Carlos BlancoManaging Director, Analytic Solutions

Hedging and Risk Management in Energy Markets: A view from the top

• Founded in 2002 with 50 employees in Boulder, Oakland, and Bozeman• Seven integrated software products for operations, portfolio analytics, and planning• Consulting and custom analytical solutions

Proven and Broadly Adopted Differentiated Value: Utilizing Uncertainty in Decision Analysis

• Portfolio management• Generation asset

management• Hydro and renewable asset

modeling• Energy purchases and sales• CFaR, GMaR, EaR

• Optimal short-term dispatch and trading

• Short-term price forecasting

• Resource Planning• Asset Valuation• Cost vs. Risk• Renewable Energy and

BatteriesBatterySimm™PowerFlex™PS Resource Adequacy™

PowerSimm OPSOPERATIONAL STRATEGY

PowerSimm Portfolio ManagerPORTFOLIO MANAGEMENT

PowerSimm PlannerRESOURCE PLANNING

1 to 10 days 1 month to ≈ 5 years ≈ 6 to 30+ years

IntegratingPhysical & Financial

Financial• Forwards • Options• Structured

Transactions• Hedge Evaluation• Asset Valuation

• Asset Operations• Weather• Load• Renewables• Spot Prices

Physical

October 22, 2019

Hedging and Risk Management in Energy Markets: A view from the top

• Risk appetite, tolerance and limits

• Risk appetite statements: Combining downside risk metrics with upside opportunity metrics

• Identifying key stakeholder requirements

• Measuring risk and regret

• Why hedging programs often fail

• A framework to measure and manage the risk culture of the organization

RISK APPETITE, TOLERANCE AND LIMITS

Understanding and Communicating Risk Appetite. COSO. 2012

Risk Appetite, Risk Tolerance and Risk Limits

• Risk Appetite

o Amount of risk, on a broad level, an organization is willing to accept in pursuit of value. Each organization pursues various objectives to add value and should broadly understand the risk it is willing to undertake in doing so.

o Sets a limit beyond which additional risk should not be taken.

• Risk tolerances guide operating units as they implement risk appetite within their sphere of operation.

o Risk tolerances communicate a degree of flexibility

• Key Risk Indicators (KRIs) can be defined to monitor risks and incorporate into corporate-wide controls

Hedging: Market, Credit, Margin/Collateral, Hedge Losses

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Overview of considerations affecting risk appetite

WillingnessRisk culture

AbilityCurrent portfolio

Risk Appetite Statements

• An organization’s risk appetite should be articulated and communicatedso that personnel understand that they need to pursue objectives within acceptable limits.

• A risk appetite statement effectively sets the tone for risk management.

• Without some articulation and communication, it is difficult for management to introduce operational policies that assure the board and themselves that they are pursuing objectives within reasonable risk limits.

• The organization is also more likely to meet its strategic goals when its appetite for risk is linked to operational, compliance, and reporting objectives.

• The length of a risk appetite statement will vary by organization.

• The aim is to balance brevity with the need for clarity.

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Characteristics of effective risk appetite statements (COSO)

Example: Portfolio Management at Exelon

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Risk vs UncertaintyLoss Avoidance vs. Value Creation

• Risk - often defined as chance of material loss event. Four letter word?

• What about Risk Management?

o Loss avoidance (risk minimization) vs. Value creation?

o Can we differentiate between speculative risk taking vs. a quality decision that involves taking calculated risk?

o How is the potential upside taking into account in making decisions?

o Is there a disconnect between risk takers and risk managers?

• Uncertainty – deviation from expected outcome

o Upside and downside included

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Deterministic Analysis: Budget projections, MtM and Stress Tests

Deterministic Analysis

1. Budget2. MTM3. Stress Test I4. Stress Test II

MTMStressTest I

StressTest II

BudgetBusiness Plan

(illustrative)

-$10.0 -$5.0 $0.0 $5.0 $10.0 $15.0 $20.0 $25.0 $30.0 $35.0 $40.0 $45.0 $50.0 $60.0 $65.0 Gross Margin

Accounting / Back Office / Risk Management

Stochastic Simulations:

1. Distribution

2. GM@R

3. Tail Risk

4. Better understandingof stress events.

5. Understand the impactof hedge strategies.

Probability distributions and stress tests

Xth

Percentile

GM@R

StressTest I

StressTest II

MTM Budget

Probability ofMeeting target

(illustrative)

-$10.0 -$5.0 $0.0 $5.0 $15.0 $20.0 $25.0 $30.0 $35.0 $45.0 $50.0 $60.0 $65.0 GMaR

Gross Margin Expected Tail Loss

Latest estimate

Cost at Risk Report

Risk appetite metrics and methodologies

Metric Sample Definition Methodology

Earnings volatility Our budget earnings forecasts will not be missed by more than X% with a confidence level of Y%

Earnings at Risk (simulation, stress tests)

Maximum quarterly loss

Our maximum quarterly loss should be lower than X million with a X% confidence

Economic Capital

Target debt rating Our combined S&P and Moody’s rating will stay above XXX

Stress tests on liquidity and solvency ratios

Liquidity headroom

Primary liquidity resource to meet current and contingent requirements will be higher than X% with a confidence level of Y%

Potential collateral requirements and cash flow at risk

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Identifying Stakeholder Requirements

Factor Impacting Tenor and Volume Decisions

Ability to respond to market changes

Stakeholder’s expectations

Risk tolerance and appetite

Market Liquidity (costs; proxy

hedges)

Accounting (hedge effectiveness)

Hedge Tenor and Volume

Firm’s Liquidity Position (funding, risk capital)

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Competitor’s strategy

Hedging vs. Speculation

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• Hedging – Economic activity in which parties try to protect against adverse price fluctuations in the market

• Speculation - Economic activity in which an entity attempts to profit from price movements (buy low, sell high…)

• Gray Area (“Hedgepeculation”)

o Influence of market views in decisions

o Tolerance between hedge min/max target volumes determined by Policy

o Timing of hedge decisions

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Are these legitimate reasons to hedge or not to hedge?(from an end-user perspective)

Reasons for hedging

• Reduce the effect of price volatility on our customer rates.

• A consistent way of “reducing” ex-ante expected rates or “making money”

• Avoid ex-post potentially disruptive cost extremes

• Mitigate a risk that you do not have any competitive advantage in managing.

• Gas prices are at historic lows, so we should lock in prices now

Some reasons for not hedging

• We are a conservative utility. We do not use derivatives.

• We don’t understand hedging and it’s difficult.

• We lost large amount of money hedging gas prices. We are done!

• We are not really responsible if prices move up and our customers have to pay more, we can’t control energy markets.

• Market expectations reflect continuation of low prices/volatility

Stakeholders are becoming more involved in the hedge strategy evaluation process

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Source: Colorado PUC

How do PUCs think about hedging programs?

Risk-based or “Risk-Responsive” Hedging

• Framework for risk mitigation informed by quantitative metrics

• Supported by robust analytical framework that fits the firm’s portfolio and markets where it operates - ‘meaningful uncertainty”

• Documented process with data-driven decisions supported by expert knowledge

o Provides confirmation of “prudent” decisions consistent with business strategy

o Allows to set hedge triggers based on risk limit breaches (e.g. budget level + P95)

o Responsive to market conditions

o Decisions supported by expert knowledge within risk limits

o Allow for evaluation of hedge outcomes vs. benchmarks

Alignment of Risk Metrics and Hedge ObjectivesSample: Electric Utility

• Uncertainty

o Net position (e.g. net buyer/seller)

o Renewable generation output

o Actual loads to be served

o Potential hedge gains/losses

• Portfolio

o Hydroelectric, Thermal, Renewable Resources

o Fixed Price gas and power contracts

o Index gas and power purchases

o District load (residential, industrial)

• Objectives

o Keep overall system costs low

o Keep customer rates low (system costs/actual load)

o Ensure net revenues (load-serving revenues – system costs) are sufficient to preserve the financial health of the district (e.g. credit rating)

o Limit potential hedge losses and counterparty risk

What forward looking risk metrics could we use to set tolerance?

Meaningful Uncertainty – Key Components

Feature Traditional risk models

Meaningful Uncertainty

Realistic, integrated and verifiable scenarios of key portfolio drivers

Accurate representation of physical and financial portfolio main attributes

Dynamic risk simulations incorporating portfolio response to simulated scenarios

Integrated analysis in one platform with robust, auditable, scalable and consistent analytics

Validations and Back-testing

PowerSimm reports a variety of validations to offer transparency to Simulation Results. Rigorous validation testing is performed as part of User Acceptance Testing (UAT). 24

Measuring Risk and Regret

Why Hedging Programs Fail

What happens after a hedge is place and the results are known? Risk vs. regret

• Risk is ex ante exposure to future volatility (unexpected potential variability)

• Regret is ex post disappointment if a hedge turns out to be more costly than not hedging would have been.

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Source: Brattle Group (2017)

Balancing Risk and Regret

• Tail risk tolerance

• Acceptable potential regret (e.g. hedge losses)

• Acceptable zone of indifference

• Time horizon of hedging decisions

Problem Reason

Ambiguity about objectives of hedging program

Why should we hedge?Who benefits from hedging?What are the key objectives behind hedge program?

Lack of benchmark How will the success of the program be measured?Without a benchmark, all eyes will be on hedges P/L Alternatives: VaR, CFaR, EaR, GMaR….

Limited understanding of hedging strategy by key stakeholders

Which stakeholders are involved in making, executing and reviewing the hedge program?Do they understand the outcomes and accept responsibility upfront

Poor communication and risk reporting

Risk reports at various levels (team executing hedging program vs. management vs. board level reports)Communication is key to get everyone on board

Why do hedging programs fail?

Risk appetite Questionnaires

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• Questions

• Tail risk loss limit

• Desired upside potential

• Tolerance for risks (e.g. zone of indifference)

• Budget for premiums

• Hedge horizons

• Level of acceptable hedge losses and margin/collateral

• Counterparty risk exposures

• Accounting considerations (e.g. hedge effectiveness)

A framework to measure and manage

the risk culture of the organization

Blanco, Hinrichs, Mark (2014) Creating a Risk Culture Framework. Part I and II. Energy Risk. Jul/Aug, Dec

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Characteristics and dimensions of an integrated risk culture framework

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Risk culture scoring process

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Risk culture dashboard

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Sample risk culture scorecards for selected energy risk management failures

Summary

• Risk appetite, tolerance and capacity

• Risk appetite frameworks and statements are needed

• Risk metrics

o Scope of portfolio is critical – Physical and Financial exposures

o Quality of simulation framework matters – meaningful uncertainty

o Choice of risk metric critical – cashflow, gross margin…

o Horizon (s) can match budget planning/business strategy KPIs

• Hedging and Risk metrics

o Risk-based hedging

o Objective benchmark

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Carlos BlancoManaging DirectorM:402.314.5620cblanco@ascendanalytics.com

Headquarters:1877 Broadway StSuite 706Boulder, CO 80302(303) 415-1400

Other Offices: Oakland, CABurlington, MABozeman, MT

Contact Information

U.S. Offices

Brief bio

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• Ascend Analyticso Managing Director, Analytic Solutions

• Faculty, MENNTA Energy Solutionso Derivatives trading, hedging, pricing and risk management courses worldwide

o 150+ publications (industry, academic)

• Prior experienceo Founder and managing director, Black Swan Risk Advisors

o VP, Risk Solution at Financial , Engineering Associates (FEA)

o Trader and Risk manager

o Platts M2M forward curves

o Lecturer. UC Berkeley, ABN AMRO

o Hedge fund macro research

o PRMIA Regional director

Captures how weather jointly drives increased volatility in renewable generation, loads, and energy prices

Simulate future conditions with “meaningful uncertainty” consistent with fundamental and new market dynamics

Unparalleled computing performance leveraging distributed computing

Hourly and subhourly chronological dispatch optimization honoring asset specific unique constraints

Stochastic simulation yielding robust probabilistic outcomes for risk metrics and informed M&A analysis

Assures confidence in results through hundreds of validation plots

What Makes Ascend’s PowerSimm Software Unique

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Gross Margin Distribution =

SUM Revenue (physical & financial)

LESS Costs (physical and financial)

Cost Distribution =SUM Supply portfolio costs

LESS Hedge Instrument P/L

Mean or Median?• Mean is more common for budgeting purposes

• Median is less influenced by outlier points (e.g., more stable)

Definition of Common Flow Metrics – “at-Risk” vs. “Conditional” metrics

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Conditional CaR

Conditional GMaR

Integrating Physical and Financial UncertaintyHybrid Modeling Framework

Fore

cast

ed m

onth

ly

forw

ard

pric

es

Durin

g d

eliv

ery

sim

ulat

ions

Weather Sim Renewables

Load Sim Spot Price Sim Calibrated Spot Prices

Forward Price SimPower, Gas, Coal, Oil,

Emissions, …

Optimal Dispatch

(Thermal, Hydro)

Hedge Instrument Valuation/Selection

Portfolio Summarization

Supply & Transmission

Unified simulation framework reflecting joint financial and physical uncertaintyo Rigorous validationo Capture of critical causal effects

Combines Financial and Physical Simulations

PowerSimm™Simulation Timing

Simulated Variable

Simulation Frequency

Forward Price Daily

Feb ContractsMarch Contracts

April Contracts

Weather DailyLoad HourlyGas Prices Daily

Generation Opt. HourlyAncillaries HourlyPeaking Assets HourlyPurchase/Sales Hourly

January February March April

Durin

g De

liver

y

Simulation Horizon

Forward ContractsPr

ior t

o De

liver

y

Electric Prices Daily Hourly

Prior to Delivery SimulationsCorrelated Forward Contracts

During Delivery Simulation

5 Day VaR

Reflects differences between “prior to delivery” and “during delivery” Distinct simulations of forward prices Convergence of forward and spot price simulations Captures structural relationships

Monthly

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Designing and Effective Risk Policy

Source: JPMorgan