes for MTM
assessment.
© Deloitte AG 2008
- 53 -
Governance and Controls in Commodity Firms
Drilling Down – The Back Office
Back-office functions include processes such as accounting, invoicing, dispute resolution, check-outs, actualization,
accounts receivable, accounts payable, tax reporting, financial reporting, and contract administration.
Responsibilities
• Perform financial accounting and compliance.
• Comply with tax rules and make appropriate tax elections.
• Account for hedging and derivatives activities.
• Record realized and unrealized gains and losses.
• Reconcile general ledger and cash positions.
• Reconcile margin accounts.
• Implement tax-hedge accounting policies and other regulatory tax requirements.
• Develop and maintain documentation outlining standard procedures for conducting business.
• Invoice counterparties.
• Resolve billing disputes.
• Perform daily/weekly/monthly checkout with counterparties.
• Develop and maintain documentation outlining standard procedures for conducting business.
© Deloitte AG 2008
- 54 -
Real World Examples
1.
An Example Project:
Commodity Risk in the Cacao Industry
© Deloitte AG 2008
- 55 -
An Example Project: Commodity Risk in the Cacao Industry
Introduction to the Project
A large commodity trader has implemented an In-House developed model for calculating the
Commodity Value at Risk.
• Requested a review of the model methodology and implementation
• Requested a review of the framework in which the model was implemented
Value at Risk at the Commodities Company
The Value at Risk (VaR) indicates the maximum loss within a given time horizon with a given confidence level in
normal market conditions. According to good practices, VaR is normally complemented with stress tests, in order
to assess the risk of extreme market scenarios.
The main features of the VaR include:
ƒ VaR is a measure of market risks (liquidity, credit, etc. not considered)
ƒ VaR is an absolute risk measure (risk is quantified in absolute monetary terms, not as a deviation to some
benchmarks)
ƒ VaR is a static measure (it assumes a static portfolio during the time horizon of the analysis)
ƒ VaR is an asymmetric measure (it only considers events with a an adverse impact on the P&L)
The main use of the VaR include:
ƒ Quantification, control and forecast of the market risks of products, portfolios or organizational units
ƒ Quantification of the risk adjusted performance of products, portfolios or organizational units
The main components of the VaR include:
ƒ Time horizon, (i.e. the time period of the analysis)
ƒ Confidence level (i.e. the probability of not surpassing the VaR value in the given time horizon)
ƒ Risk factors (i.e. the market factors with an impact on the portfolio)
ƒ Methodology (i.e. the algorithm for the vaR calculation. Standard methodologies include parametric , historical and
Montecarlo).
© Deloitte AG 2008
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An Example Project: Commodity Risk in the Cacao Industry
Objectives of the Review and Work Done
Summary of objectives
• Review the Value at Risk (VaR) model design and suitability for its intended usage
• Review the reliability of the VaR model outputs
• Preliminarily review the overall commodity market risk framework, with particular
attention to options and structure risks
Scope and Work Performed
Work Performed
Scope
Model design
and suitability
Output
reliability
1. A thorough review of the model design, theory, framework for,
and intended use of the model
2. Assessment of the chosen confidence level and time horizon
3. A review of the implementation of the model through a code
review of the H-VaR model
4. A plausibility check of the outputs of the model through a
comparison with a parametric vaR model
5. A review of the data collection process, review of historical data
and a full reconciliation of the October positions of BC Sourcing
Commodity
market risk
framework
© Deloitte AG 2008
6. A review of the of the commodity market risk framework in the
context of the GCRM Policy
7. A specific review of the preliminary concepts for the control of
the structure and option risks and a review of the limit setting
framework
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An Example Project: Commodity Risk in the Cacao Industry
VaR at the Commodity Trader- Example of the Group level Commodity Risk Report
Group Commodity Risk Report
Net position (in mt)
Limits
+/-
1)
Aug 06
Sep 06
Okt 06
December 2006
Nov 06
Dez 06
% of
Limit
35'000
26'463
28'404
24'090
22'540
27'600
79%
300'000
130'880
147'828
130'874
172'216
203'661
68%
Arbitrage
80'000
-60'746
-64'810
-75'090
-79'200
-79'917
100%
Cocoa Butter
14'500
-5'917
-5'436
-8'666
-471
3'047
21%
Cocoa Powder
5'000
3'031
3'894
3'665
3'940
4'697
94%
Cocoa Liquor
5'000
999
-150
-49
2'965
2'540
51%
-50'000
-12'790
-18'102
-25'814
-21'980
-15'275
31%
80'000
31'310
119'621
128'246
103'735
101'533
127%
2'000
-1'324
-1'976
-1'856
-1'458
-907
45%
Cocoa short/long in B.E.
Bean differential
Dairy
Sugar & Sweetener 2)
Nuts
1)
Approved by AFRQC as of January 17 , 2006 and valid as from February 1 , 2006
th
In the limit
2)
Seasonality long limit in July and August with a gradual take-off path (-30'000 MT/month) until end of December
Out of limit
© Deloitte AG 2008
st
- 58 -
An Example Project: Commodity Risk in the Cacao Industry
VaR at the Commodity Trader- Overview of Commodity Option Hedging Risk Analysis
Option Risk Analysis
Dezember 2006
CLOSING RATES
NYBOT
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
Mrz 07
$1'635
$1'350
59.3%
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
n/a
20
0
-20
-40
-60
-80
-100
OPTION SCENARIO P&L
-120
CHF 400
2
2
2
2
2
-140
-160
-180
-200--180
1)
Delta is the sensitivity of the options value to a 1 CHF equivalent terminal market price increase per MT.
2)
Vega is the sensitivity of the options value to a 1 % price volatility increase.
© Deloitte AG 2008
- 59 -
-180--160
-160--140
-0.025
0%
-272 per 1 % volatility increase
200
300
400
0
-100
-200
-140--120
Terminal market scenario
-300
-5%
CHF
Volatility scenario
35 per 1 CHF equivalent terminal market price increase per MT of beans
-3.75%
Vega (2)
CHF
100
-1.25%
Delta (1)
0.025
GREEKS
1.25%
-200
5%
Volatility
Scenarios
Terminal market scenarios
-CHF 200
Unchanged
CHF 200
-22
1
2
-25
1
2
-28
0
2
-32
-1
2
-36
-2
2
-CHF 400
-168
-172
-177
-182
-187
3.75%
(kCHF)
-5.0%
-2.5%
Unchanged
2.5%
5%
P&L impact in kCHFCHF
LIFFE
Terminal month
Terminal market
Strike
Implied call volatility
Terminal month
Terminal market
Strike
Implied put volatility
Terminal month
Terminal market
Strike
Implied call volatility
Terminal month
Terminal market
Strike
Implied put volatility
OPTION SCENARIO P&L
-400
-120--100
-100--80
-80--60
-60--40
-40--20
-20-0
0-20
An Example Project: Commodity Risk in the Cacao Industry
VaR at the Commodity Trader- Overview of Commodity Segments VaR Analysis
VALUE AT RISK REPORT
Dezember-06
BC Group
31.12.06
VALUE AT RISK
COMPONENT VALUE-AT-RISK
Component VaR
The 10 days VaR with confidence level 95% is:
Component %
Scenario
B.E.
-8'924'437
62%
30.11.2005
-17'513'913
ES
ES / VaR Ratio
1.96
DIFFERENTIAL
-2'082'071
14%
19.05.2004
-3'754'345
1.80
3%
19.04.2002
-567'304
1.38
54%
16.02.2004
-12'508'679
1.62
-14'373'021 CHF
EXPECTED SHORTFALL
BUTTER
The 10 days ES with confidence level 95% is:
-412'323
ARBITRAGE
-22'279'954 CHF
The ES is 1.55 time bigger than the VaR.
POW DER
P&L SCENARIO
-552'411
4%
04.11.2003
-842'196
1.52
CAKE
-81'417
1%
27.02.2001
-109'374
1.34
NIBS
-1'686
0%
09.02.2006
-3'625
2.15
-217'506
2%
23.01.2003
-349'121
1.61
LIQUOR
The scenario that triggers the VaR is:
-7'741'694
27 February 2004
NUTS
The P&L of the scenario is:
-354'185
2%
20.12.1999
-479'034
1.35
20%
07.04.2006
-6'782'979
2.36
-14'373'021 CHF
SUG & SWEET
The scenario that triggers the UpVaR is:
15 August 2005
The P&L of the UpVaR scenario is:
FLAVOR
16'407'512 CHF
EMULSIFIER
OIL & FAT
-2'878'637
-0
0%
15.06.2001
-0
2.32
-79'743
1%
11.04.2006
-251'732
3.16
-410'875
3%
06.04.2001
-957'404
2.33
10%
12.09.2002
-2'649'445
1.84
The UpVaR is 14% bigger than the VaR.
DIARY
-1'441'788
Sum of Component VaR
STATISTICS
Diversification effect
Mean
Std. Dev.
Skewness
Kurtosis
x x
-25'178'772
-46'769'149
43%
52%
25'886 CHF
10'570'438 CHF
0.7
19.0
31.12.06
12.01.2007
COMPONENT VALUE-AT-RISK
-30000000
-25000000
VaRamount
-20000000
-15000000
-10000000
-5000000
0
Sum of
Component
VaR
B.E.
SUGAR &
SWEETENER
DIARY
BUTTER
NUTS
Components of the BC VaR
© Deloitte AG 2008
- 60 -
CAKE
NIBS
An Example Project: Commodity Risk in the Cacao Industry
VaR at the Commodity Trader- Model Structure of the VaR Limit Setting Framework
Available equity to cover the
group commodity price risks
Available Equity
AFRQC
Board of Directors
1
2
Group VaR Limit
(CHF)
3
Group VaR Limit
GCRC VaR Limit
5
Reserve
(CHF)
4
GCRC
RRU Sourcing VaR
(CHF)
GCRC VaR Limit
(CHF)
RRU Limits
RRU Limits
RRU Limits
(MT)
GCRM Limit Setting Policy:
1)
2)
3)
4)
5)
© Deloitte AG 2008
AFRQC assesses the equity available and decides what is available to cover the Group commodity
price risks
On this basis the BoD sets Group VaR Limit (in CHF).
The AFRQC may decide to implement additional Group VaR Sub limits
GCRC defines the level of the GCRC VaR Limit needed for the Group’s normal business (in CHF).
If the GCRC VaR Limit is lower than the Group VaR Limit a‘Group VaR Reserve’ in CHF is created
- 61 -
An Example Project: Commodity Risk in the Cacao Industry
Sample Project Work - Analysis Performed Simple Comparison of VaR
As part of the project the calculated Historical VaR (H-VaR) was compared to a simplified Parametric VaR calculation,
this calculation was performed in Excel and Matlab
LIFFE2
NYBOT2 Ivory Coast Bohnen GBP/CHF USD/CHF
-0.030%
0.006%
-0.001%
0.001% -0.009%
1.940%
2.020%
1.73100%
0.472%
0.663%
Mean
Stdev
Correlation
LIFFE1
100.000% 80.074%
NYBOT1
80.074% 100.000%
Ivory Coast
99.942% 79.967%
GBP/CHF
-7.329% -4.832%
USD/CHF
-0.629% -10.052%
99.942% -7.329% -0.629%
79.967% -4.832% -10.052%
100.000% -7.437% -0.734%
-7.437% 100.000% 63.514%
-0.734% 63.514% 100.000%
Prices
GBP
USD
GBP
31.08.2006
806
1420
1958.58
Prices CHF
1746.6
1
10
1214
0
-10
Position
H-VaR
P-VaR
Variation %
Outright future
1803
1933
Arbitrage
1137
1214
Differential
97
134
Inventory
1822
1866
© Deloitte AG 2008
850
2065.5
VaR
Scenarios
CHF
- 62 -
-7%
-6%
-28%
-2%
CHF
2.43
1.23
An Example Project: Commodity Risk in the Cacao Industry
Sample Project Work - - Code Review of Historical VaR Model
H-VaR Engine Code Check - Overview
Stage 1: History 1.6
1. Control of the price time series through sample data check
2. Review of the interpolation procedure
3. Review of the price rebuilding procedure
4. Review of ordering and formatting procedures
5. Review of transfer of price time series within the model
Stage 2: History Loader 1.6
1. Basic control of data import and export Macro function code and
data loading procedures
2. Detailed review of return calculations
3. Detailed review of first derivative approximations for “DIFF”
Stage 3: Position Loader 1.6
1. Basic control of the data export Macro function code
2. Review of position transfer into the VaR Engine
3. Review of the template format
Stage 4: H-VaR Engine
1. Control of data in the VaR Engine
2. Control of H-VaR simulation procedure and Macros
3. Review of individual risk factor VaR calculation procedures
-Differential (“DIFF”)
-Arbitrage (“ARB”)
4. Review of entire portfolio VaR calculation procedures
5. Control of VaR and ES calculations
6. Control of Sub-Risk Factor Mapping
7. Review of time scaling
© Deloitte AG 2008
- 63 -
An Example Project: Commodity Risk in the Cacao Industry
Results- Assessment, Assurance and Recommendations
Assessment and assurance
X
Seriously deficient
Needs improvement
Basically controlled
Well controlled
• The suitability of the VaR framework for the intended usage was confirmed
• A positive assessment of the reliability of the Value at Risk Framework was given,
limited by the extent of the procedures performed:
1. A review of the code,
2. A plausibility check of the model output,
3. A review of the data collection process, and
4. A full reconciliation of the October 2006 positions
5. Review of the Risk Management Policies
Main recommendations
Reasonable assurance on the model reliability can only be achieved by a back testing
procedure, not yet in place. A back testing procedure consists in a comparison between
the ex-ante risk quantification and the ex-post P&L realization. It was noted that the overall
P&L and its components are not comparable with the total risk and the risk break down,
thus preventing the comparison between potential losses (risk) and realized results (P&L).
© Deloitte AG 2008
- 64 -
An Example Project: Commodity Risk in the Cacao Industry
Results- Model Design and Suitability
Gaps identified
Recommendations
• As no major issues were identified for
the suitability of the model none of the
recommendations are presented in this
presentation.
• No significant gap was identified
Assurance
• Based on the scope of our analysis, we can confirm that the model is properly designed
to reflect the commodity price risk in normal market conditions and in basic stress
scenarios.
• The suitability of the VaR framework for its current intended usage was confirmed.
• The 95% confidence level and 10 day horizon of the VaR is suitable for the current
application purposes.
• Assurances did not extend to the structure risk and option risk, which are not sufficiently
covered with the VaR Framework. The Group Risk Manager is in the process of
developing separate concepts and tools to properly quantify and control these
commodity risks.
© Deloitte AG 2008
- 65 -
An Example Project: Commodity Risk in the Cacao Industry
Results - Output Reliability
Gaps identified
Recommendations
• Implement a back-testing to obtain
assurance on the reliability of the
model results and to obtain assurance
that the limits set based on VaR are
inline with the risk appetite.
• Align the P&L to the VaR, as this is a
prerequisite for back-testing
• Review of sample risk data during
some audit.
Two significant gaps were identified
potentially affecting the model reliability:
• The lack of a back-testing procedure
• The lack of systematic controls to
ensure the reliability of data from
sources external.
Assurance
• To the extent of our analysis, reasonable assurance that the calculations performed by
the model are basically correct was given. However, reasonable assurance regarding
the reliability of the model results can only be obtained by setting up a back-testing
procedure, currently there is no procedure in place.
• Reasonable assurance that the positions are properly reported was given, however
assurance on the correctness of the positions delivered by the other units was not
confirmed.
© Deloitte AG 2008
- 66 -
An Example Project: Commodity Risk in the Cacao Industry
Results- Commodity Market Risk Framework
Gaps identified
Recommendations
• Finalize the option and structure risk
concepts, in our view two points
requiring management attention.
• Finalize and update the risk controlling
and reporting procedures.
• Overall commodity risk management
framework is in development.
• The VaR framework is an important
component of the overall risk
framework, but only addresses the
commodity price risk. The further
pursuit of other commodity risk
management tools and the finalization
of policies and procedures is central to
the solid and comprehensive
development of the commodity risk
management.
Assurance
•
The option and structure risks concepts, as reviewed in their current preliminary state,
are developing in an appropriate direction.
© Deloitte AG 2008
- 67 -
An Example Project: Commodity Risk in the Cacao Industry
Results- Performance Gap Mapping
4.2.3 Position Reporting
© Deloitte AG 2008
- 68 -
An Example Project: Commodity Risk in the Cacao Industry
Sample Project Work - Analysis Performed
The following table summarizes the issues addressed in the investigation along with the most important findings(for details on issues
categorization, please refer to section 7.1). A complete description of all issues is documented in the section 4 (Process Review, Gaps and
Recommendations)
Title
Process / area
Alignment with
VaR
P&L and
Framework
Backtesting
Reliability
Overall
Commodity
Risk
Framework
© Deloitte AG 2008
Description
Signif.
Reasonable assurance on the model reliability can only be achieved by a back testing
procedure, not yet in place. A back testing procedure consists in a comparison between
the ex-ante risk quantification and the ex-post P&L realization. Currently, we noted that
the overall P&L and its components are not comparable with the total risk and the risk
break down, thus preventing the comparison between potential losses (risk) and realized
results (P&L). Main differences include the return period considered (VaR: 10 days, P&L:
1 month) and the FX result (not considered in the VaR but considered in the P&L).
As no integrated trading system is in place, position data are delivered by the various
business units to the Corporate risk controller in standard templates, and as a
consequence no automatic data check is in place at central level. No gaps were
Position
identified for the risk position reporting of BC Sourcing, based on our process analysis
Reporting
and reconciliation work. Based on a previous work by the Internal Audit of BC of 2006,
there are evidences that risk positions reported by ESC were not inline with their actual
positions.
BC is in the process of defining a limit framework for its commodity trading business
based on VaR, on option limits, and in structure limits components. As this is a new
concept, it is not integrated into the risk policies yet. Regarding the preliminary
Commodity
framework, it is our opinion that s quantification of the structure risk in CHF instead of in
Risk Limits
MT should be considered. Although no major gaps in the preliminary work reviewed
have been identified, we classified this item as “B” because the finalization of a
commodity market risk limit framework should be a major point of management attention.
The current GCRM policy describes well the reporting and limit exceedence policies as
well as the general framework for the commodity risk management. We noted that the
risk policies do not address the risk controlling and reporting of the structure and option
Risk Controlling risks, as they are still in the development phase, and that there is no description of the
and Reporting break down procedure of the total VaR Limits to RRU Sourcing and to the other RRUs.
Although no major gaps in the preliminary work reviewed have been identified, we
classified this item as “B” because the finalization of a commodity risk controlling and
reporting framework should be a major point of management attention.
- 69 -
Ref
A/B
4.2.1
B/C
4.2.3
B
4.3.1
B
4.3.2