Message-ID: <15393371.1075856365684.JavaMail.evans@thyme>
Date: Thu, 2 Nov 2000 07:13:00 -0800 (PST)
From: v.weldon@enron.com
To: mike.roberts@enron.com, mark.tawney@enron.com, claudio.ribeiro@enron.com, 
	gary.taylor@enron.com, todd.kimberlain@enron.com, 
	joseph.hrgovcic@enron.com, jose.marquez@enron.com, 
	vince.kaminski@enron.com, milind.pasad@enron.com
Subject: Hurricane Warning Derivatives
Cc: william.smith@enron.com, stephen.bennett@enron.com
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Folks,

This note is intended to update all who may be concerned on our progress 
toward developing a commercial hurricane warning derivative product or line 
of products.  

It is clear that numerous entities have underlying exposures to hurricane 
warning frequency and/or duration.  It is our objective to develop derivative 
products that will enable these entities to effectively hedge this 
exposure.   We have generated a partial brainstorm-style list of whom natural 
counterparties might be according to their underlying exposure:

Pro-Hurricane     Anti-Hurricane
The Weather Channel    Resorts
Home Depot     Cruise Ships    
Lowes      Riverboat Casinos
CNN      Chemical Plants and Refineries
Local TV Stations    U.S Armed Forces
Dry Ice Manufacturers    Athletic Teams
Chainsaw Manufacturers   City Governments
Insect Repellant Manufacturers   State Governments


It is obvious that there are numerous naturally offsetting parties but it is 
important to note that the pro-hurricane entities are more macro in nature 
while the anti-hurricane entities are typically more regional.  Thus, we have 
documented the frequency and duration data by regional location with the 
thought that the anti-hurricane entities would be interested in regional 
products and the pro-hurricane entities would likely be more interested in 
bundled regional products depending on their exposure.

Thus far, we have collected and documented all U.S hurricane warning data 
from 1980-2000 in the form of an Excel database.  The data can be sorted by 
year, storm, or location on the U.S coastline.  Total hurricane warning 
duration as well as number of discrete hurricane warnings are the primary 
data sets of interest for any given location (or year or storm).  The U.S 
coast has been divided into 11 different geographic regions of roughly 
similar size.  These regions are: New England, Mid-Atlantic, Virginia, North 
Carolina, Georgia/South Carolina, East Florida, West Florida, Florida 
Panhandle, Orleans/Miss/Bama, Lousiana, and Texas.

While this data set may not yet be sufficient for price modeling purposes, it 
has confirmed our expectation that hurricane warning frequency and duration 
is quite volatile and unpredictable.   It is believed that this volaility, 
when graphically depicted and mathematically represented, could be used to 
effectively demonstrate to would-be customers the impact of hurricane warning 
frequency on their business financials.  In many cases, businesses may be 
well aware of their exposure but may not have quantified it and certainly 
probably felt as if this was a risk they would have to wear themselves.

As we move forward on the modeling front, the data will certainly need to be 
scrutinized to correct for any skewing factors such as political trends, 
satellite availability, population trends, etc.   Additionally, we need to go 
further back in time so long as the accuracy doesn't decline.

On the marketing front, I am certainly open to ideas.  It is believed the 
Weather Channel would be the most natural party for such a product.  Given 
our positive relationship that we currently have with them, they might be the 
easiest sell.     Any and all ideas are welcome with regard to how and when 
we should approach customers.

Please respond with any questions, comments or concerns on this project.


Thanks,

Charlie
















