1. Uncertainty in 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.

2. 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.

3. 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.

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

5. Determining the Price of the 38 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.

6. Historical Distribution of Outcomes

7. 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
Total 53 cases Total $12500
cont….

8. 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 ($12500/[61 cases (38 deg C or below)+53 cases (above 38 deg C) ]), which is the
price of our option.

9. Example from Aquila Business Situation
A wheat farmer has specific times during the year when his crops must sprayed with pesticide in order to ensure a healthy yield.
If there is substantial rain within a few days of application, the pesticide will wash away and will have to be reapplied.
Not only is the pesticide application a substantial part of his operation costs, but he also could miss his window and hit a season or growth cycle that is especially susceptible to pests if he is unable to reschedule the application.
In order to keep his costs down and guarantee the best growing conditions for his crop, he needs to access a short-term precipitation forecast.
Source:

10. Example from Aquila (cont.)
Solution
The Guaranteed Forecast product along with a partnership with agrochemical companies - allows him to schedule the pesticide application, and ensures that his crops will be protected against pests, even in rainy conditions.
Based on a 72-hour forecast, he can have the pesticides applied if the precipitation will be less than 5 mm.
If the forecast predicts 5 mm or more, he should wait for the next dry period.
If he chooses to apply based on the forecast the chemical company will treat the farmer's fields.
If the forecast was incorrect, and too much rain falls, the chemical company can reapply the farmer's field free of charge.
Source:

11. Ensemble Forecasting
Another approach to obtaining a measure of forecast uncertainty, 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.

12. Some Important Issues Quality of weather and climate data.
Changes in the characteristics of observation sites.
Security of data collection processes.
Privatisation of weather forecasting services.
Value of data.
Climate change.

13. Weather Derivative Applications
Several Case Studies in the Australia Market will be analysed including:
Soft Drink Sectors
Power
Air Conditioning
Theme Park
Clothing
Brewing
Mining
Ice Cream
Gas
Agricultural
Weather Derivatives

14. Applications: Agricultural (1)
From plantation to harvest, precipitation, temperature, sunshine hours and wind can affect the quality and quantity of a crop.
Source:EnronOnline

15. Applications: Agricultural (2)
Rising production costs and stricter rules regulating the use of agrochemicals mean farmers must be increasingly efficient in their management practices.
Although more intensive technology programs have been developed in recent years to integrate the use of high-yield seed varieties with planned applications of fertilizers, herbicides, and fungicides,weather remains a major risk.

16. Applications: Agricultural (3)
While there is a strong correlation between fluctuations in crop production volumes and the weather, risk management tools are now available which can minimize the financial impact of the weather on a grower's profitability.
For example, weather derivatives can be tailored to protect growers against losses to heat-loving crops, such as cotton, due to frosts or prolonged cloudiness in the early stages of development.

17. Applications: Agricultural (4)
Similarly, weather derivatives can be structured to provide financial compensation for the ill effects of excess precipitation. (Too much rainfall can cause flooding and ponding of the soil, which can restrict the amount of oxygen available to root systems. This, in turn, can reduce nutrient uptake, leading to nitrate leaching and an increase in the incidence of disease.)

18. Applications: Agricultural (5)
The diagram illustrates the payout structure of an option designed for a cotton grower in New South Wales that needs protection against excessive rainfall. This derivative will pay the farmer AU$70,000 per millimetre of rainfall in excess of 150mm between 1st March - 30th April, less the premium. A maximum payout of AU$10,000,000 is set.
Source:EnronOnline

19. Applications: Agricultural (6)
With weather exposure covered by a derivative, yield-related financial volatility can be reduced significantly. The earnings of the grower are thus stabilized, and minimum levels of financial income guaranteed, before the crop is sold, making profit forecasting more predictable and accurate.
The grower's strengthened risk management program, combined with more transparent accounts, may result in a lower cost of debt from financial institutions. In general, profit levels stabilize, and business management decisions can be made with greater confidence.

20. The increasing focus on weather risk
3,937 contracts transacted in last 12 months (up 43% compared to previous year).
Notional value of over $4.3 billion dollars (up 72%).
Market dominated by US (2,712 contracts), but growth in the past year is especially so in Europe and Asia.
Australian market accounts for 15 contracts worth over $25 million (6 contracts worth over $2 million, previously).
Source: Weather Risk Management Association Annual Survey (2002)

21. Survey Design and Implementation (1)
Presurvey (sent in February)
Sent to All WRMA members
Will you participate? 20 companies responded in 2002 (19 in 2001)
Survey (sent in April)
Establish size of market between April 2001 and March 2002 (Latest statistics)
5 Pages in total (2 pages returned to PwC)
General information about company
Information on Contracts
Responses confidential and destroyed once tabulated
Source: Weather Risk Management Association Annual Survey (2002)