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Weather Risk Management
David Molyneux, FCAS
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Introduction
• Weather Risk - Revenue or profits that are
sensitive to weather conditions
• Weather Derivatives - Financial Products
that allow companies to manage or “hedge”
their weather related risk exposures
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Weather Derivative Basics
• Like Financial derivatives, Weather derivatives are
used to “hedge” risk
• The value of a Financial derivative depends on the
value of an underlying asset, index or commodity
• The value of a Weather option depends on the
value of an underlying weather statistic
• Weather Derivatives protect against abnormal
weather outcomes
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Weather Derivative Customers
• Utilities and energy companies
• Agricultural companies
• Municipalities
• Seasonal Clothing Manufacturers
• Ski/Beach Resort Operators
• Golf Course Management Companies
• Beverage Companies & Distributors
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Weather Derivative Risks
• Average Temperature - HDDs/CDDs
• Abnormal Temperature - # of Days above
100F
• Precipitation or snowfall
• Humidity
• Wind speed
• Riverflow
• Combinations of the above
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Heating and Cooling Degree Days
• Most temperature contracts in current practice are
based on Heating Degree Days (HDD) for winter
protection, and Cooling Degree Days (CDD) for
summer protection.
• HDD = Max (0, 65 F - average temperature in a
day)
• CDD = Max (0, average temperature in day - 65)
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How Weather Derivatives Work
• Pay off is based on a measurable index
(CDD, HDD, etc)
• Pay off is based on how the index performs
relative to a trigger or strike value - not on
actual loss
• Coverage usually has a defined maximum
limit
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Basic Option Terminology
• Weather Options pay off when the
underlying weather statistic is above or
below a certain “strike” value
• Put Options - pay if the weather statistic is
below the predetermined strike value
• Call Options - pay if the weather statistic is
above the predetermined strike value
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Option Payoffs
Put Payout
-5
0
5
10
Strike
Call Payout
-5
0
5
10
Strike
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Simple Example - Snow Removal
• Problem: The municipality of Fort Wayne, IN has spent
$3,000,000 to provide for snow removal for the upcoming
winter. This money will fund the equipment and labor to
remove 12 inches of snow. Because of overtime rules, the
municipality estimates that every additional1/2 inch of snow
leads to an additional $250,000 of snow removal costs.
• Solution: A Snowfall call option which pays $250,000 per
1/2 inch of snowfall above a strike of 12 inches to a
maximum of 20 inches.
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Snowfall Call Option
Call Option Features
Period = Nov-Mar
Strike = 12 inches
Limit = 20 inches
Tick= $250,000
Limit = $4,000,000
Price = $500,000
2.5
3.0
3.5
4.0
4.5
5.0
9 12 15 18
Inches of Snow
Rem
oval
Cos
t (M
illio
ns)
Hedged Costs
Unhedged Costs
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Snowfall Distribution
Snowfall Probability Distribution
0%
2%4%
6%
8%
10%12%
14%
16%
6 7 8 9 10 11 12 13 14 15 16 17 18
Inches of Snow
Below the Strike Above the Strike
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Removal Costs With & Without the Call
Inches of With Without Probability Snow Call Call4.0% 6 3,500,000 3,000,0005.0% 7 3,500,000 3,000,0007.0% 8 3,500,000 3,000,0009.0% 9 3,500,000 3,000,00010.0% 10 3,500,000 3,000,00012.0% 11 3,500,000 3,000,00015.0% 12 3,500,000 3,000,00012.0% 13 3,500,000 3,500,00010.0% 14 3,500,000 4,000,0008.0% 15 3,500,000 4,500,0004.0% 16 3,500,000 5,000,0003.0% 17 3,500,000 5,500,0001.0% 18 3,500,000 6,000,000
Average 12 3,500,000 3,465,000
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Effect of the Call Purchase
• If the total snowfall exceeds 12 inches - the
payoff from the call exactly offsets the
increased cost of snow removal
• Fort Wayne guarantees snow removal costs
of $3.5 mil
• Variability is reduced - although Expected
Cost is actually higher
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Pricing Weather Derivatives
Method 1 - Apply Structure to Empirical Data
– NCDC Historical Database
– Adjust the Historical Data
– Apply Derivative Structure to Adjusted Data
Method 2 - Simulation
– Fit a Probability Distribution to Adjusted Data
– Model Stochastically
Black Scholes does not work!!!
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Data Adjustments
• Station Changes– Instrumentation
– Location
• Trends– Global Climate Cycles
– Urban Heat Island Effect
• ENSO Cycles
• Forecasting
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Phoenix CDD Data
Phoenix CDD Data Jun-Sept
2200
2400
2600
2800
3000
3200
3400
3600
1949
1953
1957
1961
1965
1969
1973
1977
1981
1985
1989
1993
1997
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Phoenix CDD Data - Adjusted
Phoenix CDD Data Adjusted for Trend
2200
2400
2600
2800
3000
3200
3400
3600
3800
19491952195519581961196419671970197319761979198219851988199119941997
Original Adjusted
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Phoenix CDD Call Graph
2200
2400
2600
2800
3000
3200
3400
3600
1949
1953
1957
1961
1965
1969
1973
1977
1981
1985
1989
1993
1997
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Phoenix CDD Call - Impact of Data Adjustments
CDD Call Structure
Period = Jun-Sept
Strike = 3,200
Tick = $10,000
Limit = $2 mil
All Year Expected Loss
•Based on Unadjusted
Data:
$826,000
•Based on Adjusted Data:
$1.3 mil
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Simulation Analysis
• Fit a Distribution to Adjusted Data
– Normal & Lognormal often work for HDD/CDD
– Other Statistical Models can be used for Percip,
etc.
• Fit can be focused on area between strike
and limit
• Run simulation analysis
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Portfolio Management
• Diversify Geographically & Directionally
• Track Correlations Between Cities
• Manage Transactional & Aggregate Limits
• Hedging & Trading Strategies
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Future of the Weather Market
• Growth in the Overall Size of the Market
• Larger/Multi-Year/More Complex Deals
• International Expansion
• Expanded End User Market
• Imbedding Weather Derivatives in Insurance
or Other Types of Contracts
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