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Weather Risk Management

Weather Risk Management. David Molyneux, FCAS. 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. Weather Derivative Basics.

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Weather Risk Management

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  1. Weather Risk Management David Molyneux, FCAS © Zurich Re

  2. 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 © Zurich Re

  3. 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 © Zurich Re

  4. Weather Derivative Customers • Utilities and energy companies • Agricultural companies • Municipalities • Seasonal Clothing Manufacturers • Ski/Beach Resort Operators • Golf Course Management Companies • Beverage Companies & Distributors © Zurich Re

  5. Weather Derivative Risks • Average Temperature - HDDs/CDDs • Abnormal Temperature - # of Days above 100F • Precipitation or snowfall • Humidity • Wind speed • Riverflow • Combinations of the above © Zurich Re

  6. Heatingand 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) © Zurich Re

  7. 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 © Zurich Re

  8. 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 © Zurich Re

  9. Option Payoffs © Zurich Re

  10. 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. © Zurich Re

  11. 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 © Zurich Re

  12. Snowfall Distribution © Zurich Re

  13. Removal Costs With & Without the Call © Zurich Re

  14. 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 © Zurich Re

  15. 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!!! © Zurich Re

  16. Data Adjustments • Station Changes • Instrumentation • Location • Trends • Global Climate Cycles • Urban Heat Island Effect • ENSO Cycles • Forecasting © Zurich Re

  17. Phoenix CDD Data © Zurich Re

  18. Phoenix CDD Data - Adjusted © Zurich Re

  19. Phoenix CDD Call Graph © Zurich Re

  20. 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 Phoenix CDD Call - Impact of Data Adjustments © Zurich Re

  21. 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 © Zurich Re

  22. Portfolio Management • Diversify Geographically & Directionally • Track Correlations Between Cities • Manage Transactional & Aggregate Limits • Hedging & Trading Strategies © Zurich Re

  23. 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 © Zurich Re

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