This document discusses weather risk management in India and the potential role of weather derivatives. It notes that over 70% of Indian agriculture is dependent on monsoons, making the sector highly vulnerable to weather fluctuations. Other industries like energy and manufacturing also face revenue losses due to weather. The document examines how weather derivatives could help mitigate these risks by allowing entities to hedge their weather exposures. It provides context on India's weather insurance market and outlines some challenges to further development, such as limited weather data infrastructure and high premium rates. Overall, the document analyzes the rationale for a weather derivatives market in India to strengthen the country's management of weather risk.

1. Weather Risk Management -
A Guide for Corporations,
Hedge Funds and Investors
Publisher:
Oxbridge Climate Capital, UK

3. 4
Weather Derivatives in India
Janani Akhilandeswari, Alok Shukla
Centre for Insurance and Risk Management
With over 70% of Indian agricultural production correlated with the
monsoon, weather has historically been a predominant factor in agriculture
planning for the country. In addition to agriculture, many Indian industries,
particularly in the energy sector (hydro electric, wind energy, etc), manu-
facturing and airlines suffer huge revenue losses on account of vagaries in
the weather. This means that the insurance industry is constantly on the look
out for a macro hedge to reinsure its weather exposures.
This chapter therefore analyses the role of weather derivatives in miti-
gating the weather risks the Indian economy is exposed to. Potential
prominent players and market projections are also estimated. With the Indian
regulators on the verge of authorising weather derivative trading in the
exchanges at the time of writing, the country is on the way to developing,
deepening and strengthening its weather risk management framework.
Although the contribution of the agriculture sector to India’s overall
wealth has fallen sharply over the past few decades, at the beginning of 2010
the sector still accounted for 23% of the nation’s GDP. With over 60% of the
labour force employed in agriculture, it does not come as a surprise that the
Indian government – in its 11th five-year plan (2007–2012) – principally
focused on improving the contribution of agriculture to the GDP growth to
at least four percentage points.1
With the Indian farmer constantly battling against the twin problems of
mounting debts and crop failures, the need for effective risk management
solutions has never been more pressing.
Risks in the agriculture sector, as a “game of uncertainty”, are associated
with negative outcomes brought about by adverse changes in both the input
and output sides of the game. It can be classified into production (yield) risk,
57

4. WEATHER RISK MANAGEMENT
PANEL 4.1 INDIAN AGRICULTURE – QUICK FACTS
J India sustains 16% of the world’s population on 2.4% of land resource.
J Agriculture in India supports two-thirds of the population, employs 60%
of the workforce and is the single largest private sector occupation.
J 80% of the agricultural land depends on rainfall.
price (market) risk, credit (financial) risk, technology risk, institutional
(policy) risk and personal risk. Weather risk falls under “production risk”,
although it also has a substantial bearing on the price risk faced by farmers
(Gaurav 2008).
Households try to mitigate such risks by adopting various informal insur-
ance techniques, including savings, borrowing at high rates of interest, crop
diversification, etc. Although these measures provide a hedge against the
idiosyncratic risks faced by the farmers, systemic risks leave many house-
holds with great problems. However, there has been one large-scale, formal
risk-hedging effort made by the government to deal with price and yield
risk – state-sponsored insurance schemes offered with directed agriculture
credit.
The performance of these government-subsidised crop insurance schemes
has come under heavy criticism. For instance, in 2000 the scheme collected
Rs211 crores (US$0.48 million) in premiums; however, it also paid out
Rs1,100 crores (US$2.5 million) in claims. These figures have led one critic to
observe that “the performance of the crop insurance scheme in India can
only be judged as disappointing on all counts: financial, economic and
administrative” (Parchure 2002).
Previous studies that examined the drivers of crop losses concluded that
weather (particularly rainfall) contributes to a significant proportion of crop
losses (Parchure 2002). It has been estimated that about 70% of losses during
PANEL 4.2 WEATHER AND GDP – THE WORST HIT
The two most badly affected years over the last 25 years, in terms of
weather conditions, have been 1987 and 2002. In 1987–88, when agri-
cultural GDP fell by 1.39%, overall growth clocked in at 3.8%. In
2002–03, the impact of adverse weather on agriculture was even more
catastrophic, with GDP in the sector fell by 5.99%.
Source: Muralidharan (2008)
58

5. WEATHER DERIVATIVES IN INDIA
the period 1985–86 to 2001–02 were caused by drought (low rainfall), while
20% of losses during the same period were caused by floods (excess rainfall).
The impact of unfavourable weather on other sectors is equally disas-
trous. As of April 2008, the total installed power generation capacity of the
country stood at 0.143 million mega-watts. India’s power sector suffers from
capacity shortages, frequent power failures, poor reliability and deterio-
rating physical and financial conditions. As a public policy, the government
is encouraging environment-friendly sources like hydro and wind energy.
Weather factors like rainfall, snowfall and wind speed will play a critical
role in power generation through these sources.
Monsoons in India also have an adverse impact on the financial markets.
When a majority of the country is experiencing a drought or a flood, the
share markets tend to act in tandem. Businesses in industries such as travel
and tourism, construction, manufacturing and airlines experience consider-
able losses in revenue due to weather hazards. Banks and non-banking
financial institutions that lend to rural portfolios are also indirectly exposed
to weather risk.
One limiting factor for the growth of weather insurance markets has been
the unavailability of re-insurance facilities for weather-indexed products.
An active weather derivative market could increase the ability of the
insurers to hedge against their rural portfolios. Hence, weather-linked
hedging solutions appear to be a natural complement to weather risk
management in India. The main exchanges in India are preparing them-
selves for the next logical step, the introduction of exchange-traded weather
derivatives. These products, when implemented, would bring agricultural
insurance to the capital markets, albeit in an indirect manner.
Figure 4.1 Percentage share of fuel in India’s power sector (2005)
Hydro Nuclear Renewable
26% 3% 5%
Thermal
Hydro
Nuclear
Renewable
Thermal
66%
Source: Sharma and Vashishtha (2007)
59

6. WEATHER RISK MANAGEMENT
As this chapter explores the rationale for the creation of a weather deriv-
ative market in India, it is prudent to begin by understanding the
functioning of the weather insurance market in the country. We will also try
to identify the potential market makers and project potential market size,
explore the challenges in designing weather derivative products, and
discuss how things are expected to progress in the 21st Century.
WEATHER INSURANCE IN INDIA
Since independence in 1947, policy makers in India have understood the
importance of providing agriculture insurance to the majority of the Indian
population whose livelihood is directly or indirectly dependent on agricul-
ture or allied sectors.
With the General Insurance Corporation of India (GIC)2 making
pioneering efforts, crop insurance products have ranged from individual
claim assessment products, area-yield index insurance covers, to the recent
weather-indexed products. The Agriculture Insurance Company of India
(AIC)3 took over the role as the implementing agency from the General
Insurance Corporation. AIC was granted “the overriding authority and
overall responsibility in the operation of the public agriculture insurance
schemes in India” (Sinha, 2007).
Following the causality demonstrated between revenue losses in agricul-
ture and weather in India, a greater interest in developing weather-indexed
insurance products resulted. Weather-index contracts make payments if the
cumulative rainfall during the season falls below (or above) the historical
average. The rainfall insurance is then a put (call) option on this index with
a strike price and premium amount. (See Panel 4.3). This is a viable alterna-
tive to the traditional crop insurance market and has the potential to extend
beyond the farming sector into the corporate end-user market. The key to
unlocking such markets lies in developing the appropriate index.
In 2003 an attempt was made to offer insurance products in which
payouts are based on a rainfall index, with a pilot scheme launched in
Mehboobnagar district, Andhra Pradesh, by the private general insurer
ICICI Lombard General Insurance Company and BASIX, a microfinance
institution (see Panel 4.5). Following this pilot, three risk carriers, ICICI
Lombard General Insurance Company, IFFCO Tokio General Insurance
Company and Agricultural Insurance Company of India (AIC), stepped in
and started to offer weather products commercially.
End-users who purchase weather insurance include farmers, corporations
engaged in contract farming, tea, coffee and sugar producers, wind farms,
salt producers, bio-diesel plantations. Since the introduction of weather-
60

7. WEATHER DERIVATIVES IN INDIA
PANEL 4.3 PAYOUT STRUCTURE OF A WEATHER-INDEXED INSURANCE
PRODUCT – AN EXAMPLE
Consider a contract that is being written to protect against deficient cumu-
lative rainfall during a cropping season. The writer of the contract may
choose to make a fixed payment for every 1mm of rainfall below the
strike. If an individual purchases a contract where the strike is 100mm of
rain and the limit is 50mm, the amount of payment for each tick would
be a function of how much liability is purchased.
There are 50 ticks between the 100 mm strike and 50 mm limit. Thus,
if US$50,000 of liability were purchased, the payment for each 1mm
below 100mm would be equal to US$50,000/(100–50), or US$1,000.
Once the tick and the payment for each tick are known, the indemnity
payments are easy to calculate.
For example, if the realised rainfall is 90mm, there are 10 ticks of
payment at US$1,000 each; the indemnity payment will equal
US$10,000. Figure 4.2 maps the payout structure for a hypothetical
US$50,000 rainfall contract with a strike of 100mm and a limit of 50mm.
Figure 4.2 Payout structure for a hypothetical rainfall contract
60,000
Indemnity payment (US$)
50,000
40,000
30,000
20,000
10,000
0
0 10 20 30 40 50 60 70 80 90 100 110 120 130
Rainfall in mm
Source: Skees (2003)
index insurance products in 2003, over 539,000 farmers have purchased
weather insurance (Staheli, 2007).
Weather insurance covers have already been developed and offered for
crops such as groundnut, oranges, coriander, wheat, soybean, cotton, black
gram, castor and gherkins. Insurers were also working on solutions for agro
61

8. WEATHER RISK MANAGEMENT
PANEL 4.4 TERM SHEET FOR WEATHER INDEX INSURANCE – AN EXAMPLE
Product Reference NA06
Crops Any crop in the district
Reference Weather Station Nalgonda
Index Aggregate rainfall during the cover
phases in mm.
If rainfall on a day is < 2mm it is not
counted in the aggregate rainfall
If rainfall on a day is > 60mm it is
not counted in the aggregate rainfall
Above condition applicable only for
deficit rainfall cover and not for
excess rainfall cover
Definition of Day 1 Month of June at reference station is
observed >= 50mm
If above condition is not met in June,
Policy invariably starts on July 1
Policy Duration 110 days
Cover Phase I II III
Duration 35 days 35 days 35 days
PUT
Strike (mm) < 60 80 –
Exit (mm) < 10 10 –
Notional (Rs/mm) 10.00 10.00 –
Policy Limit (Rs) 1,000 1,000 –
Phase premium (Rs) 90 90
CALL
Strike (mm) > – – 240
Exit (mm) > – – 340
Notional (Rs/mm) – – 10.00
Policy Limit (Rs) – – 1,000
Phase premium (Rs) – – 110
Combined Premium (Rs) 280
Combined policy limit (Rs) 3,000
Data Source Indian Meteorological Department
Settlement Data Thirty days after the data release by
IMD and verified by insurer
Source: Skees (2007)
62

9. WEATHER DERIVATIVES IN INDIA
PANEL 4.5 WEATHER-INDEXED INSURANCE: THE FIRST PILOT
Area Mehboobnagar, Andhra Pradesh
Crops covered Castor and groundnut
Nature of product Against deficit rainfall for the Kharif season
(monsoon) 2003. The index capped rainfall per
sub-period at 200mm
Insurer ICICI Lombard General Insurance Company
MFI support KBS (Krishi Bima Samruddhi), the local area bank
of BASIX one of India’s largest micro-finance
institutions
Premium rates Landholding Premium Maximum
size rates claim
Small (less than
five acres) 400 14,000
Medium (2–5
acres 600 20,000
Large (more than
five acres) 900 30,000
Policy duration 110 days
No. of policies sold 300 individual policies
Source: Ulka Kelkar (2007)
input providers, wind farms, tea plantations, hydro-power projects, sugar
and salt production, contract farming, etc (FWWB 2006).
While the most common weather parameter covered for is rainfall, there
are also covers for temperature, humidity, frost and a combination of such
factors. The composition of weather-index contracts in India can be found in
Figure 4.3.
Some shortcomings that need to be overcome in the weather-indexed
insurance market include (Gaurav 2007):
J Poor weather infrastructure. With only around 8000 weather stations (out
of which a majority are non-automated rain gauges) set up to measure
rainfall (and other weather phenomenon) patterns for the entire nation,
India lacks exhaustive historic weather data for many areas.
63

10. WEATHER RISK MANAGEMENT
Figure 4.3 Weather-indexed insurance contracts – parameters covered
2%
7%
17%
74%
Rainfall index (74%)
Temperature index (17%)
Combined temperature and
rainfall index (7%)
Humidity index (2%)
Source: Staheli (2007)
Furthermore, there is a high entry barrier as data is not digitised and
disaggregated. Some glaring examples include the maintenance of only
two weather stations in Simla, with a complete absence of snowfall data
for the last 30 years. Topographical unevenness also adds to the deteri-
oration in quality of the data, and the computation of actual farm losses
also proves difficult. The ability to cover weather events based on some-
times inadequate data (data with gaps, daily rainfall covers based on
monthly data, etc) is an important requirement – if not, this could
reduce the potential coverage by an order of 30–50%.
J High premium rates. The pricing of insurance products has also been crit-
icised. Premiums have been around 8–22% of payouts, making it
unattractive to potential buyers. This can be attributed to the fact that
reinsurance is not forthcoming in weather insurance due to the reluc-
tance of reinsurers to rely on the existing weather data (with gaps and
limited history). At high premium rates, customer segments do not find
risk transfer very attractive. As a result, many farmers do not renew the
contracts after the initial pilot phase.
J High basis risk. At the execution level, there is a high degree of basis risk
that stems from the lack of weather stations. This is a huge concern since
64

11. WEATHER DERIVATIVES IN INDIA
weather, as a commodity, is “location-specific” and “non-standardised”,
unlike other commodities. Setting up a comprehensive network of
weather stations at strategic locations all over the country is imperative.4
J Lack of product knowledge. Most customers are ignorant about the product.
Given its complexity, marketing the product in the agricultural market is
a huge challenge. This is further exacerbated by a lack of trust in the
insurer. Surveys by various agencies indicated that farmers chose to rely
on informal methods of risk management rather than entering into formal
insurance schemes.
Nevertheless, weather-indexed insurance schemes have emerged as a
pioneering venture in acknowledging the impact of weather on business
and providing a hedge against the same.
WEATHER DERIVATIVES
A financial weather derivative contract may be termed as a weather contin-
gent contract whose payoff will be in an amount of cash determined by
future weather events. The settlement value of these weather events is deter-
mined from a weather index, expressed as values of a weather variable
measured at a stated location. Where insurance generally pays out on the
basis of actual damages, derivatives pay on the basis of difference between
a negotiated “strike” and the actual value of a specific weather parameter,
such as, rainfall, temperature, snowfall, wind speed, etc (Sharma and
Vashistha, 2007).
The first weather derivative contract was entered into in 1996 between
Aquila Energy and the Consolidated Edison Company. The transaction
involved Consolidated Edison’s purchase of electric power from Aquila for
a specific month. Over-the-counter (OTC) trading in weather derivative
instruments began in 1997. Two years later, the Chicago Mercantile
Exchange (CME) introduced exchange-traded weather futures contracts. In
2010 CME was trading weather derivative contracts for 24 cities in the US,
11 in Europe, six in Canada, three in Japan and three in Australia.5
As in any other financial market, the weather derivative market can also
be sub-divided into OTC and exchange-traded segments. While the OTC
market usually focuses on designing tailor-made products for organisations
that face risks associated with weather, the exchange-trade market provides
an opportunity for risk carriers in OTC markets to hedge their risks. Some
of the entities that have weather-related risks set up their in-house weather
trading desk to hedge their portfolios. In most cases, OTC contracts are
65

12. WEATHER RISK MANAGEMENT
PANEL 4.6 ADVANTAGES AND DISADVANTAGES OF INDEX-BASED
WEATHER INSURANCE
Advantages Disadvantages
Reduced moral hazard Basis risk
The indemnity does not depend on the Without sufficient correlation between
individual producer’s realised yield. the index and actual losses, index-
based insurance is not an effective risk
Reduced adverse selection management tool. This is mitigated by
The indemnity is based on widely providing self-insurance of smaller
available third-party information, so basis risk by the farmer, offering
there are few informational asymme- supplemental products underwritten
tries to be exploited. by private insurers, blending index
insurance and rural finance and
Lower administrative costs offering coverage only for extreme
Index-based insurance does not events.
require underwriting and inspections
of individual farms. Precise actuarial modelling
Insurers must understand the statistical
Standardised and transparent structure properties of the underlying index.
Insurer could apply uniform structure
of contracts. Education
Much information is required by users
Availability and negotiability to assess whether index-based insur-
Standardised and transparent, index- ance will provide effective risk
based insurance can be traded in management.
secondary markets.
Market size
Reinsurance function The market is still in its infancy in
Index insurance can be used to more developing countries and has some
easily transfer the risk of widespread start-up costs.
correlated agricultural production
losses. Weather cycles
Actuarial soundness of the premium
Versatility could be undermined by weather
Index products can be easily bundled cycles that change the probability of
with other financial services, facili- the insured events (such as el Niño
tating basis risk management. events).
Forecasts
Asymmetric information about the
likelihood of an event in the near
future will create the potential for inter-
temporal adverse selection.
Source: World Bank (2005)
66

13. WEATHER DERIVATIVES IN INDIA
options because they generally do not carry downside risk and require a lot
of proactive risk management.
Types of weather derivative contracts
A variety of weather parameters have been employed over the years to
develop derivative instruments. Since the energy sector is the most domi-
nant player in the weather derivatives sector, the most common parameter
is temperature. Other weather parameters used include rainfall, snow,
hurricane and frost.
Some significant weather based indexes are defined below.
J Heating degree day (HDD) indexes are derived from daily temperature
observations – a cumulative count of the difference between 18°C and the
daily average temperature6 for each day the temperature falls below 18°C.
Depending upon whether the option is a put option or a call option, the
contract pays out a notional amount per heating degree day that the
actual count differs from the strike.
J Cooling degree day (CDD) indexes are quite similar to HDD contracts, as
they are essentially derived from daily temperature observations. The
CDD indexes are based on a cumulative count of the difference between
18°C and the daily average temperature, for each day that the tempera-
ture is above 18°C.
J Cumulative average temperature (CAT) indexes are commonly used in
European markets. It is cumulative sum of daily average temperature
over the contract period.
J Weekly average temperature (WAT) indexes are short-term indexes designed
to hedge risk of variations in average temperature. The index is based on
the arithmetic average of daily average temperatures for a particular week
(Monday to Friday).
J Rainfall indexes commonly traded across the globe are cumulative
monthly or seasonal rainfall contracts. These indices measure cumulative
rainfall during the period of contract.
J Hurricane contracts have been recently introduced in the market and are
based on the Carvill Hurricane Index (CHI). There are different types of
hurricane index contracts actively traded in market; there are contracts
that focus on the CHI of a particular hurricane, and those that focus on the
CHI of all hurricanes to make landfall within a specific location.
J Snowfall indexes are based on total snowfall (inches) in a specific location.
Indexes can be monthly as well as seasonal.
67

14. WEATHER RISK MANAGEMENT
J Frost degree days index is the accumulation of Frost Index Points over the
period where frost index points shall be recorded whenever one or more
of the predefined conditions are met. Cover period varies from monthly
to seasonal.
Apart from those just listed, a lot of weather protection providers extend
various non-standard products that are very specific to the risks faced by
their client. Many of these contracts are simple or a complex combination of
the products listed above. As the energy sector contributes to more than 50%
of the total contracts traded, the proportion of contracts based on HDD and
other temperature-based covers are high. In fact, HDD and CDD contracts
constitute approximately 90% of total exchange-based contracts.
Potential players in the Indian market and their benefits
Agriculture
A rainfall index futures or options contract may be used by the farmer to
hedge against the volume risk of agriculture in case of deficit rainfall. A put
contract provides protection against the risk from low rainfall in the form of
specified payment per mm of rain. For example, a rainfall index of 750
would mean the futures contract had a notional value of US$7,500 (750 x
US$10). The minimum tick size would be 1.00 rainfall index points with each
having a value of US$10. If a trader were to go short, or sell, the rainfall
futures on the Mumbai Exchange at 750 index points on September 10, 2009,
and on October 10, 2009, and buy the same contract back at 625 index points
Figure 4.4 Farmer’s cashflow
800
Farmer’s cashflow
700
600
500
400
300
200
100
0
–100
0
0
0
0
0
0
0
0
0
0
00
00
00
00
00
00
10
20
30
40
50
60
70
80
90
10
11
12
13
14
15
Source: Alok Shukla, co-author
68

15. WEATHER DERIVATIVES IN INDIA
(thus closing out the position), the trader would show a gain of US$1,250
(US$10 x 125 rainfall index points) on the position taken in September, 2009.
Rainfall index futures are usually not very optimal for farmers due to the
downside risk associated with these contracts. A call or put option contract
is better suited here. For example, consider a farmer who is aware that he
requires at least 750mm rainfall to get a good crop yield. He purchases a put
contract that pays him US$1 per mm of rain if total rainfall in the season goes
below 750mm. He makes an upfront premium of US$50.
Scenario 1: Total rainfall is 900mm; farmer’s cashflow: US$50
Scenario 2: Total rainfall is 500mm; farmer’s cashflow: US$250 – US$50 =
US$200
Agriculture supply chain companies (fertilisers, pesticides, etc) and all the
businesses which are directly or indirectly affected by rainfall can also hedge
their risk of revenue losses due to volatility in rainfall.
Energy sector
Energy sector across world are highly affected by the vagaries of climate.
Extreme weather events affect production as well as consumption. Most of
the hydel power plants run at 100% capacity only during the rainfall season,
and are very highly dependent on rainfall in the catchment area. Due to this
high dependence of hydel plants on rainfall production, the variation is very
high.
The hydel power stations in India have been experiencing sharp dips due
to weather fluctuations. Between April and July 2008 there was an 8% short-
fall in hydro generation in western states compared with targets for the
Table 4.1 Hydel power generation in India (April–July 2008)
Region Target Actual generation Deviation
(million units) (million units) (%)
Northern 18,916.42 18,976.12 0.32
Western 4,531.55 4,175.46 –7.86
Southern 8,743.75 10,336.70 18.22
Eastern 2,992.60 2,568.66 –14.17
North-east 1,712.36 1,364 –20.34
Source: Central Electricity Authority
69

16. WEATHER RISK MANAGEMENT
period, while there was a 14% dip in the eastern and a 20% dip in the north-
east regions of the country (Sharma and Vashishtha 2007).
The rainfall index futures and options can be very helpful in mitigating
risks faced by hydel plants. Other renewable energy sources such as wind
and solar power can also use weather derivatives based on wind speed and
sunshine hours.
Domestic and industrial energy consumption is also dependent on the
weather. A less than average summer can reduce consumption drastically,
which, in turn, affects the revenue of a power supply company. HDD and
CDD contracts can be used very efficiently to hedge such risks.
Corporates exposed to weather risk
Manufacturing and construction companies (which may have to discon-
tinue activities due to unfavourable weather conditions), the airline industry
(which can experience flight delays due to fog/rain), hotels and resorts
(which may attract fewer customers than usual in extreme weather condi-
tions), chemical industries and the fast-moving consumer goods (FMCG)
industry are among the sectors that could also hedge their revenue losses
due to weather fluctuations using derivatives.
Insurance/re-insurance companies
By hedging against those schemes where reinsurance is not forthcoming,
insurance companies would be able to provide better pricing for their prod-
ucts and widen their area of operations, indirectly benefitting the host of
small and marginal farmers who seek insurance.
In an interview with CIRM-IFMR, K. N. Rao of AIC, India, stated that
“Weather insurance is a micro-level product and weather derivatives can be
Figure 4.5 Risk layering for the insurer
Weather
derivatives
Portfolio of several
micro insurances
Weather
insurance
Micro risks in
agriculture
70

17. WEATHER DERIVATIVES IN INDIA
considered the macro hedge for aggregated micro insurance schemes.” He
also added that this can be achieved only if “significant correlations are
derived between the pay-off of the derivative and the pay-outs of the insur-
ance settlement. If the desired correlation is achieved, the socio-economic
cause of achieving 100% agriculture insurance may become a reality.” For
the re-insurers, weather derivatives are a hedge to their portfolios. It may
also extend their portfolios to provide re-insurance to a wider array of insur-
ance schemes.
Banks and financial institutions that lend to farmers
Banks and rural finance institutions could also purchase weather derivatives
to protect their portfolios against defaults caused by weather events. By
hedging against potential bad debts, financial institutions might find them-
selves in a better position to offer extended credit facilities and improved
schemes/policies (loans could be extended for development purposes such
as rainfall harvesting, improved irrigation technology, etc.).
Investors
Weather derivatives could provide liquidity and diversification benefits to
the entire gamut of investors, including hedge fund operators, commodity
traders and international investors/speculators. Other advantages include:
J prices of the underlying asset cannot be manipulated, unlike financial
asset prices;
J prices can be forecasted better; and
J no direct hedge against weather variables exists other than taking a
counter position on the same variable itself (Sharma and Vashishtha
2007).
Government
The government may use weather derivatives to hedge financial setbacks that
arise due to weather hazards. For example, Indian electricity, which is largely
a monopoly, incurs high costs in power generation. This is an important
factor that contributes to the ever-rising fiscal deficit of the country. Applying
weather derivatives may provide a possible solution to this problem.
Estimated market size
It is estimated that trading capital of approx. Rs250–300 billion (US$5–6
billion) could be employed in agricultural equity and commodity derivatives,
71

18. WEATHER RISK MANAGEMENT
an amount that is rising at a rate of around 20–25% per annum. With high
volatility in Indian weather, it is reasonable to expect that approximately
Rs20–100 billion of trading capital could be employed in weather trading
over a period of five years, which means a gross trading turnover of approx-
imately Rs800–4000 billion (US$16–80 billion).7 This could still be on the low
side – Indian markets have shown a large appetite for all kind of derivative
instruments and surpassed initial forecasts.
Regulatory infrastructure
The Forward Markets Commission (FMC) regulates trading in commodities
in India.8 Having identified the need for a weather derivative market, the
Forward Contracts (Regulation) Amendment Bill 2006 for authorising
commodity derivatives was introduced in 2006. Following certain recom-
mendations regarding the bill, a new bill was introduced in 2008; however,
this bill has yet to be passed by parliament due to the unforeseen recent
chain of political crises that the government is combating, ranging from the
inflationary pressures to the nuclear deal and problems around price specu-
lation in the commodity markets.
The inclusion of commodity derivatives within the ambit of a “forward
contract” (as proposed in the bill) would enable trading in commodity
options, weather derivatives, index futures and other such intangibles in the
Indian commodity exchanges. Currently, option trading is not allowed by
the FMC as per Section 19 of the Forward Commission Regulation Act,
1952. Some of the highlights and key issues in the bill are presented in Panel
4.7.
Commodity exchanges
The major nationalised exchanges in India include:
J the Multi Commodity Exchange of India Ltd (MCX), located in Mumbai;
J the National Commodity and Derivatives Exchange Ltd (NCDEX),
located in Mumbai;
J the National Multi Commodity Exchange (NMCE), located in
Ahmedabad; and
J the National Board of Trade (NBOT), located in Indore.
The exchanges design the contracts that are traded on the exchange. Given
the latent demand for derivative/insurance products and the impending
bill, the possibility of trading in weather derivatives is now more of a reality.
72

19. WEATHER DERIVATIVES IN INDIA
PANEL 4.7 HIGHLIGHTS OF THE FORWARD CONTRACTS (REGULATION)
AMENDMENT BILL, 2008
J The Forward Contracts (Regulation) Amendment Bill, 2006 amends the
Forward Contracts (Regulation) Act, 1952 to transform the role of the
Forward Markets Commission (FMC) from a government department to
an independent regulator.
J The powers and responsibilities of FMC with regard to regulating
commodity forward and derivatives market is similar to that of the
Securities and Exchange Board of India (SEBI) in the securities markets.
J The main objective of this bill is to permit and regulate financial instru-
ments that enable buyers and sellers of commodities to effectively
manage risk from price and volume fluctuation.
J Commodity derivatives are contracts that derive their value from differ-
ences in prices of goods or services, activities or events. The bill
permits trading in these derivatives.
J Options on commodities were explicitly prohibited earlier. This bill
allows options trading.
J The bill requires all exchanges to be set up as corporations and sepa-
rates trading rights from ownership in an exchange.
Key issues
J International experience shows that futures markets tend to reduce
price volatility in the underlying cash markets.
J This bill proposes separate regulators and exchanges for securities
markets and commodity markets. This is different from the structure in
most countries.
J While FMC will regulate all commodity derivatives, the markets for the
underlying goods will be regulated by state governments. This could
lead to divergence in regulation.
J Though the trading system for commodity derivatives uses depositories
established under the Depositories Act, 1996, these entities are regu-
lated only by SEBI and not by FMC.
J The lack of a VAT facility for inter-state sales, and limitations of the
Cenvat facility, could deter delivery-based trading in commodity deriv-
atives.
J The penalties applicable for various offences are significantly lower
than that under the SEBI Act, 1992, for similar offences in the securities
market.
Source: PRS Legislative Research (2006)
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20. WEATHER RISK MANAGEMENT
ISSUES OF WEATHER DERIVATIVE PRODUCT DESIGN
Despite the benefits derivatives would provide to a wide range of players,
there are numerous issues that can hamper the designing of a weather deriv-
ative product for the market. Some of these challenges are outlined below.
Lack of infrastructure. Lack of transparent and reliable weather data infra-
structure is a big bottleneck to the weather derivative market. Accuracy of
weather data is extremely critical, as settlement of all the contracts is based
on weather data and a small error in data can cause huge financial losses.
Availability of real-time data on an online platform is essential to get the
required liquidity in exchange-traded derivatives.
Accurate forecasting services. Liquidity is the key to any exchange-traded
derivative, and speculators play a vital role in giving market this liquidity.
Reliable and frequent weather forecast plays an important role in acquiring
liquidity in the weather derivative markets. In most developed markets
three forecasts are released per day, and this substantially increases market
activity at the time that the forecast is released.
Market education. Weather as a phenomenon is understood by almost
everyone, but it is hard for traders to connect weather derivatives with any
other exchange-traded instrument. This is because, unlike equity and
commodity, weather does not have any intrinsic value/price associated
with it. In such a scenario, a more intensive and holistic market education
approach is required to make people comfortable with weather derivatives.
Contract designing. Research efforts in product designing in order to deter-
mine the parameters and type of contracts applicable in the Indian context
are essential. However, given the fact that India is an agriculture dominant
economy and that the rainfall index is already being used in insurance, the
initial derivative products would naturally be centred on the rainfall index.
Temperature seems to be the second most important parameter after rainfall
as it greatly influences the energy sector.
Pricing of the contract. Since the weather derivatives market is, by construc-
tion, incomplete (ie, the underlying asset, namely weather, is not traded),
more traditional derivatives pricing models cannot be easily applied to the
context of weather derivatives. This problem is further exacerbated by the
absence of reliable historical data.
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21. WEATHER DERIVATIVES IN INDIA
Basis risk. Given a high level of basis risk that is inherent in indexed based
contracts, it is imperative to be aware, if these derivatives were to be perfect
hedges for the farmer, that derivatives should be defined on rainfall in each
district or some finer unit of aggregation. However, this will adversely affect
the liquidity of these contracts given that there are about 600 districts in
India. For instance, traders in Mumbai, the financial capital of India, might
not be interested by rainfall in Dungarpur, a remote village in Rajasthan.
This is a cost that has to be incurred in bringing the capital markets and
insurance markets closer to each other. Hence, in the interest of increasing
liquidity, a broader unit of aggregation needs to be found.
Efficient ways of handling the basis risk that arises from such a scenario
need to be devised by market participants. It seems evident that such knowl-
edge is more likely to reside with an insurance company seeking
reinsurance and less likely to reside with a farmer. This, however, is not
unique to the Indian context; for instance, when the CME introduced
exchange-traded weather derivatives, it was linked to a mere 10 cities in the
US (Wei et al, 2003).
CONCLUSION
At this stage, with the Indian economy on an accelerated growth path, the
country cannot overlook the problems associated with unfavourable
weather. Given the complexity and the multitude of the issues and chal-
lenges in managing weather risks, and the critical co-movement between
weather parameters and sectoral outputs, the existing “wide gaps” need to
be bridged.
As and when the regulations are in place, the market will see a diverse
range of participants taking offsetting positions in weather-indexed deriva-
tive contracts. The real challenge is to be able to offer customised products
and effective hedges that bring down the level of basis risk. It is also imper-
ative that various stakeholders understand that exchange-traded weather
derivatives are not a substitute for crop insurance programmes – they
should co-exist with such insurance programmes.
We are seeing the tip of an iceberg in terms of the weather derivatives
market in India is concerned. In view of the significance of agriculture,
power and other key sectors of the Indian economy and their vulnerability
to weather factors, the need to evolve an adequate, sustainable weather risk
management system has now been recognised. Conscientious effort
towards planning, designing and implementing weather derivative prod-
ucts at the grass root level are an immediate requirement. The very fact that
75

22. WEATHER RISK MANAGEMENT
this will affect and transform the life of the common man in India is reason
enough for sustained work in this area.
The authors would like to acknowledge the contributions made by Rupalee
Ruchismita and Mangesh Patankar of the Centre for Insurance and Risk
Management (CIRM), and R. L. Shankar of the Centre for Advanced Financial
Studies (CAFS). The authors would also like to thank Kolli Rao, Sonu
Agrawal, Raj Benahalkar, Mr. Gunaranjan, Ms. Harini, Mr Yoonus and other
experts in the field for their significant inputs.
1 The growth rate of the contribution of agriculture to GDP was at 1.7% percentage points (as
of 2007).
2 Incorporated in 1972, GIC is completely owned by the Indian government, and is controlled
by a single organisation with four subsidiaries: National Insurance Company, New India
Assurance Company, Oriental Fire and General Insurance Company and United India
Insurance Company. With effect from December 2000, these subsidiaries were de-linked
from the parent company and made independent insurance companies. The general insur-
ance companies are also known as property insurance companies and liability insurance
companies, and specialise in insurance in areas such as fire, hail, automobile, inland marine,
aviation, theft, loss, damage, liability, etc. GIC serves as a re-insurer.
3 Incorporated in 2002, AIC is a public sector undertaking promoted by GIC, NABARD and
the four public sector general insurance companies. It offers area-based and weather-based
crop insurance programmes in almost 500 districts of India. It covers almost 20 million
farmers, making it one of the biggest crop insurers in the world. AIC sells various agricul-
ture and allied insurance products and schemes, including the weather-based crop
insurance scheme (WBCIS), the bio-fuel tree/plant insurance policy, wheat insurance and
others.
4 This poses an additional question as to who shall bear the costs of setting these stations, ie,
is it likely to be passed on to the insured in the form of higher premiums? It is also impor-
tant to understand the nature of the subsidies provided by the government, and how they
would help in building infrastructure.
5 Source: www.cmegroup.com/trading/weather.
6 The daily average temperature is defined as the arithmetic average of the maximum temper-
ature (Tmax) and minimum temperature (Tmin).
7 Based on information shared by Sonu Agarwal, CEO of Weather Risk Management Services
(WRMS), India. WRMS is an insurance consultancy firm that has played a pioneering role in
developing the Indian weather market.
8 It must be noted here that India has an unorganised rainfall trading market that amounts to
US$1 billion (Rs50 billion).
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