Weather data issues for the weather derivatives market Jeff Hamlin Risk Management Solutions October

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Weather data issues for the weather derivatives
marketJeff HamlinRisk Management
SolutionsOctober 5th, 2006jeffh_at_rms.com
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Weather Data Topics

• Historical data
• Raw
• Synop vs Climate
• Cleaned
• Enhanced
• Dealing with trends in temperature data

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RAW Historical Weather Data

• Two types of raw historical weather data for any
  country
• SYNOP
• data that are collected in real-time at various
  stations around the globe and provided through
  the Global Telecommunication System (GTS)
• Distributed freely around the world for use as
  inputs to global forecasting models
• Climate
• data that are quality controlled by the
  respective national meteorological services (NMS)
  where the data is collected. The 'climate data'
  are the 'official' station data of the country.
• WRMA has previously recommended that Climate data
  is the most appropriate data to be used in
  weather derivatives transactions

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SYNOP data details

• Benefits
• Available for a huge number of locations around
  the world (over 5,500 stations in 183 countries)
• Inexpensive and readily available
• Problems
• Data quality issues missing and erroneous
  values
• Some non-standard recording conventions (e.g. 12
  hour periods for measuring Tmax or Tmin)
• Short historical records relative to Climate data

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Climate data details

• Benefits
• Data is Quality Controlled and certified by
  personnel of the relevant National Meteorological
  Office
• Long historical records
• Consistent recording conventions
• Problems
• Must contract with relevant Met Office to obtain
  (or licensed distributor)
• Data can be very expensive
• Final Edited data can be released infrequently
  true-ups

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Cleaned Historical Weather Data

• Problems with raw historical weather data
• Missing values
• Erroneous values
• Missing and erroneous values generally not a
  significant problem going forward, but can be a
  problem historically
• Solutions exist for timely, quality controlled
  weather data (EarthSat CME settlement data)

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Enhanced Historical Weather Data

• Most weather stations have existed for 50 years
• Over time, station location, instrumentation, or
  environment may have changed
• Any change can lead to a discontinuity in
  temperature record for the station
• Discontinuities must be accounted for and can
  greatly affect valuation calculations

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Enhanced Weather Data Example

• Station X was moved from location A to location B
  on May 1, 2006.
• Location A is 3 meters from a taxiway and within
  15 meters of some airport buildings. Location B
  is 100 meters beyond the end of a runway in the
  middle of a grassy field and is located in a
  shallow depression.
• Weather stations were maintained at location A
  and location B for the past 5 months and studies
  show that Tavg as recorded at location B is
  consistently 0.8 degrees cooler than Tavg as
  recorded at station A.
• Why should we care?

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Enhanced Weather Data Example (cont.)

• Assume we are pricing a Nov-Mar HDD contract for
  a cold location.
• Nov-Mar risk period contains 151 days of risk
• 151 days x 0.8 HDDs/day 120.8 HDDs
• Calculation of mean and option values based on
  historical data will be erroneous, given current
  conditions
• Need to cool all historical temperature values by
  0.8 C to make historical temperatures relevant

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Trends in Weather Data

• Significant trends exist in the historical
  temperature data for many locations (global
  warming/urban heat island effect)
• Trends must be removed from historical data
  before using historical data as input to any
  model.
• Many different methodologies exist for removing
  trends from weather data

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Trend Example (Barcelona Nov-Mar HDDs)
What is the expected value (fair strike) for a
2006-07 swap?
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Trend Example (Barcelona Nov-Mar HDDs)
Historical average 1100 HDDs
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Trend Example (cont.)
Many different formulas that can be applied to
remove trends from data (loess linear)
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Trend Example (cont.)
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Trend Example (cont.)
Historical average 1100 HDDs Detrended average
955 HDDs
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Summary

• Climate data still the standard
• Recent advances may make SYNOP data viable for
  trading
• Data must be cleaned and Enhanced before being
  used in pricing
• For temperature data, trends must be addressed.
  May be less relevant for other weather variables