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WEATHER DERIVATIVES
An Emerging Market in Indian Context
2012
SUBMITTED TO:
Dr. Lalita Gauri Kulkarni
Dr. Anurag Asawa
A dissertation presented in part consideration for the degree of MA Economics by
Neha Saraswat
1026
2
DECLARATION
I, hereby undersigned, affirm that this study has been done solely by me, as
Master‘s thesis course in partial fulfilment of the requirements for the degree of
Master‘s in Arts in Economics from Gokhale Institute of Politics and Economics,
Pune.
April 2012. Yours Faithfully
________________
(Neha Saraswat)
We, hereby undersigned, confirm that this study has been completed by the
above mentioned student independently under our guidance, as part of Master‘s
in Arts in Economics from Gokhale Institute of Politics and Economics, Pune.
__________________ ____________________
Dr. Anurag Asawa Dr. Lalita Gauri Kulkarni
GIPE GIPE
3
ABSTRACT
Weather influences human lives and impacts economic and business
activities significantly. It is very well stated that “weather is not just an
environmental issue; it is a major economic factor”. Wide spectrums of
businesses are affected by weather fluctuation. Then a new class of
financial derivatives- Weather Derivatives evolved to manage the economic
impact of weather events on the revenues of various business activities.
This paper studies the need for weather derivative contract in the context
of Indian market. The variability of monsoon and its impact on crop
production significantly affects farm revenues. Therefore the aim of this
paper is to create a rainfall contract suitable for the Indian market and
henceforth study the challenges in implementing a weather derivative
structure in India.
4
ACKNOWLEDGEMENT
I am extremely grateful to my guide Dr. Lalita Gauri Kulkarni for the
guidance and motivation throughout this period of six months that I have
done my analysis in. Her unmatched devotion and sincerity has been a
great inspiration for me. I would also like to thank my guide, Dr. Anurag
Asawa for the valuable support he has given me. His assurance at the time
of confusion and despair has given me motivation every time.
I am also very grateful to Prof. Rajas Parchure and Dr. Kiran Karande
for their support and suggestion which helped me shape my research.
I would take this opportunity to heartily thank my family and friends
whose support was imperative for this study to have happened.
Neha Saraswat
1026
M.A. Economics 2010-2012
Gokhale Institute of Politics and Economics
5
TABLE OF CONTENTS
Serial
No.
Topic Page No.
1. List of tables and graphs 6
2. List of abbreviations 7
3. Introduction 8
4. The Weather Derivative Market 11
5. An emerging market in Indian
context
21
6. Cross country comparison 32
7. Conclusion 42
8. Bibliography 44
6
List of Tables and Figures
Sectors /businesses affected by weather risk. (Table1-page 13)
Periodicity of occurrence in droughts in various parts of the
country. (Table 2-page 25)
Changes in value of crop output and livestock in drought years.
(Table 3-page 25)
Frequency distribution of years according to direction of deviation
in crop output from trend and deviation in rainfall from the
average 1967-68 to 2007-08. (Table 4- page 26)
Rainfall based contract for the Indian market (Table 5-page 40).
Temperature based contract for the Indian market (Table 6-page
41).
Figure1: Percent deviation in value of crop output from the trend
and in the south west monsoon from the long run average
expressed in log. (page 29)
Figure 2: Number of weather derivative contracts in North
America. (Page 32)
Figure 3: Number of weather derivative contracts in Europe. (page
34)
Figure 4: Number of weather derivative contract in Asia. (page 35)
Figure 5: Total share of each major player in the market. (page 36)
7
List of Abbreviations
CDD : Cooling Degree Day
CME : Chicago Mercantile Exchange
FCRA : Forward Contract (Regulation) Act
GoI : Government of India.
HDD : Heating Degree Day
ICE : Inter Continental Exchange
LIFFE : London International Financial Futures & Options
Exchange
MCX : Multi Commodity Exchange
OTC : Over the Counter
WRMA : Weather Risk Management Association
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1. INTRODUCTION
“Climate is what we expect, weather is what we get”. This quote by Mark
Twain very much pronounces the need for managing weather risks.
Adverse weather leads to financial and economic losses to those sectors
with natural exposure to weather. The primary sectors affected by weather
risks are agriculture, construction, retailing, transportation, offshore,
entertainment, energy, tourism.
The unpredictability of weather makes it difficult to determine weather
risk accurately. Therefore a new market called the weather derivative
market has been developed to effectively reduce the economic impact of
weather events. A weather contract is a contract whose cash flows depend
on the occurrence of some weather event which can be considered as non
catastrophic. The weather events are easily measurable and sufficiently
transparent to act as triggering underlying for a financial contract. The
five essentials of a weather contract as defined by Richard, Manfredo and
Sanders 2004 are:
I. The underlying weather index should be relevant.
II. The index should accumulate over a well defined period such as
particular season or month.
III. Daily weather reports of maximum and minimum temperatures
should be available from reliable weather station.
IV. Each move in the index should be attached to rupee value.
9
V. A reference value or strike value of the underlying index should be
defined.
The first transaction in weather derivative market took place in the United
States in 1997. Since then the market has seen tremendous growth and
development. The key factors driving the growth of the market have been
deregulation of the energy market, convergence of the capital market with
the insurance market, increased use of derivative to hedge funds, increased
availability of standardized derivative contracts through Chicago
Mercantile Exchange.
The survey conducted by Price Waterhouse Cooper in association with
Weather Risk Management Association shows that the weather derivative
market grew by 20% in 2010-20011. The American market has the largest
share in the industry with European and Asian market quickly catching
up. Amongst the weather contracts the most prevalent ones are those
based on temperature with the underlying asset being Heating Degree
Days and Cooling Degree Days. Various other contracts based on rain,
snowfall, precipitation and frost are growing with time.
Since agriculture is the sector which is directly influenced by weather
fluctuations therefore my research focuses on introducing weather
derivatives in this particular sector. The heavy dependence on erratic
summer monsoon and inadequate spread of irrigation in the Indian sub
continent has made crop production vulnerable to fluctuations in rainfall.
Also the weather risk management tools like insurance schemes have
10
failed in India. So a niche market for such a product can be developed to
better the farm production and stabilize farm income.
In Chapter 2 the weather derivative market structure and the elements of
a weather contract have been discussed. Chapter 3 focuses on the need for
such a product in India and why agriculture. In Chapter 4 a cross country
comparison has been made to learn from the countries where weather
derivatives have been introduced and to study the challenges and prospects
of such a market structure in India.
11
2. The Weather Derivative Market
2.1 Birth and evolution of the market
The first transaction in weather derivative market can be traced back in
1997 between Koch Industries and Enron. Their work mostly focused on
the use of weather data on rainfall, temperature, precipitation, snowfall in
terms of which the risk was expressed and transferred.
The history of the weather derivative dates back to 1996, when electricity
deregulation in the United States caused the power market to begin
changing from series of local monopolies to competitive regional wholesale
markets (Cao & Wei 2004). In the deregulated environment with growing
competition and uncertainty in demand, the energy merchants had to deal
with the volumetric risk to stabilize their incomes. In a deregulated
environment the energy merchants soon realized that uncertain weather
conditions became a main source of their revenue fluctuations. Hence the
first weather deal between Koch and Enron took place wherein a HDD
collar was exchanged. Since then the US weather market has grown in size
and continues to be dominated by the energy industries. The first
European deal was structured in 1998 whereas in Asia the first transaction
in the weather derivative market took place in 1999.
Since then the market has mushroomed and diversified tremendously. The
key factor behind the growth of the market has been the convergence of
capital market with the insurance market. Other key factors are the
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deregulation of the energy market, increased use of derivatives to hedge
funds and availability of standardized derivative contracts through CME.
‘Uncertainty of events’ being a common factor between the weather market
and insurance market became an attraction for the insurance industry to
participate in the weather market. Also the insurance industry players
interrelated skills and experience required to participate in the weather
market. These two reasons gave sufficient incentive to the insurance and
re-insurance companies to enter this segment.
Most of the weather trading is over the counter usually through call/put
options and swap structures. The weather trading has also been facilitated
through electronic exchange. The standardized weather contracts are now
listed on CME, ICE and LIFFE. The CME Globex platform was the first
exchange where a standardized weather derivative could be traded.
The increasing trade volumes in these contracts are having positive
impacts on market liquidity and price discovery. The weather derivative
market is blooming in size and diversity. The annual WRMA survey results
show that the market for weather derivative grew nearly by 20% in 2010-
11. The total notional value for OTC traded weather risk contracts rose to
$2.4 billion while the overall market grew to $11.8 billion (WRMA).
2.2 Market Participants
Weather derivative help companies to hedge the risk arising from weather
fluctuations by buying the weather derivative from a group of speculators.
The speculators are usually banks, insurance companies, energy
13
companies, reinsurance companies and hedge funds. The speculators are
involved in trading because their aim is to make profit rather than to
hedge risk unlike the hedgers. Therefore we have a significant overlap
between hedgers and speculators who wish to make money through both
the ways that is by hedging their risk and by speculating.
Since its inception apart from the energy industry the weather derivative
market has attracted traders from diversified segments like insurers,
reinsurers, investment banks and hedge funds. A list of various sectors and
end users affected by weather risk is given below.
Table 1: Sectors/Businesses affected by Weather Risk
Risk Holder Weather Type Risk
Agriculture Rainfall, Temperature Crop yield, Storage, Pest
Construction Snowfall, Rain Delay on meeting the
deadline of the projects
Beverage companies Temperature Lower sales during cool
summers
Hydroelectric power
plants
Rainfall Low revenue during
droughts
Ski-resorts Snowfall Lower revenues during low
snowfall
Retailing Temperature Lower demand of products
which are weather sensitive
like low sales of winter
clothes during warm winters
Energy Temperature Lower revenues during cool
summers/hot winters.
Offshore Storm Low revenue during severe
storms
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2.3 Weather Derivatives Instruments & Structures
The list of actual contracts is extensive and constantly evolving but most
of the weather derivatives traded have been either swaps or call and put
options or a combination of these. The recently developed structures
include binary/options.
Payoff on a weather derivative contract is usually a specified dollar
amount multiplied by the difference between the actual cumulative levels
which occurred during the contract period. To limit the maximum pay out
by the counter parties the contracts are usually capped which implies that
only a certain maximum amount of payout can change hands.
Call/Put Options
Weather options can either be a call or a put option or a combination of
these like collars, straddles and strangles.
A call option gives the holder the right to buy (and not an obligation) an
asset by a certain date for a predefined price. Mostly the underlying asset
in most of the contracts is HDD/CDD. While calculating the payoff, a
dollar amount is associated with each degree day index. Consider a CDD
call option with a strike of 2000 CDD’s paying $100 per degree day index.
15
Payoff on call = $100 * max [0, CDD-1000]
where CDD is the cumulative CDD over the life of the contract.
Payoff for a call and put option can thus be expressed as:
Payoff on Put option: $ per degree day index * max o, (K – X t)
Payoff on Call option: $ per degree day index * max 0, (X t – K)
Where X t – Strike price
$ Per degree day index – per degree day payoff
K – Strike
The buyer of the call option will receive the payoff if the cumulative
HDD/CDD for the season is greater than the strike K. Whereas the buyer
of the put option receives the payoff if the cumulative HDD/CDD is lower
than the strike.
Weather Swaps
Swaps are agreements between two parties to exchange cash flows in the
future wherein one party pays a fixed price and the other pays a variable
price after a specified period of time.
Swap contracts are usually tailor made to meet specific needs of the
investors swaps are thus non-standardised contracts wherein the investors
16
can privately negotiate the terms over the counter. It is usually
customised as to timing, seasonality, volume, swing and location.
The buyer of the swap contract makes payments to the seller when
cumulative CDD/HDD index rises above the strike price. The buyer
receives payments when cumulative CDD/HDD index lies below the strike
price.
Example: let the tick size = $ 1000 per HDD. MNO Ltd. agrees to pay ABC
Ltd. a fixed rate of 1500 HDD in return for a floating rate which is the
actual number of accumulated HDD during a contract month. The
cumulative HDD is say $900 for the contract month. The realized payoff
for MNO ltd. at maturity is $1000 * (900 – 1500) = - 600000.
The buyer of the swap receives the payments if recorded HDD/CDD is
greater than the strike and will make payments if the recorded HDD/CDD
is lower than the strike.
Weather Futures Contract
Weather futures contracts entails the holder the right but not an
obligation to buy/sell the relevant contract at a specified strike price on a
specified future date. The CME provides a standardised platform for
trading in weather futures which is based on the CME degree day index.
This degree day index is a cumulative sum of HDD and CDD during a
17
single calendar month. Weather futures are though not as frequently
traded as other derivative structures. The daily marking to market makes
these contracts complex especially if the underlying asset is weather.
2.4 Elements of a Weather Derivative
The anatomy of a weather derivative can be defined by several elements
explained below:
Reference weather Station- there should be one or more specific
weather stations which provide reliable records of weather data. Most of
the weather contracts are based on a single station while some are based
on a weighted combination of readings from multiple stations.
Index- the underlying index of a weather derivative defines the measure of
weather like rainfall, snowfall, temperature which governs the pay outs on
the contract. The most common indexes are HDD and CDD. They are the
cumulative variation of average daily temperature from 650F or 180C over
a season. Average temperature is another common index for non-energy
applications.
Term- all contracts have predefined period over which the underlying
index is calculated.
18
Structure- weather derivative are based on standard derivative structures
like put, call, swap, collar, straddle and strangle. Key elements of these
structures are the strike that is the value of the underlying index at which
the contract starts to pay out. The tick size is the pay out amount per unit
increment in the index beyond the strike and the limit which is the
maximum financial pay out of the contract.
2.4 Pricing Problems in a Weather Derivative Market
The weather derivative market is a classic example of an incomplete
market. In case of weather derivative the underlying asset is not a traded
asset rather it is an intangible asset. Pricing of this derivative thus
requires high quality and reliable data. The number of weather elements
like snowfall, rain, temperature that will be experienced at a given
location for a given time period can be modelled statistically in terms of
probability distribution, mean, standard deviation and other parameters
(Dunis & Karalis 20003). These other parameters are derived from
historical weather data and not from market information. Thus high
quality weather data is a pre requisite without it pricing is not feasible.
Most commonly observed errors and problems in weather data is of
missing values, unreasonable readings and spurious zeroes. A common
problem amongst climate data sets is that most of them contain
discontinuities introduced by non-climatic factors such as instrumentation
that is malfunction of instruments or out of calibration example-
dirt/grime can cause a slow warming/cooling trend of the instrument.
Other reasons of discontinuity in weather data are changes of station’s
19
physical location, human errors, changes of operator and changes in
operation procedure. These malfunctions create additional ‘noises’ in the
detection of discontinuities. To overcome the problem of instrumentation
‘Enhanced data’ can be used. Enhanced data is a version of daily historical
values that has been adjusted to be consistent with differences in
operational procedure used to record temperature by the instrumentation
at each individual weather station.
To deal with the problem of missing values in weather data, the weather
risk professionals came up with the versions of cleaned data. Cleaned data
is a version of historical data which has been corrected for missing or
erroneous values in the historical record. Erroneous or missing data is
replaced with estimated values derived from comparisons with
neighbouring station recordings and analyses of local micro-climate biases
(www.climetrix.com). However this process requires a continuous and
complete historical time series of daily values. Replacing a missing value
is fairly easy but if the data sets have blocks of missing values then it may
create a problem. The missing values in such a case can be replaced
through interpolation observed across several stations that is spatial
interpolation and interpolations observed over time that is temporal
interpolation. The differences in daily time conventions and different
reporting times for different parameters would require specific data
cleaning techniques to be developed for each weather variable and each
country (Boissonnade & David). Also it would be unwise to assume that
20
the closest points correlate higher than ones farther away because each
variable has its own unique spatial correlation characteristics.
Thus a reliable, standardized and inexpensive weather data is a pre
requisite for the growth of the market.
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3. An Emerging Market for India
3.1 Why India?
“India is an agrarian economy” is a famously known fact about India.
Though this is not true anymore, but what cannot be ignored is that
agriculture is the pulse of any developing economy.
Agriculture has always been a major contributor to Indian GDP. Till date it
contributes around 19% to the GDP. Of the world’s 16% population living
in India, agriculture is a source of livelihood to the two third of the
population. Apart from providing employment to 57% of the workforce it is
the single largest private sector occupation. Agriculture is also a source of
raw material to large number of industries like textile, silk, sugar, rice,
flour, milk and milk products.
This chapter explains that monsoon in India is uncertain and this
variability in monsoon affects agricultural production profoundly. Hence to
stabilize farm income which in turn will augment farm production, it is
22
necessary to provide a derivative framework to make good the loss in farm
revenue.
3.2 Variability in Indian Monsoon
“Delay in monsoon may spell doom for farmers” – The Economic Times 2011
“Monsoon delay halves kharif sowing in Gujarat” – DNA 2011
“Monsoon delay deepens power crisis” – The Times of India 2010
“Monsoon ends, one third of the country rain deficient” – NDTV 2010
“Monsoon delay to impact growth significantly” – Moody’s 2009
“Monsoon delay may stall economic recovery” – The Economic Times 2002
“Drought situation is serious says centre” – The Times of India 2002
Erratic monsoon is hardly surprising in India. In four out of ten years India
has irregular rainfall. There have been 23 major drought years since 1871
till 2008. According to the official sources the problem of monsoon rains
being erratic in India is as high as 40%, which means that 40% of the time
the behaviour of the monsoon deviates from its long term average.
According to the agriculture ministry 68% of India’s sown area is
vulnerable to drought in varying degrees. Around 85%of the rainfall is
agglomerated in 100-120 days of the monsoon and the remaining one third
of the area receives less than 750 mm rainfall becoming a severely drought
prone area.
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It has been shown that the frequency and intensity of extreme rain events
are increasing over central Indian monsoon trough region (IITM, B.N.
Goswami). The role of Indian Ocean and South China Sea are critical
factors affecting intraseasonal variability of Indian Summer Monsoon.
Ramesh Chand states in his paper that impact of monsoon is now being felt
more severely than before because of several reasons. One, in the world of
information, communication, technology and infrastructure the public is off
the expectation that in the 21st century a country should be well equipped
and prepared to deal with the adverse effects of monsoon failure. Two,
during a monsoon failure the same amount of water shortage is felt
strongly in present era than before due to tremendous increase in demand
for water. Third, increasing water intensive cultivation and the rapid
commercialisation of agriculture has driven the farmers to face higher risk
in income due to weather shocks.
The International Conference on Challenges and Opportunities in Agro
meteorology - Intromet 2009 by IMS draws our attention to the fact that
climate change (that is variation in rainfall, increase in temperature,
variation in precipitation and extreme weather events) has adverse impact
on agricultural productivity and yield and that the impact will turn more
dramatic in future.
3.3 Monsoon Variability and Subsequent Production
Summer monsoon continues to dictate the economy of India. A good
monsoon year results in an increased agriculture production and a bad
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monsoon year results in a decreased agriculture production. Though the
commercialisation of agriculture has helped in augmenting the agriculture
production to meet the needs of growing population but variability in the
monsoon continues to affect the productivity of agriculture. However El
Nino periods (that is ocean currents which affect monsoon) have resulted in
below normal rainfall which in turn has decreased production. From the
sequential march of grain production it is seen that the El Nino years
resulted in deficit production (Murthy, Satyanarayan & Subrahmanya,
Intromet).
Long term trends have shown that drought is experienced at least once in
three years in states like Rajasthan, Andhra Pradesh, Haryana, Tamil
Nadu, Jammu & Kashmir, Gujarat & West Uttar Pradesh (Ramesh
Chand). States of West Rajasthan, Haryana and Telangana are the worst
affected areas by droughts.
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Table 2: Periodicity of occurrence of droughts in various parts of the
country
Frequency of deficient
rainfall
Meteorological Sub-Division
Once in 2.5 years
West Rajasthan; Rayalaseema;
Telangana; Haryana;
Once in 3 years
East Rajasthan; Gujarat Region;
Jammu and Kashmir; Tamil
Nadu and Pondicherry; West Uttar
Pradesh.
Once in 4 years
North Interior Karnataka;
Uttarakhand; Vidarbha
Once in 5 years
Bihar; Coastal Andhra Pradesh; East
Uttar Pradesh; Gangetic
West Bengal; Jharkhand; Kerala;
Orissa; South Interior
Karnataka; Madhya Maharashtra;
West Madhya Pradesh.
Once in 15 years
Arunachal Pradesh; Assam and
Meghalaya; Nagaland;
Manipur; Mizoram and Tripura.
Source: NCAP, Ramesh Chand, S.S. Raju.
Table 3: Changes in value of crop output and livestock in drought
years
Drought Year Change in Crop
Output
Change in Livestock
Output
1972-73 -6.25 3.66
1979-80 -12.80 4.30
1987-88 -3.12 2.27
2002-03 -10.50 2.74 Source : NCAP, Ramesh Chand, S.S. Raju
26
The paper by Ramesh Chand studies the change in the value of crop output
during four major drought years 1972-73, 1979-80, 1987-88 and 2002-03.
The value of crop output fell in drought years whereas the livestock output
increased. The adverse impact of drought is thus majorly seen on crop
output.
The change in output due to monsoon failure is seen by comparing output
between the years of monsoon failure and the previous years. Accordingly
the paper studies the effect of deficient rainfall on crop output by
examining and comparing direction of deviations in value of crop output
measured in constant prices (1999-2000) from the semi log trend.
Table 4: Frequency distribution of years according to direction of
deviation in crop output from trend and deviation in rainfall from the
average, 1967-68 to 2007-08.
Deviations Number of years Frequency %
Deviations in output
and rainfall in same
direction
31 75.6
Deviations in output
and rainfall in
opposite direction
10 24.4
Output deviation
positive and rainfall
deviation negative
4 9.8
Output deviation
negative and rainfall
deviation positive
6 14.6
Total 41 100 Source: NCAP, Ramesh Chand, S.S. Raju.
27
Study over a period of 41 years shows that in most of the years the
deviation in output and rainfall is in the same direction. This means that if
rainfall in a particular year is deficient then the crop output is also
deficient. It is only in 10 out of 41 years that deviation in output and
rainfall was in opposite direction. This implies that higher the rainfall in a
given year higher will be the crop output.
Studies have shown that the impact of drought on Indian agriculture is
more than the impact of flood. It is mostly the kharif food grains which are
affected by droughts. On the other hand the rabi food grains depict a better
adaptability to deficient rains. Among the major crops analysed rice shows
more sensitivity to extreme climate events than wheat and jowar which can
efficiently face flood.
28
Table 5: Deviation in Kharif foodgrain production from the trend at all
India level
Source: NCAP, Ramesh Chand & S.S. Raju
29
Figure1: Percent deviation in value of crop output from the trend and in the
south west monsoon from the long run average expressed in log.
Source: NACP, Ramesh Chand, S.S. Raju
3.4 Insurance vs. Derivative
Insurance is a tool designed to protect the participants against small
probability events associated with which are large unexpected losses.
However where crop insurance is concerned the presence of a systematic
risk component in agricultural risk makes it difficult to diversify the risk
by pooling. In case of an insurance one condition that must be satisfied is
that the insured must have an interest in the subject of the contract of
insurance and he must suffer a loss in relation to his insurable interest.
30
On the other hand a derivative contract is a type of agreement enforceable
by law and whose value is derived from an underlying asset which can be
temperature, rainfall, wind, snowfall, precipitation etc.
Hedging a risk using a derivative contract or taking an insurance is almost
the same in commercial terms because they both cover against a financial
loss. The major difference between the two is that to claim insurance the
insurer must prove that a loss has occurred due to changes in weather
condition. Unlike an insurance contract the buyer of a derivative need not
have an insurable interest or any weather sensitive production, the
contract can be purchased simply for the purpose of speculation.
Also an insurance contract is illiquid that is it should effectively be a buy
and hold instrument which implies that the coverage is non-cancelable.
Whereas a derivative contract has greater liquidity as it is traded on
exchange and is not necessarily a buy and hold instrument. Another
advantage of holding a weather derivative over weather insurance is that a
derivative can be bought or sold and indexed on a virtually unlimited array
of weather variables whereas insurance offers limited flexibility in this
context. Insurance is also limited to the purchase of insurance covering
measured weather element/combination of elements. Weather derivative
has an edge over the insurance contract because the derivative instrument
usually covers high probability but limited loss events whereas insurance
covers low probability but higher loss events.
Though the design and implementation of contingent contracts became an
integral part of the development process in Indian agriculture sector but
31
the present agricultural insurance schemes have done little to reduce the
risk exposure of the farmers to the uncertain weather.
There are certain inherent difficulties of moral hazard and adverse
selection in the insurance sector. Due to the moral hazard problem farmers
with higher expected yield opted out whereas those with lower expected
yield purchased crop insurance thereby increasing the indemnity payments
relative to the premiums paid. If the insurance schemes are to be made
financially viable then the premiums paid must rise continuously.
To conclude we can say that since crop production is highly sensitive to
variability in rainfall a weather derivative based on a rainfall index can be
a big hit in protecting Indian farmers from varying revenues due to
weather fluctuations. Also weather derivative market enjoys certain
advantages over the weather insurance market plus the inherent problems
in insurance market pronounces the need to develop a weather derivative
market to facilitate development of the agricultural sector.
32
4. Cross Country Comparison
4.1 The US Market
The first transaction of weather derivative in the US market took place in
1996. The majority of contracts in US are for the winter months. Hence
heating degree days make about 60% of the deals whereas cooling degree
days make about 30% till date the US market is dominated by the big
energy companies who hedge their risk exposure to mild winters.
The free dissemination of information and easy availability of high quality
data has enabled a wider spread of the weather market in US. With the
increased transparency and liquidity more speculative players came into
the market.
Figure 2: Weather derivative contracts in North America
Source: www.dbresearch.com
33
4.2 The European Market
The first European transaction was a swap in 1998 between Enron and
Scottish Hydro Electric. The growth of the weather derivative market
within Europe is mostly restricted to France and UK with Scandinavian
countries and Germany closely behind. Most of the European deals are
OTC. According to WRMA survey 2001 the total European market deals
are around 765 contracts that is an increase of over 345% in terms of
number of contracts. Just like the US market most of the contracts in
Europe continue to be temperature based. Amongst the temperature based
contracts the proportion of rain, snow and wind contracts have increased.
However the take-off speed is slow in Europe as compared to US market.
The most important reason being lack of reliable, standardised and
inexpensive weather data. The data issued by the Met Offices is not
standardised and it can only be obtained by going to a particular office.
Also there is a difference in the recording times of max/min temperatures
for each country. Apart from this, a country can shut down or change the
location of its weather station without any prior warning. The definition of
daily average temperatures differ from country to country which is again a
hindrance to the growth of the market. Differences in data cleaning
practices, different formats of data, long delivery time to obtain data and
lack of good quality historical records are other serious problems.
34
To overcome these issues ECOMET- an economic weather group
comprising of 20 members countries was established in 1995 to ensure free,
unrestricted exchange and widest availability of meteorological information
between the national meteorological stations for commercial applications.
Furthermore to make the existence of standardised contract more
convenient LIFFE has developed pan-European weather futures which
would also lead to an increase in size of the overall weather derivative
market.
Figure 3:Number of weather derivatives contracts in Europe
Source: www.dbresearch.com
4.3 The Asian Market
The first Asian transaction took place outside the energy market. The
transaction was executed between a Japanese ski resort and a Societe
Generale in Nagano for protection against low snowfall in December 1999.
The trade in Japanese weather derivative market reached a total of 2100
contracts in 2003 that is approximately 150% of the previous year
35
(WRMA). Japan being a pioneer in the Asia Pacific weather derivative
market has a total notional value of weather contracts to a tune of $420
million in 2003.
Figure 4: Weather derivative contracts in Asia
Source: www.dbresearch.com
According to the Asia Pacific Committee review the Japan market has few
unique characteristics. Firstly, the weather derivative product has a wider
reach in the market because it reaches the end users as a risk management
tool through the network of major commercial banks and non-life insurance
companies which usually have a tie up with regional banks. Secondly,
unlike the US market which is mostly dominated by giant energy
companies the Japanese market is primarily dominated by small and
medium sized companies with small pay outs and premiums across a wide
range of industries. Thirdly, Japan has also developed a new legislative
framework for investor protection wherein the weather derivative are
subject to the exchange law (passed in Diet) and investors are classified
36
into professional and general with stricter obligations to be imposed on
general investors.
The only problem to be dealt in future is of limited market liquidity which
is mostly because of limited development of a secondary market
Figure 5: Total share of each major player in the market
Source: www.dbresearch.com
The market situation outside Japan also seems to be blooming. In Taiwan
the weather derivative products are approved by a competent authority
and a type of weather index insurance has already been launched. Whereas
in Korea weather derivative product have not been approved officially. The
Korean insurance companies are however allowed to sell index based
weather insurance.
Weather Derivatives
Europe
Asia
North America
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4.4 Prospects and Challenges for the Indian Market
“Indian weather market could see dramatic growth” - WRMA
The future of the Indian weather market is blooming. A survey by WRMA
finds that the Indian weather risk management market could see major
growth in several sectors with a potential notional value of $2.35 billion
over the next two years. WRMA’s Indian market survey shows how
different risk mitigation tools could be used to benefit several important
sectors of the economy specially agriculture.
The successful implementation of weather derivatives depends on the
efficiency of the institutional infrastructure and regulatory mechanism.
Data deficiency is a major challenge that stands in the way of developing a
weather derivative market for the Indian economy. As discussed in the
previous chapters, lack of reliable and quality data leads to pricing
problems in the derivative market. To address this issue the government
must set up weather stations to penetrate every part of the country.
Lack of product knowledge is another major hurdle. The GoI must take the
initiative to educate the farmers with the pros and cons of the market
through government programmes. If this is not done efficiently then it
could be a major deterrent for the growth of the weather market in India.
In order to address this issue mock trading platform will be launched to
educate people about the benefits of the product by MCX and Weather Risk
38
Management Services Pvt Ltd. This initiative might help in increasing
product knowledge and liquidity in the market. Most of the Indian farmers
are marginal farmers with small land holdings. In such a case designing a
product for such farmers is difficult.
Another essential pre requisite for developing this market is creating an
institutional set up which comprises of derivative exchange, brokers and
weather observatories. The Forward Exchange Act at present covers
forward trading in goods only. The push for weather derivatives continues
in India. Necessary amendments in FCRA have been made which will
enable the market to introduce new and innovative hedging products like
weather derivatives. Stringent regulatory mechanism will improve price
discovery and price dissemination which will in turn stabilize the market
forces and allow effective risk management.
4.5 Lessons Learned from Other Countries.
Incomplete and riskiness are the two inherited attributes of the weather
derivative market. For a successful implementation of such a market
structure India can learn from the mistakes and achievements of the
countries where the weather derivative market is in full swing. The basic
requirement of the market is easy and free availability of high quality
reliable data.
As seen in the previous section, a major deterrent in the development of
the weather market in U.S. is the lack of reliable, standardised and
39
inexpensive data. Given the incomplete nature of the weather market,
availability of high quality, standardised data through a wide spread
network of Met Offices becomes essential. Just like Europe, an economic
weather group can established in India to ensure free, unrestricted
exchange and widest availability of meteorological information.
Before developing the weather derivative market in India the unique
characteristics of the Japanese market can also be absorbed. Just like
Japan a network of commercial banks, non-life insurance companies and
regional banks can be used to reach a wide spectrum of users.
To overcome the riskiness in the market, a legislative framework like that
of Japan which ensures investor protection by dividing investors into
groups and imposing stricter obligations on non-professional investors, can
be implemented in India. Regularisation and transparency in the working
is a must for development of the market. Developing a secondary market
can help to deal with the problem of market liquidity.
4.4 Creating a Contract for the Indian Market
In my modest attempt to create a contract which is suitable for Indian
agriculture, I consider the case of rice production first. Since rice is a crop
which is heavily dependent on water, a rainfall contract to suit the Indian
scenario is justified. If the average requirement of rainfall is 200 - 250 mm
during the main field preparation of the crop then a strike rate of say 200
40
mm is appropriate. The pricing unit would be in rupee terms with the tick
size equal to 5 paisa (going by the Indian standards).
Table 5: Rainfall Contract
Product Description Rainfall Index Option
Pricing Unit Rupees per index point
Strike Level 200 mm units
Tick Size Rupees .05 per index point
Trading Hours 9:55 a.m. till 3:30 p.m.
Contract Months Monsoon Months i.e. June-September
Settlement Procedure Cash settlement
Similarly an effort can be made to develop a temperature based contract for
any crop whose production is sensitive to temperature. Since it is mostly
the horticulture crops, so consider the case of apples. Apples are mostly
harvested from September to January. They are grown on the shadow side
of the hill because early morning light is harmful for production. The
average temperature required for its production is 160C to 240C and any
increase in temperature beyond that harms the production.
41
Table 6: Temperature based Contract
Product Description CDD Option
Pricing Unit Rupees per index point
Strike Level 240C
Tick Size 1 index point = rupees .05
Trading Hours 9:55 a.m. till 3:30 p.m.
Exercise Procedure European style
Contract Months September to January
42
5. Conclusion
In today’s dynamic world, weather challenges a wide spectrum of
businesses like utilities, construction, agriculture, energy, retailing etc.
Changes in weather have adverse financial impact especially on the
developing economies like India.
“Climate and weather are significant factors affecting agriculture
production in India. Both seasonal and regional variability in weather
directly influences crop yield potential.”
- WRMA
Though climate risk affects different sectors of the economy but in India
weather risks has a major impact on agriculture. Indian farmers are
grappling with rising costs of production and fluctuating weather patterns.
Due to insignificant spread of irrigation a large part of Indian agriculture
still depends on the erratic monsoon. Studies have shown that correlation
between crop volumes and weather can result in successful yield or a
financial disaster. From plantation to harvest precipitation, temperature,
sunshine hours and wind affect crop output. The advent of technology has
done enough to help with improving the quality and quantity of crop
production. But insufficient spread of irrigation and technology and the
adverse affects of global warming leave crop production at the mercy of
weather God.
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Though weather risk management tools like insurance contracts have been
used to minimise the financial impact of fluctuations yet a lot can be done
with the help of weather derivatives. Besides the advantages that a
derivative enjoys over an insurance contract, the failure of insurance
schemes in India necessitates the need for a weather derivative market.
Before such a market structure can be introduced in the Indian market
reliable and high quality weather data should be made widely available.
Spreading product knowledge and stringent regulatory mechanism are
other basic requirements for a successful implementation of such a
structure.
The future of weather derivative market in India seems to be exciting at
the moment but additional research is needed on pricing approaches and
the illiquidity of the market.
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BIBLIOGRAPHY
A primer on weather derivative, Pauline Barrieu & Olivier Schillet, LSE.
Dealing with effects of monsoon failure in India, Ramesh Chand & S.S.
Raju, National Centre for Agricultural Economic & Policy Research.
European weather derivatives, working paper, Nick Buckley & Alex
Hamilton.
Government vs. weather- the true story of crop insurance in India,
Jennifer Ifft, CCS.
Introduction to Weather derivative, Geoffrey Conidine.
INTROMET- International Conference on challenges and opportunities in
agrometerology- Indian Meterological Society- Research papers.
Price Waterhouse Coppers and WRMA survey reports.
Weather data: Cleaning & enhancement, A.C. Boissonade, L.J.
Heitkemper & David Whitehead, Risk Management Solutions Earth
Satellite Corp.
45
Weather derivative pricing & filling analysis for missing temperature
data, Christian L. Dunnis & V.Karalis, 2003.
Weather derivative: a new class of financial instruments, Melanie Cao,
Jason Wei & angling Li, 2004.
Weather derivative: instruments and pricing issues, Mark Garman, Carlos
Blanco & Robert Erickson.
Weather derivatives heading for sunny times, www.dbresearch.com.
www.artemis.bm
www.climetrix.com
www.cmegroup.com
www.ftkmc.com
www.futuresandoptions.gr
www.speedwellweather.com
www.vortexinsuranceagency.com
www.wrma.org