September 8-12, 2008. 1 Linz Kickoff workshop Power and Gas - - PDF document

September 8-12, 2008. 1 Linz – Kickoff workshop

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Power and Gas Markets

Challenges for Pricing and Managing Derivatives

Peter Leoni, Electrabel

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Outline

Power Markets:

• Spot Market
• Forward Market

Gas Markets Derivatives

• Plain Vanilla Products
• Exotic Products

Conclusions

POWER MARKETS

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Power Market

Electricity is unique:

• cannot be stored (flow commodity)
• No flavours
• Transport is limited
• Production = Consumption (auction)

Trading Power is relatively new 2 Different Markets

• Spot Market
• Forward Market

Power Markets – Spot Market

Day-ahead auction per market (~country)

• Power supply:

– Nuclear Power plants – Gas-fired power plants – Coal-fired power plants – Hydro-power plants – Transport Capacity (import) – …

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Power Markets – Spot Market

Day-ahead auction per market (~country)

• Power demand:

– Transport Capacity (export) – Industrials – Home users – …

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Power Markets – Spot Market

Day-ahead auction per market (~country)

• Auction for each hour of the next day
• Price = (Supply meets demand)
• Price is set by marginal cost
• Price reflects the consumption pattern

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Power Markets – Spot Market

CASE STUDY: NORDIC MARKET

• Considered as Very liquid
• Hydro-driven (closest to storability)

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Power Markets – Spot Market

Day-ahead auction per market (~country)

(example: Nordic System Price Pattern)

Linz – Kickoff workshop September 8-12, 2008. 10 10 20 30 0.8 1 1.2 1.4 WINTERWEEKDAY 10 20 30 0.9 1 1.1 1.2 WINTERWEEKENDDAY 10 20 30 0.8 0.9 1 1.1 1.2 SUMMERWEEKDAY 10 20 30 0.8 1 1.2 1.4 SUMMERWEEKENDDAY

Power Markets – Spot Market

Intraday Price Pattern

• Very weather-dependent
• Depends on type of day

(weekday/Saturday/Sunday/Holiday)

• Depends on Month
• Very volatile with respect to the ‘average’ profile
• Unpredictable

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Power Markets – Spot Market

Time Series of the Spot Price (Nordic)

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Daily Price Curve

Power Markets – Spot Market

Features:

• Very FAT tails
• Prices expected to be

– Higher in the winter / Lower in the summer – Higher during the Week / Lower during the weekend – Higher During PeakHours / Lower during offpeak (night)

• Mean-reversion(?)

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Power Markets – Spot Market

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• 1
• 0.5

0.5 1 50 100 150 200 250 300 350 400

• 4
• 2

2 4

• 0.8
• 0.6
• 0.4
• 0.2

0.2 0.4 0.6 0.8 1 Standard Normal Quantiles Quantiles of Power Returns QQ Plot of Power Returns versus Standard Normal

• 0.1
• 0.05

0.05 0.1

• 0.8
• 0.6
• 0.4
• 0.2

0.2 0.4 0.6 0.8 1 SX5E Returns Quantiles Power Returns Quantiles

Power Markets – Spot Market

1 2 3 4 x 10

4

20 40 60 80 100 120 HYDRO SYSTEM 1 2 3 4 5 6 7 x 10

4

500 1000 1500 2000 2500 NO HYDRO SYSTEM

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SPIKES FAT TAILS Hourly Price Curve

The need to manage Risk on the Spot Market

led to the development of the Forward Market

Power Markets

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Power Markets – Forward Market

Forward Contracts F(t, T1, T2):

• Price at time t for the commodity to be delivered (in

a constant ‘volume’ during the entire period [T1;T2]

• [T1;T2] = delivery period
• Payment done during the delivery period, usually

settled on a monthly basis (swap)

• Price is fixed and constant during delivery
• Forward price is an estimate of the AVERAGE

realised Spot price during delivery period.

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Power Markets – Forward Market

Delivery period is bucketed into

• Days – Weeks on the short-end of the curve
• Months / Quarters
• Years

Cascading Mechanism:

• 1 Year 4 Quarters
• 1 Q 3 Months
• 1M 4 Weeks
• 1W WEEKEND + DAYS

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Power Markets – Forward Market

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0.5 1 1.5 2 2.5 3 3.5 4 4.5 54 56 58 60 62 64 66 68 70 72 74 Forward Curve

Power Markets – Forward Market

Seasonality is very obvious in the Forwards Forward Market Organised in

• Exchange (Futures)
• Brokered OTC Market (very liquid and transparant)

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Power Markets – Forward Market

Some numbers on the Nordic Market:

• First liberalised Market in Europe
• About 150 players in the Forward Market
• About 15 (active) players in the Vol market
• About 3-5 option trades per day

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GAS MARKETS

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Gas Markets

Gas is storable to some extent

• Pipelines
• Day-storages

No Hourly market No spike-behaviour Still seasonal, still very fat tails, very physical

as well

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PLAIN VANILLA DERIVATIVES

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Derivatives: Plain Vanilla Products

Option Expires before delivery period starts Power:

• Options on Futures (Exchange)
• Swaptions: Options on the ‘Forward’ (OTC)
• ‘Liquid’ Markets: Nordpool, Germany

Gas:

• Options on Summer/Winter Forwards
• Strip of Options on Summer/Winter (most liquid)

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Derivatives: Plain Vanilla Products

Study (Koekebakker and Ollmar, 2005):

• Multifactor (geometric Brownian) forward dynamics
• 2 factors explain 75% of volatility of the forward

curve

• 10 factors capture 95%
• Low correlation between short-end and long-end

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Derivatives: Plain Vanilla Products

Typically only a few expiries per product Volatility ‘Term Structure’ refers to underlying

forward curve

• Short-end of the forward curve: HIGH VOL
• Long-end of the forward curve: LOW VOL

Seasonality in Volatility

• Winter Vol (relative) high
• Summer Vol (relative) low

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Derivatives: Plain Vanilla Products

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Derivatives: Plain Vanilla Products

Challenges for the ‘Plain Vanilla Options’

• Option market is thin (implied vol quotes not always

reliable)

• Implied Vol quoted according to bad model (model

for forwards rather than swaptions)

• Bid/Offer spreads in the underlying (hedging cost)
• Fat tails (as any market)
• Liquidity

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Derivatives: Plain Vanilla Products

Bid/Offer spreads for Forwards:

• Days: 0.75% - 5% (sometimes even 15%, for SUN)
• Weeks: 1.25% - 6%
• Months: 0.5% - 2% - 5%
• Quarters: 0.10% - 3%
• Cals: 0.25% - 2%

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Derivatives: Plain Vanilla Products

Liquidity in Forwards:

• Can dry up easily and fast
• Risk premium: implied vol is much higher than

realised vol (difference about 10%)

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Derivatives: Plain Vanilla Products

Underlying does not (yet) exist

• Strip of Options on Winter/Summer products
• 6 Options each expiring right before Monthly-

Forward goes into delivery

• Monthly forwards may not be traded at the time of

writing the option

• Basis Risk: “Hedging of Untradable Assets,”
• N. Vandaele, P. Leoni and M. Vanmaele (in preparation)

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Derivatives: Plain Vanilla Products

Skew is rather small About 15 players in the vol market

Linz – Kickoff workshop September 8-12, 2008. 33 0.7 0.8 0.9 1 1.1 0.516 0.517 0.518 0.519 0.52 0.521 0.522 0.523 0.524 Q4-2008 Nordic 0.8 1 1.2 1.4 0.47 0.475 0.48 0.485 0.49 0.495 Q1-2009 Nordic

EXOTIC DERIVATIVES

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Derivatives: Exotic Products

2 Examples and their risks:

• Hourly Option (power)
• Swing Option (gas)

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Derivatives: Exotic Products: Hourly Option

Specifications

• Strip of options expiring on the SPOT market
• For each hour of the day, for each day over the

period (typically 3 years), the owner has a right:

• Call/Put
• Fixed strike (can be floating as well)
• For each hour: ‘nomination’ or exercise has to be

decided on a day-ahead basis

• Settlement can be financial or physical

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Derivatives: Exotic Products: Hourly Option

Model - Risks:

• Year-to-Quarter-to-Month-to-Week-to-Day profile
• Intraday profile (hourly profile)
• Volatility on each scale

Challenges

• Pricing the product
• Hedging the product (profiles cannot be hedged

perfectly)

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Derivatives: Exotic Products: Swing Option

Swing Option:

• Very complex product in an imperfect market
• Traded very often because of physical nature of the

(Gas) Market

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Derivatives: Exotic Products: Swing Option

Specifications

• A certain volume of gas can be bought at Strike

Price (Call Option)

• Strike can be fixed/floating (oil-related)
• Nomination on day-ahead (or month-ahead)
• Constraints:

– Total Volume between Vmin and Vmax – Daily nomination between Dmin and Dmax – Monthly nomination between Mmin and Mmax

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Derivatives: Exotic Products: Swing Option

Challenges

• Usual model risks (fat tails, stochastic vol,…)
• American features: “Do I nominate today or do I

wait”

• Optimizing the nomination process within

constraints

• Correlation/Comovement across the curve
• Highly dimensional: daily level (sometimes hourly)

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CONCLUSIONS

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Conclusions

Derivatives in Power/Gas

• Combination of hedgable risk and unhedgable risk
• Discrete hedging to its fullest extent
• Liquidity premiums

Market is growing rapidly Physical nature cannot be forgotten Matching Spot Model and Forward Model

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