Australian New Breeze - recent developments in managing weather risk

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Australian New Breeze- recent developments in
managing weather risk

• Dr Harvey Stern,
• Bureau of Meteorology, Australia

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The Australian Climate in Poetry

• I love a sunburnt country,
• A land of sweeping plains.
• Of rugged mountain ranges,
• Of droughts and flooding rains.
• Core of my heart, my country!
• Her pitiless blue sky.
• When sick at heart, around us,
• We see the cattle die -

But then the grey clouds gather, And we can bless
again. The drumming of an army, The steady
soaking rain. Verses from My
Country Dorothea Mackellar
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The words of O. G. Sutton

• The analogy between meteorology and astronomy is
  often made There is a closer resemblance, to my
  mind, between meteorology and economics. Both
  deals fundamentally with the problem of energy
  transformations and distribution - in economics,
  the transformation of labour into goods and their
  subsequent exchange and distribution in
  meteorology, transformation and distribution of
  the energy received from the sun. Both are
  subject to extremely capricious external
  influences.
• (from Mathematics and the future of
  meteorology, Weather, October, 1951)

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Outline of Presentation

• Special features of the Australian climate.
• Some recent developments in weather risk.
• Applications of weather derivatives.
• Utilising forecast accuracy and other databases.
• Ensemble weather forecasting.

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Introduction

• The meteorological community is becoming
  increasingly skilled at applying weather-related
  risk management products.
• Most of these products originate from the
  financial markets.
• It is the energy sector (in the USA) that has, so
  far, taken best advantage of the growing
  weather-risk market.

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Major Australian Climate Controls

• The moderating influence of the large body of
  water to the south.
• The Great Dividing Range, stretching from the
  tropics to the mid-latitudes along the eastern
  flank of the continent.
• The El Niño - La Niña phenomenon.

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The Australian Climate Risk

• Weather risk is one of the biggest uncertainties
  facing Australian business.
• - e.g. recently, a brewer blamed a decrease in
  earnings on the cool summer.
• We get droughts, floods, fire, cyclones
  (hurricanes), snow ice.
• Economic adversity is not restricted to disaster
  conditions.
• - A mild winter ruins a ski season
• - Dry weather reduces crop yields
• - Rain shuts-down entertainment construction.

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Some Recent Developments

• For many years, the power industry has received
  detailed weather forecasts from the Bureau.
• Now, Australia has joined the global trend
  towards an increased focus on the management of
  weather-related risk.
• The first instance of a weather derivative trade
  occurred about two years ago.
• A number of businesses have now moved into the
  trading of weather risk products, almost all
  over the counter.
• Recently, partnerships (such as that between
  Macquarie Bank and Aquila) have been formed.

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Weather Climate Forecasts

• Weather forecasts provide specific detail as to
  what one might expect over the next few days.
• Climate (anomaly) forecasts indicate how the
  forthcoming months (or seasons) conditions
  might depart from normal.

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Forecasts and Risk Management

• Weather forecasts may be used to manage risk
  associated with short-term activities (e.g.
  pouring concrete).
• Climate forecasts may be used to manage risk
  associated with long-term activities (e.g. sowing
  crops).
• These forecasts are based on a combination of
  solutions to the fundamental equations of
  physics, and some statistical techniques.
• With the focus upon managing risk, the forecasts
  are increasingly being couched in probabilistic
  terms.

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Weather-risk the Financial Markets

• Weather-linked securities have prices which are
  linked to the historical weather in a region.
• They provide returns related to weather observed
  in the region subsequent to their purchase.
• They therefore may be used to help firms hedge
  against weather related risk.
• They also may be used to help speculators
  monetise their view of likely weather patterns.

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Two Important Issues

• Quality of weather and climate data.
• Changes in the characteristics of observation
  sites.

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Securitisation of Insurance Risks

• The property and casualty reinsurance industry
  experienced several major events during the late
  1980s early 1990s.
• The ensuing industry restructuring saw the
  creation of new risk-management tools.
• These tools included securitisation of insurance
  risks.
• A third party issues these securities, which
  provide a return structured to peak if an adverse
  event occurs.

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Securitisation of Weather Risks

• Weather securitisation may be defined as the
  conversion of the abstract concept of weather
  risk into packages of securities.
• These may then be sold as income-yielding
  structured products.

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Weather Derivatives

• Weather derivatives are financial instruments
  that are utilised to manage weather ( climate)
  related risk.
• They are similar to conventional financial
  derivatives.
• The basic difference lies in the underlying
  variables that determine the pay-offs.
• These underlying variables include temperature,
  precipitation, wind, and heating ( cooling)
  degree days.

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An Early Example

• In 1992, the present author explored a
  methodology to assess the risk of climate
  change.
• Option pricing theory was used to value
  instruments that might apply to temperature
  fluctuations and long-term trends.
• The methodology provided a tool to cost the risk
  faced (both risk on a global scale, and risk on a
  company specific scale).
• Such securities could be used to help firms hedge
  against risk related to climate change.

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An Early Example (cont.)

• The cost of a call option contract on the value
  of a Futures Global Mean Temperature (GMT)
  contract was calculated.
• In determining the cost, the volatility of the
  GMT, calculated over 130 years of data, was
  applied.
• One application given was that of the cost of
  protecting against diminished industrial output
  as a consequence of global warming.
• Another application was protecting against
  decreased value of a manufacturer of ski
  equipment as a consequence of warming.

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Another Example

• A common example is the Cooling Degree Day (CDD)
  Call Option.
• Total CDDs in a season is defined as the
  accumulated number of degrees the daily mean
  temperature is above a base figure.
• This is a measure of the requirement for cooling.
• If accumulated CDDs exceed the strike, then the
  seller pays the buyer a certain amount for each
  CDD above the strike.

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Specifying the CDD Call Option

• Strike 400 CDDs.
• Notional 100 per CDD (gt 400 CDDs).
• If, at expiry, the accumulated CDDs gt 400, the
  seller of the option pays the buyer 100 for each
  CDD gt 400.

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Pay-off Chart for the CDDCall Option
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Approaches to Pricing

• Historical simulation.
• Direct modeling of the underlying variables
  distribution.
• Indirect modeling of the underlying variables
  distribution (via a Monte Carlo technique).

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Significant Long-term Trends

• Some weather elements have trended significantly.
• Trends need to be considered when valuing weather
  securities (such as CDD Call Options).
• The trend in the minimum temperature at Melbourne
  (Australia) is shown here.

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Gentle Long-term Trends

• Some weather elements have trended only gently.
• Nevertheless, these trends still need to be
  considered when valuing weather securities.
• The trend in Melbourne maximum temperature is
  shown here.

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Elements that have not Trended

• Other weather elements have not trended, merely
  having undergone fluctuations due to natural
  variability.
• The example below shows the fluctuations in
  Melbourne rainfall.

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Cooling Degree Days (1855-2000)

• The chart shows frequency distribution of annual
  accumulated Cooling Degree Days at Melbourne
  using all data

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Cooling Degree Days (1971-2000)

• The chart shows frequency distribution of annual
  accumulated Cooling Degree Days at Melbourne
  using only recent data

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Pricing the CDD Call Option

• The two CDD frequency distributions are quite
  different.
• Utilising the different data in valuation results
  in different prices.
• Utilising 1855-2000 data yields a price thus
  (.051x2500.045x7500.008x12500) 565.00
• Utilising 1971-2000 data yields a price thus
  (.238x2500.119x7500.029x12500) 1850.00
• The more recent frequency distribution should
  provide a more relevant result.

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An Option linked to a Climate Index

• Suppose we define a rainfall put option, to apply
  when the Southern Oscillation Index (SOI) is in
  the lowest three deciles.
• Location Echuca.
• Strike Decile 4.
• Notional 100 per decile below Decile 4.
• - If, at expiry, the rainfall Decile is less
  than 4, then the seller of the option pays the
  buyer 100 for each Decile below 4.

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Pay-off Chart for Decile 4 Put Option
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Rainfall Distribution

• To value the put option one uses data giving
  actual distribution of rainfall for cases when
  the SOI is in the lowest 3 deciles.

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Evaluating the Decile 4 Put Option

• 9 cases of Decile 1 yields (4-1)x9x1002700
• 6 cases of Decile 2 yields (4-2)x6x1001200
• 4 cases of Decile 3 yields (4-3)x4x100400
• The other 25 cases (Decile 4 or above) yield
  nothing.
• leading to a total of 4300, and an average
  contribution of 98, which is the price of our
  put option.
• Later, a catastrophe bond, which may be issued to
  provide protection in the case of drought, will
  be described.

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Impact of Forecasts

• When very high temperatures are forecast, there
  may be a rise in electricity prices.
• The electricity retailer then needs to purchase
  electricity (albeit at a high price).
• This is because, if the forecast proves to be
  correct, prices may spike to extremely high
  (almost unaffordable) levels.

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Impact of Forecast Accuracy

• If the forecast proves to be an over-estimate,
  however, prices will fall back.
• For this reason, it is important to take into
  account forecast verification data in determining
  the risk.

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Using Forecast Verification Data

• Suppose we define a 38 deg C call option
  (assuming a temperature of at least 38 deg C has
  been forecast).
• Location Melbourne.
• Strike 38 deg C.
• Notional 100 per deg C (above 38 deg C).
• If, at expiry (tomorrow), the maximum temperature
  is greater than 38 deg C, the seller of the
  option pays the buyer 100 for each 1 deg C above
  38 deg C.

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Pay-off Chart 38 deg C Call Option
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Determining the Price of the38 deg C Call Option

• Between 1960 and 2000, there were 114 forecasts
  of at least 38 deg C.
• The historical distribution of the outcomes are
  examined.

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Historical Distribution of Outcomes
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Evaluating the 38 deg C Call Option (Part 1)

• 1 case of 44 deg C yields (44-38)x1x100600
• 2 cases of 43 deg C yields (43-38)x2x1001000
• 6 cases of 42 deg C yields (42-38)x6x1002400
• 13 cases of 41 deg C yields (41-38)x13x1003900
• 15 cases of 40 deg C yields (40-38)x15x1003000
• 16 cases of 39 deg C yields (39-38)x16x1001600
• cont.

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Evaluating the 38 deg C Call Option (Part 2)

• The other 61 cases, associated with a temperature
  of 38 deg C or below, yield nothing.
• So, the total is 12500.
• This represents an average contribution of 110
  per case, which is the price of our option.

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A Forecast Error Put Option (defining error as
predicted minus observed)

• Strike 0 deg C.
• Notional 100 per degree of forecast error below
  0 deg C
• If the forecast underestimates the actual
  temperature, then the seller of the option pays
  the buyer 100 for each 1 deg C of
  underestimation.

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Evaluating theForecast Error Put Option

• Historical simulation yields a suggested price of
  67 for our put option.
• Does todays error influence the price?
• Does tomorrows expected weather pattern
  influence the price?

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Answering the First Question

• Todays error does influence the price.
• If todays forecast is an underestimate, then
  tomorrows is also likely to be, leading to a
  suggested option price of 75.
• If todays forecast is an overestimate, then
  tomorrows is also likely to be, leading to a
  suggested option price of 41.

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Answering the Second Question

• Tomorrows weather pattern does influence the
  price.
• If tomorrows weather pattern is moderate
  anticyclonic NNE, tomorrows forecast is likely
  to be underestimated, leading to a price of 77.
• If tomorrows weather pattern is strong
  anticyclonic NNE, tomorrows forecast is likely
  to be overestimated, leading to a price of 47.

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Other Applications(particularly applicable to
Australia)

• Purchase of put contracts to protect against
  reduced rainfall, by a generator of
  hydroelectricity.
• Purchase of call contracts to protect against a
  sequence of very hot days.
• Purchase of variable degree day contracts to
  protect against very high temperatures.
• Purchase of guaranteed yield contracts (based on
  relationships between wheat yield rainfall and
  temperature).

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Improved Forecast Methodologies for Risk
Assessment

• In order to obtain a measure of forecast
  uncertainty, there is an alternative to using
  historical forecast verification data.
• This is to use ensemble weather forecasts
• The past decade has seen the implementation of
  these operational ensemble weather forecasts.
• Ensemble weather forecasts are derived by
  imposing a range of perturbations on the initial
  analysis.
• Uncertainty associated with the forecasts may be
  derived by analysing the probability
  distributions of the outcomes.

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Concluding Remarks

• The sophistication of weather-related risk
  management products is growing.
• Australia has joined this new market.
• In evaluating weather securities, one may use a
  variety of data types, and take into account
  climate trends.
• Ensemble forecasting is a new approach to
  determining forecast uncertainty.