Australian New Breeze - recent developments in managing weather risk

1. Australian New Breeze- recent developments in managing weather risk Dr Harvey Stern, Bureau of Meteorology, Australia

2. The Australian Climate in Poetry 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 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 -

3. 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)

4. 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.

5. 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.

6. 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.

7. 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.

8. 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.

9. 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 month’s (or season’s) conditions might depart from normal.

10. 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.

11. 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.

12. Two Important Issues • Quality of weather and climate data. • Changes in the characteristics of observation sites.

13. 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.

14. 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.

15. 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.

16. 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.

17. 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.

18. 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”.

19. Specifying the CDD Call Option • Strike: 400 CDDs. • Notional: $100 per CDD (> 400 CDDs). • If, at expiry, the accumulated CDDs > 400, the seller of the option pays the buyer $100 for each CDD > 400.

20. Pay-off Chart for the CDDCall Option

21. Approaches to Pricing • Historical simulation. • Direct modeling of the underlying variable’s distribution. • Indirect modeling of the underlying variable’s distribution (via a Monte Carlo technique).

22. 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.

23. 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.

24. 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.

25. Cooling Degree Days (1855-2000) • The chart shows frequency distribution of annual accumulated Cooling Degree Days at Melbourne using all data:

26. Cooling Degree Days (1971-2000) • The chart shows frequency distribution of annual accumulated Cooling Degree Days at Melbourne using only recent data:

27. 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.

28. 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.

29. Pay-off Chart for Decile 4 Put Option

30. 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.

31. Evaluating the Decile 4 Put Option • 9 cases of Decile 1 yields $(4-1)x9x100=$2700 • 6 cases of Decile 2 yields $(4-2)x6x100=$1200 • 4 cases of Decile 3 yields $(4-3)x4x100=$400 • 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.

32. 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.

33. 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.

34. 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.

35. Pay-off Chart: 38 deg C Call Option

36. 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.

37. Historical Distribution of Outcomes

38. Evaluating the 38 deg C Call Option (Part 1) • 1 case of 44 deg C yields $(44-38)x1x100=$600 • 2 cases of 43 deg C yields $(43-38)x2x100=$1000 • 6 cases of 42 deg C yields $(42-38)x6x100=$2400 • 13 cases of 41 deg C yields $(41-38)x13x100=$3900 • 15 cases of 40 deg C yields $(40-38)x15x100=$3000 • 16 cases of 39 deg C yields $(39-38)x16x100=$1600 cont….

39. 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.

40. 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.

41. Evaluating theForecast Error Put Option • Historical simulation yields a suggested price of $67 for our put option. • Does today’s error influence the price? • Does tomorrow’s expected weather pattern influence the price?

42. Answering the First Question • Today’s error does influence the price. • If today’s forecast is an underestimate, then tomorrow’s is also likely to be, leading to a suggested option price of $75. • If today’s forecast is an overestimate, then tomorrow’s is also likely to be, leading to a suggested option price of $41.

43. Answering the Second Question • Tomorrow’s weather pattern does influence the price. • If tomorrow’s weather pattern is moderate anticyclonic NNE, tomorrow’s forecast is likely to be underestimated, leading to a price of $77. • If tomorrow’s weather pattern is strong anticyclonic NNE, tomorrow’s forecast is likely to be overestimated, leading to a price of $47.

44. 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).

45. 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.

46. 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.