Oxford University - Jan 2010 - UBS Global Warming Index - Weather Derivatives - ilija Murisic Keywords: auction, CDD, CME, derivatives, futures, global warming, HDD, ilija murisic, Index, UBS, UBS Global Warming Index, Weather

1. Course outline
Financial Time Series Analysis
• 1. Data analysis, probability, correlations, visualisation techniques
• 2. Time series analysis, random walk, autoregression, moving average
Patrick McSharry • 3. Technical analysis, trend following, mean reversion
patrick@mcsharry.net
www.mcsharry.net • 4. Nonlinear time series analysis
• 5. Nonlinear modelling, regime switching, neural networks
• 6. Parameter estimation, model selection, forecast evaluation
Trinity Term 2010
• 7. Volatility forecasting, GARCH, leverage effect
Dartington House Seminar Room 1
Mathematical Institute
• 8. Risk analysis, value at risk, quantile regression
University of Oxford • 9. Energy consumption, demand forecasting
• 10. Ensemble prediction, wind power generation
• 11. Weather derivatives, index-based insurance
• 12. Quantitative trading strategies, algorithmic trading
Lecture 11 Copyright © 2010 Patrick McSharry
Overview Carbon emissions
• Historical weather observations
• Future projections
• Weather indices
• Weather derivatives
• Index-based insurance
Source: www.globalwarmingart.com
Reconstructed temperature Global warming
Source: www.globalwarmingart.com Source: www.globalwarmingart.com
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2. British rainfall extremes
• British Rainfall (Symons, G. J.,1885) lists all observed 24 hour rainfall
depths which exceeded 2.5 inches (63.5mm). See Rodda et al. (2008)
Source: Wikipedia
Change in
Extreme rainfall trend
mean annual
temperature
by the end of
this century
Source: Little et al. (2008) Source: http://peseta.jrc.ec.europa.eu/
Change in Weather risk
mean annual
precipitation • Fluctuations in the weather affect the revenues of
many sectors (agriculture, energy, retail,
by the end of transportation and construction)
this century • Weather risk tends to influence demand rather
than price and adjustments of the latter are rarely
adequate to compensate for lost revenues
• Insurance offers cover for low-probability extreme
events but it does not provide compensation for
the reduced demand that may result from slight
variations in the weather such as the temperature
Source: http://peseta.jrc.ec.europa.eu being warmer or colder than expected.
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3. Electricity load and temperature Electricity and temperature
• Electricity demand displays a non-linear
U-shaped dependence on temperature
• Demand increases both for decreasing and
increasing temperatures
• This results from the use of electric heating
appliances in winter and air conditioners in
summer
• Pardo et al. (2002) analysed the dependence of
electricity load on a population weighted • There is a minimum around 18oC where the
temperature index in Spain demand is inelastic to temperature changes
Summer and winter regimes Heating and cooling degree-days
• The nonlinearity in the response function • Heating degree-day (HDD) and cooling degree-
prompted a separation of the effect into day (CDD) are indices designed to reflect the
summer and winter regimes demand for energy needed to heat or cool:
• Typically 18oC (or 65 oF) is used as a
threshold variable to switch between
summer and winter regimes
• HDD measures the intensity and duration of cold
• Within each regime, the response is in the winter
approximately linear which facilitates
traditional linear time series analysis • CDD measures the intensity and duration of heat
in the summer
Weather derivatives Weather and revenues
• Weather derivatives are financial instruments that • By creating a weather index that can be linked to the
can form a risk management strategy to mitigate revenues of a particular organisation, it is then possible
risk associated with adverse or unexpected to trade the weather in order to mitigate the risk of
weather conditions adverse weather conditions
• Unlike other derivatives the underlying asset • Advantages of decreased earnings volatility are efficient
(temperature, rainfall, wind, frost or snow) has no use of equity, improving the company value to
direct value stakeholders and availability of lower debt costs and
higher advance rates
• Weather derivatives, in contrast to insurance,
provide protection against low-risk high-probability • The Chicago Mercantile Exchange (CME) introduced
events by treating the weather as a tradable exchange-traded weather derivatives in 1999 and now
commodity, similar to a stock price or interest rate provides standardised contracts for 18 US, nine
European, six Canadian and two Japanese cities
www.cme.com/trading/prd/weather/
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4. Derivative pricing Energy utility case study
• If an energy utility believes that November may
• Approaches employed for pricing weather be hotter than usual, possibly leading to reduced
derivatives vary greatly, reflecting different revenues, it could take out a HDD swap
assumptions made about the variability of future • Suppose the reference was 18oC and the actual
weather conditions over the duration of the average temperature on each day was 16oC, the
contract utility would receive 60 (30 x 2) times the agreed
sum of money for each degree-day
• The disparity results from the availability of a
range of atmospheric and statistical models • Alternatively if the average temperature on each
day was 19oC, the utility would have to pay 30
• Further complications arise from the inclusion of (30 x 1) the agreed sum of money for each
the effect of El Niño in the model. degree-day
Restaurant case study Agriculture
• In May 2002, Element Re announced a new
weather derivative transaction with The Rock
• Farmers are exposed to financial risk arising from
Garden, a London restaurant. the variability in crop yield that occurs due to
• The contract was designed to protect the different weather conditions.
restaurant against financial loss from colder- • Crop yield and price are weather-dependent. In
than-normal weather from March 1-June 30. the case of corn, both temperature and
precipitation provide significant explanatory
• The contract will pay out if the maximum daily variables.
temperature is less than a pre-agreed level for
that month for more than a specified number of • Drought in particular presents a substantial risk.
days (8.5oC in March; 11oC in April; 14.5oC in Many farmers depend upon pre-financing against
their future revenue streams for seed, fertilizer, and
May; 18oC in June). other agro chemical products.
Global warming
Weather Risk Management index
• A survey carried out for the Weather Risk Management
Association by PricewaterhouseCoopers in 2006 • In April 2007, UBS launched a Global Warming index
concluded that: (UBS-GWI) allowing businesses most affected by the
• The total value of trades in the 2005/6 survey reached uncertainty of climate change to hedge their profits
$45.2 billion, compared to $9.7 billion in the 2004/5 against it in a simple and transparent fashion
survey • The index is based on weather derivative contracts for
• The CME experienced significant increases in both the winter and summer traded on the Chicago Mercantile
number of trades (increasing by a factor of 4) and the Exchange (CME)
value of those trades (increasing by a factor of 8) • The index is currently based on 15 US cities, including
• HDD remains most common type of trade New York, Chicago, Atlanta and Las Vegas
• If you think Mr Gore is an alarmist sensationalist, you
would sell the Index.
www.wrma.org www.ubs.com/globalwarming
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5. Appetite for weather derivatives Index-based insurance (IBI)
• “I think it’s a perfect market. You can’t spook it, you can’t • IBI is an innovative means of managing weather risk by
manipulate it. You can’t make people think it’s going to assessing risk in terms of expected loss of income by
be 110 degrees in London next week,” he says. “And of affected people whose livelihoods depend on agriculture/
course, weather is absolutely uncorrelated [to other farming that is highly susceptible to weather.
asset classes].” - Peter Brewer, Cumulus Weather Fund • Traditional insurance products are based on an
individual's circumstances and losses.
• No contract is too small. We’ve sold a weather derivative
contract for a dollar” - David Friedberg, Weatherbill • In developing countries or remote rural areas, traditional
insurance services may not be available because of high
• Weatherbill’s clients include car wash companies, hair administration costs.
salons and golf courses. “The other day one farmer rang • IBI is a more appropriate as it is based on a fixed trigger
me up and said his sows wouldn’t make a move to mate mechanism not directly related to any individual farm.
if the temperature went above 95 degrees Fahrenheit. This could be calculated on average crop yields, area
He wanted to hedge against that.” average livestock mortality rates, cumulative rainfall or
even data from satellite imagery.
Source: FT, 20 June, 2007
Implementing IBI Advantages of IBI
• Index-based insurance can be effectively delivered • Where traditional insurance products
through a wide range of products. aren't available (too costly or impractical)
• Government or international aid agencies can purchase
famine insurance based on a weather index tied to the • Where moral hazard is high
likelihood of droughts.
• A means of reducing risk exposure for
• Individual producers can purchase insurance privately
from insurance providers, local banks, NGOs or some vulnerable agricultural producers, giving
partnership of these. them confidence to invest in inputs and
strategies that will potentially give them
• Insurance clauses can be folded into loan agreements
whereby indexes triggered by adverse events relax the higher returns in other years.
terms of the loan or pay it off.
Livestock insurance in
How IBI works
Mongolia
• Crop- and area-specific estimates are • In Mongolia, livestock husbandry accounts for 87% of agricultural
GDP and supports at least half the population.
aggregated and mapped to income via price
• The country is prone to extreme climatic events that can cause high
estimates, and then converted into a livelihood rates of livestock mortality.
loss index. • The insurance sector is immature and under capitalised.
• Livestock insurance is a key element of risk mitigation but the
conventional approach, based on individual herder losses, has been
• If weather data gathered throughout the contract ineffective in Mongolian conditions. It has proved unpopular with
period indicates that rainfall was significantly both insurers and herders with a high cost of verification and moral
below historic averages the insurer pays out. hazard.
• The government has now introduced an indexed mortality product
which embraces risks exposure of the herders
• No moral hazard, no complication of counting • Risks are covered by the private insurance sector in Mongolia
dead cows. • A disaster recovery program is to be provided by Government
(maybe in years ahead by international reinsurers).
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6. Drought protection in
IBI challenges
Ethiopia
• Lack of accurate climate models in
• In 2006 the Ethiopian Government, in partnership with developing countries
the World food Program insured its farmers against
rainfall failure. • Limited availability of reliable and objective
• In return for a premium of US$930,000, the insurance data.
company would have paid out anything up to $7.1 million
in the case of severe drought.
• Lack of weather stations in remote areas.
• This money would have been given to the Ethiopian
Government on the condition that it would be used for • Models that make index-based insurance
emergency relief and recovery.
contracts attractive to both buyers and
• This means that the World food Program can rely on the
insurance money to pay for their relief work if there is a sellers.
climatic emergency, rather than having to depend on
donations, which can entail long delays.
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