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.

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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

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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

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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)

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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.

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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

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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.

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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

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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.

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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

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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

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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.

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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

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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

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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

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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

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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.

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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.

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Table 5: Deviation in Kharif foodgrain production from the trend at all

India level

Source: NCAP, Ramesh Chand & S.S. Raju

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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.

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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

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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.

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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

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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.

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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

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(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

37

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.

44

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.

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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