hurricane warning derivatives 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
hurricane warning derivatives
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