Presentation held at an EUCI conference describing how to deal with expected and unexpected uncertainty in the energy markets.

1. Managing Physical and Financial
Uncertainty
By Bjornar Eide
Director of Risk Management Sempra Energy Utilities
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2. Presentation / Discussion Overview
 Framing the issue
 Definition of uncertainty
 Understanding impact of uncertainty
 Structural methods available to quantify impact of uncertainty
 Mitigation techniques available to address uncertainty
 Strategic approach to “value of hedging” or/and mitigation of uncertainty
 Formulation of hedging objective and financial/risk parameters
 The importance of the “Cash Flow Base”
 Timing and execution/trigger techniques
 Hedging philosophy, organizational capability (programmatic, semi-dynamic, dynamic)
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3. FRAMING THE ISSUE
• Learning how to live with and embrace uncertainty has become an integral part of
strategic thinking in the US energy sector over the past 5 years due to the following
drivers;
• Divergence of business models
• State of deregulation / competitive environment
• Volatile fuel and regulated markets/environment
• Pressure on decreasing foreign energy dependence (physically and financially)
• Renewable energy focus
• Building business models with sustainable growth potential
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4. DEFINITION OF UNCERTAINTY
• “The expected and un-expected variability caused by internal and external factors
that drive earning and/or rates”
– Expected variability refers to normal market events (i.e. change in market prices)
quantifiable with standard risk measures at statistical confidence levels (VaR, EaR,
CFAR) to portray the probable impact.
– Un-expected variability refers to market events (i.e. event of default, price spikes, etc)
quantifiable with extreme value theory, stress tests, scenario analysis to describe the
potential impact.
– Internal factors refers to what can be reasonably controlled through internal governance
and pro-activeness in positioning, contractual formulations, etc.
– External factors refers to sudden changes in regulatory direction/focus, tax credits,
market dynamics, volatility, etc.
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5. UNDERSTANDING IMPACT OF UNCERTAINTY
• Important to understand the financial impact of expected and un-expected uncertainty on the
following;
• Business Models / Strategic direction
• Earnings
• Rates
• Major projects
• Main Questions
– Does our organization / regulated environment have the financial strength to withstand
expected uncertainty (probable ) and un-expected uncertainty (potential) ?
– How does the risk appetite and financial situation help describe the desired risk
philosophy and governance structure of your organization ?
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6. Impact of Uncertainty (2)
• Potential for adverse outcomes drives how the Risk Philosophy of the organization addresses
how to deal with expected and unexpected uncertainty.
• Risk adversity/appetite not a goal in itself, but rather a consequence of quantifiable studies,
capital allocation and insurance against bad outcome.
• Capital markets expectancy for company identity and return generation can help formulate
positioning for expected and unexpected uncertainty.
• Uncertainty can also lead to higher value if identified and utilized to flexibly respond to
unfolding events – real options
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7. Cone of Uncertainty
Real options View
Ownership and
Value
control of Managerial
Options Increase
Value
Traditional view
___________________________________________
“real options” by Martha Amram and Nalin Kulatilaka Uncertainty
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8. Structural methods available to quantify
impact of uncertainty
• Business Models / Strategic Direction
– Constant Financial Benchmarking and scorecards to evaluate strategic flexibility and direction
– Identify top strategic dependencies to enhance internal focus
– Sustainability testing of Earnings Growth projections
• Earnings
– Develop robust quantification/standardization of earnings component base through cash flow mapping
techniques
– Mark to market accounting capability or/and data-ware house capability.
– VaR, EaR, CFAR on an incremental basis for each component and across earnings base.
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9. Structural Methods (Continued)
• Rates
– Simulation of rate behavior utilizing Monte Carlo Techniques or/and descriptive inputs
(rate matrix)
– Identify tolerance band to be managed structurally with the help of standard Risk Measure (VaR, EaR,
CFAR)
– Monitor or create programs to manage rates
• Major projects
– Identify project variables
– Calculate an actuarial project VaR for top identified variables
– Translate project risk measures impact to financial metrics of project
– Monitor project VaR
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10. Mitigation techniques available
to address uncertainty
• When choosing potential mitigation techniques for uncertainty it becomes essential to
differentiate the approach between expected uncertainty and un-expected uncertainty.
• Mitigation techniques for expected uncertainty (probable) can be considered economic hedging
and are typically liquidity intensive and measured on the basis of immediate economic
impact/effect on the hedged items (delta, hedge ratio, dollar offset).
• Mitigation techniques for unexpected uncertainty (potential) can be considered insurance and
hedging are typically liquidity constrained and measured on the basis of insurance coverage /
guarantees associated with adverse events and therefore will typically not meet the same
stringent GAAP hedge effectiveness rules (Fair Value, Cash-Flow Hedge).
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11. Strategic approach to “value of hedging” or/and
mitigation of uncertainty
• Measurement of success an important issue up front in communication with process stakeholders.
• Important aspects to consider are as follows;
– Is the hedge in place to secure earnings/rates/asset value / project financials where expected risk could
results in adverse outcome ? (to protect fair value)
– Is the hedge in place to secure earnings/rates/asset value/ project financials where un-expected risk could
result in adverse outcome ? (to protect what if scenarios)
– Is it expected over time that hedging/timing decisions should be value added/accretive on a stand alone
basis ?
• Comparison against alternative portfolio benchmarks
• What are the expectations for return on capital allocation / liquidity allocation
– Does the portfolio contain type of positions (fair value) that if not actively managed will diminish with
time or/and can not be realized in the cash market (theta)
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12. Formulation of hedging objective and
financial/risk parameters
The hedging objective should identify the following elements:
1) What are the financial goals of the program (insurance, economic hedge) ?
2) What level of insurance / economic hedge will be provided (minimum, maximum, average guarantees) ?
3) How will compliance with insurance / economic hedge goals be measured (delta, capped, other) ?
4) Will the program cover all types of basis risk (location differences, cash flow expiry etc) ?
5) What are the funding requirements of the program (Max Liquidity, Credit VaR, Budgets etc)
6) What type of program will be put in place (programmatic, semi-dynamic, dynamic) ?
7) What are the triggers for the program (market, weighted cost of rates etc) ?
8) What are the organization execution guarantees put in place to support type of program ?
Formulation of a recommended approach should also include a review of the following:
 Earnings/rate aspiration in combination with stakeholder expectations (Markets)
 Expected Peer Competitiveness
 Liquidity Utilization (Max)
 Total Potential Cost/Impact of Program
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13. Hedging Alternative Quantification
Alternative #1 Alternative #2 Alternative #3
Liquidity $ 10.00 $ 15.00 $ 12.00
(Max in Millions)
Delta 12.00 11.00 13.00
(Initial in Bcf)
Delta 20.00 20.00 20.00
(Max in Bcf)
Hedge Program 12.00 12.00 - 15.00 11.00 - 25.00
(Cost in Millions)
Rate Level $ 11.45 $ 12.45 $ 10.85
(Stress + 30%)
Rate Level $ 7.45 $ 8.45 $ 7.85
(Stress – 30%)
All numbers in the table have been randomly generated
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14. The importance of the “Cash Flow Base”
• Cash flow mapping of linear and non-linear exposure vital for incremental understanding of
potential impact of hedge programs to cash flow base.
• Cash flow base capability should enable the organization to break down risk measures into the
following risk views;
A. Periodic components (buckets of time periods)
B. Location break down
C. Position type break down (linear/non-linear)
• Incremental hedges can be assessed by total portfolio impact, impact on option sensitivities
and liquidity (fund usage) to understand impact of proposed hedge programs/mitigation
techniques.
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15. Timing and execution/trigger techniques
Triggers of hedging programs or incremental hedge tranches can be broken down into the
following categories;
a) Market Price Triggers
i. Price Level
ii. Price level + Risk Factors (95% confidence, 2 standard deviations etc)
b) Fundamental Triggers
i. Days of carry (natural gas inventories), by season
ii. Number of accumulated heating degrees
c) Cost/Revenue Triggers
i. Portfolio VaR triggers (10day, TeVaR)
ii. Weighted cost of rates / IRR, NPV, RAPM
iii. % increase in weighted cost or rates / IRR
iv. Weighted cost of rate / IRR, NPV, RAPM plus risk factors
d) Technical Triggers
i. Momentum indicators (200 Day Moving Average, RSI, Stochastic etc)
ii. Price support/resistance triggers
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16. Hedging Methods
(programmatic, semi-dynamic, dynamic)
• Hedging methods can be broken into many categories, but what distinguishes the methods is
how they are constructed and the formulation of how dynamic the execution and maintenance
of the programs are. The following categories of hedge methods have been identified for this
presentation;
• Programmatic: The design of a transaction structure consisting of physical/financial
transactions which once executed pose no surprises and are in accordance with the hedging
objective where a predetermined outcome and use of funds has been identified through
simulation / risk slides.
• Semi-Dynamic: The design of programs where the base of the program is static (constant
set of transactions) while incremental parts of the program are determined dynamically by
market or other types of triggers (VaR, Weighted Cost of rates etc)
• Dynamic: The design of programs where the entire program is dynamic and at the discretion
of portfolio manager (s) within certain financial constrains
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17. Schematic Overview
of Hedging Methods
Programmatic: Semi dynamic: Dynamic:
Characterized by a Places an initial hedge Leaves the timing and
mechanical, predetermined tranche with a progressive composition of hedges at the
hedge plan execution based ramp up of the hedge volume discretion of the decision
on expected effectiveness; dependent on market signals, maker; focuses on after-the-
no ongoing maintenance; probability of price level fact success criteria such as
either predictable use of and/or expected weighted hedge ratio, dollar offset and
funds/liquidity or predictable costs; some focus on cost RAPM measures; manages
total cost to customer (i.e. effectiveness and/or use of use of funds with budget,
hedge-and-hold). funds. liquidity and/or VaR limit.
Passive Semi Active Active
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18. Risk Profile
(Programmatic)
SUMMARY: Buy calls to cap 55% of volume
at a predetermined level ($2.50 out of the
No Hedging money) portrayed by the risk diagram to the
Storage Only
left.
Storage + Calls Only
Customer Rates
PROS: Execution at initiation with no
maintenance required. Capped liquidity
demand. Very easy to explain – does not
depart from extreme event “insurance”
concept.
CONS: Low delta – possible for customers
(today)
to see material cost increases with no benefit
from hedges. Total max rate not guaranteed.
Market Prices No ability to react to changing conditions.
This is a programmatic example that provides insurance only. Protection primarily
or unexpected uncertainty .
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19. Risk Profile
(Programmatic with financing to cap 55% )
SUMMARY: The program consists of buying
calls of hedge volume at a predetermined level
($2.50 out of the money) financed by ($1.50
out of the money puts) and covered downside
of (-$2.25) portrayed by the risk diagram to the
left.
No Hedging
Storage Only
Similar to Calls only, but:
Storage + Calls
Customer Rates
+ Put financing
PRO: Significantly lower premium outlay. In
turn, call strikes can be reduced and premiums
raised, resulting in higher delta (bill protection
at lower price moves). Good approach to
compare with peers at most market points
except the most suppressed prices.
(today)
CON: Need to monitor liquidity risk during
price declines. Total settlement value of
Market Prices derivatives unknown.
This is a programmatic example of a hedge that provides both economic and insurance protection
for both expected and unexpected uncertainty.
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20. Risk Profile – Semi Dynamic
(Simulating the Market)
Build internal capability or procure external analysis
Concept:
• Hedging as an integral part of the business for adding value and/or reducing risk
• Detailed simulation of the entire market assuming competition on variable cost
• Simulation of electricity generation, and regional energy flows in the power market in order to
satisfy total demand at minimum costs
Model requirements:
• Detailed description of electricity system
• Updated information on all reservoir levels
• Marginal costs for all power stations
• Detailed and representative inflow statistics
• Detailed information on transmission system, regional load characteristics and variations in
demand over time
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21. Forecasting fundamental value of
Natural Gas prices (principle)
$/Mwh
Today’s physical equilibrium
of natural gas prices
(Mmbtu Value)
Reflect the range
of possible future
Price paths and spot prices
in the market
Time
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22. Fundamental market analyses require
$/Mwh extensive back-testing (example) Production
74 TWh
Predicted range of
spot prices depending Actual production
72 220 000
on production alternatives for entire power system
70
200 000
68
66
180 000
64
62 160 000
Average spot
60 price observed
Range of possible in the market
inflow alternatives 140 000
58
56
120 000
54
52 100 000
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23. Summary of Fundamental Approach
• Fundamental view of over-value or under-value against the current market (forward curve)
through quantitative forecasting methods forms the basis for hedging decisions and physical
optimization.
• The approach requires rigid structure and data ware-house capability to support calculation
methodology (regression, stochastic) and forecasting equations.
• Data series needs to be supplied to modeling phase in a very structured fashion.
• The approach requires extensive back testing capability of forecasted data against actual
results.
Semi-Dynamic
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24. Risk Profile SUMMARY: The program consists of buying
(Semi Dynamic) OTM calls to bring portfolio capped rate to
55%. Premium cost remains below budget.
Calls are converted in 2 stages to FPIs when
prices exceed preset market price
thresholds, and are re-converted to calls
when market prices fall below the same
No Hedging levels.
Strategy (Backstop)
Storage Only
PRO: Up front coverage with catastrophe
Customer Rates
insurance at low cost. Deltas increase with
Strategy (Expected) rising markets, yet potential settlement
losses on FPIs expected to be less than
traditional hedge-and-hold strategy.
Converted/re-converted call options
expected to result in reduced premium costs.
Added FPIs can be designed to exceed 55%.
(today)
CON: Expected net loss on hedge
instruments. Potential for Call-FPI to skip
Market Prices widely across the designated threshold
levels or otherwise to cycle back-and-forth
across the level, increasing settlement
Protect against both expected and unexpected uncertainty. losses.
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25. Risk Profile
(Dynamic)
The program consists of allocating a
progressive VaR (10$ million) to hedging
Prices activity whereby the hedging activity can only
lead to a positive delta impact of portfolio,
but need to guarantee a linear cap at certain
level Unrealized gains of executed hedges a
additive to allocated VaR (25%) while
$12.50 unrealized losses reduces allowable VaR by
75% stopping out ineffective use of funds
and capital for hedging purposes.
PRO: Market driven and highly visibility
$6.50 strategy to value of timing of hedges with the
ability to ramp up program driven by timing
success.
$5.75
CON: Need to monitor VaR and Liquidity
parameters within allocated capital.
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26. Designing Hedge Programs
Step 1 Frame the Hedging Objective
Step 2 Research possible alternatives
Step 3 Quantify impact of alternatives
Step 4 Recommend best fit alternative
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27. Hedging Output
(Risk Matrix)
Delta : 120,000 Mwh
Gamma : 30,000 Mwh
Theta :: 250,000 USD
VaR : 2.7 Mill
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28. Hedging Output
(Risk Slide)
Proprietary position example P&L movement of portfolio with each The overview can be constructed per strategy
(Combination of all strategies winter strip) incremental move of prices or as a combined strategy of all books
Data exhibited above for illustrative purposes
The left hand column shows the financial parameters
of the portfolio while any point within the matrix will
provide information about the value for each financial
parameter given the price level
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29. BIBLIOGRAPHY
• Bjornar Eide has been a Director of Risk Management for Sempra Energy Utilities
since September 2005. Bjornar oversees the risk governance structure for San
Diego Gas & Electric and Southern California Gas Company. He is a member of the
Risk Management Committee for each of the utilities, which is responsible for
managing each of the utility’s exposure to market, credit, liquidity and operational
risk. Bjornar has over 13 years of experience from energy markets, serving in a
variety of capacities in an international environment. Prior to joining Sempra Energy
Utilities, he worked as an independent strategic risk consultant for a variety of clients
in Europe and the US focusing on strategic risk management related issues and the
design of risk assessment capability. As a Director of Risk Management for NRG
(from 2000 – 2002) he built up the risk management department and during his four
year tenure with Statoil A/S as a portfolio manager, he actively managed positions
that involved petroleum products, crude, natural gas & electricity including the build-
up of the power marketing department. Eide holds an MBA in Finance from San
Francisco State University and a BA in Business Administration from California
Lutheran University.
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