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Weather risk management


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This chapter therefore analyses the role of weather derivatives in mitigating 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.

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Weather risk management

  1. 1. Weather Risk Management - A Guide for Corporations,Hedge Funds and Investors Publisher: Oxbridge Climate Capital, UK
  2. 2. 4 Weather Derivatives in India Janani Akhilandeswari, Alok Shukla Centre for Insurance and Risk ManagementWith over 70% of Indian agricultural production correlated with themonsoon, weather has historically been a predominant factor in agricultureplanning 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 inthe weather. This means that the insurance industry is constantly on the lookout 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. Potentialprominent players and market projections are also estimated. With the Indianregulators on the verge of authorising weather derivative trading in theexchanges 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 overallwealth has fallen sharply over the past few decades, at the beginning of 2010the sector still accounted for 23% of the nation’s GDP. With over 60% of thelabour force employed in agriculture, it does not come as a surprise that theIndian government – in its 11th five-year plan (2007–2012) – principallyfocused on improving the contribution of agriculture to the GDP growth toat least four percentage points.1 With the Indian farmer constantly battling against the twin problems ofmounting debts and crop failures, the need for effective risk managementsolutions has never been more pressing. Risks in the agriculture sector, as a “game of uncertainty”, are associatedwith negative outcomes brought about by adverse changes in both the inputand output sides of the game. It can be classified into production (yield) risk, 57
  3. 3. 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
  4. 4. WEATHER DERIVATIVES IN INDIAthe period 1985–86 to 2001–02 were caused by drought (low rainfall), while20% 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 thecountry stood at 0.143 million mega-watts. India’s power sector suffers fromcapacity shortages, frequent power failures, poor reliability and deterio-rating physical and financial conditions. As a public policy, the governmentis encouraging environment-friendly sources like hydro and wind energy.Weather factors like rainfall, snowfall and wind speed will play a criticalrole 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, theshare markets tend to act in tandem. Businesses in industries such as traveland tourism, construction, manufacturing and airlines experience consider-able losses in revenue due to weather hazards. Banks and non-bankingfinancial institutions that lend to rural portfolios are also indirectly exposedto weather risk. One limiting factor for the growth of weather insurance markets has beenthe unavailability of re-insurance facilities for weather-indexed products.An active weather derivative market could increase the ability of theinsurers to hedge against their rural portfolios. Hence, weather-linkedhedging solutions appear to be a natural complement to weather riskmanagement in India. The main exchanges in India are preparing them-selves for the next logical step, the introduction of exchange-traded weatherderivatives. These products, when implemented, would bring agriculturalinsurance 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
  5. 5. 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
  6. 6. 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 purchasedweather insurance (Staheli, 2007). Weather insurance covers have already been developed and offered forcrops such as groundnut, oranges, coriander, wheat, soybean, cotton, blackgram, castor and gherkins. Insurers were also working on solutions for agro 61
  7. 7. 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
  8. 8. 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, sugarand salt production, contract farming, etc (FWWB 2006). While the most common weather parameter covered for is rainfall, thereare also covers for temperature, humidity, frost and a combination of suchfactors. The composition of weather-index contracts in India can be found inFigure 4.3. Some shortcomings that need to be overcome in the weather-indexedinsurance 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
  9. 9. 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 since64
  10. 10. 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.4J 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 apioneering venture in acknowledging the impact of weather on businessand providing a hedge against the same.WEATHER DERIVATIVESA financial weather derivative contract may be termed as a weather contin-gent contract whose payoff will be in an amount of cash determined byfuture weather events. The settlement value of these weather events is deter-mined from a weather index, expressed as values of a weather variablemeasured at a stated location. Where insurance generally pays out on thebasis of actual damages, derivatives pay on the basis of difference betweena negotiated “strike” and the actual value of a specific weather parameter,such as, rainfall, temperature, snowfall, wind speed, etc (Sharma andVashistha, 2007). The first weather derivative contract was entered into in 1996 betweenAquila Energy and the Consolidated Edison Company. The transactioninvolved Consolidated Edison’s purchase of electric power from Aquila fora specific month. Over-the-counter (OTC) trading in weather derivativeinstruments began in 1997. Two years later, the Chicago MercantileExchange (CME) introduced exchange-traded weather futures contracts. In2010 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 alsobe sub-divided into OTC and exchange-traded segments. While the OTCmarket usually focuses on designing tailor-made products for organisationsthat face risks associated with weather, the exchange-trade market providesan opportunity for risk carriers in OTC markets to hedge their risks. Someof the entities that have weather-related risks set up their in-house weathertrading desk to hedge their portfolios. In most cases, OTC contracts are 65
  11. 11. 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
  12. 12. WEATHER DERIVATIVES IN INDIAoptions because they generally do not carry downside risk and require a lotof proactive risk management.Types of weather derivative contractsA variety of weather parameters have been employed over the years todevelop derivative instruments. Since the energy sector is the most domi-nant player in the weather derivatives sector, the most common parameteris 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
  13. 13. 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-author68
  14. 14. 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 thedownside risk associated with these contracts. A call or put option contractis better suited here. For example, consider a farmer who is aware that herequires at least 750mm rainfall to get a good crop yield. He purchases a putcontract that pays him US$1 per mm of rain if total rainfall in the season goesbelow 750mm. He makes an upfront premium of US$50.Scenario 1: Total rainfall is 900mm; farmer’s cashflow: US$50Scenario 2: Total rainfall is 500mm; farmer’s cashflow: US$250 – US$50 =US$200Agriculture supply chain companies (fertilisers, pesticides, etc) and all thebusinesses which are directly or indirectly affected by rainfall can also hedgetheir risk of revenue losses due to volatility in rainfall.Energy sectorEnergy sector across world are highly affected by the vagaries of climate.Extreme weather events affect production as well as consumption. Most ofthe 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 thishigh dependence of hydel plants on rainfall production, the variation is veryhigh. The hydel power stations in India have been experiencing sharp dips dueto weather fluctuations. Between April and July 2008 there was an 8% short-fall in hydro generation in western states compared with targets for theTable 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 0.32Western 4,531.55 4,175.46 –7.86Southern 8,743.75 10,336.70 18.22Eastern 2,992.60 2,568.66 –14.17North-east 1,712.36 1,364 –20.34Source: Central Electricity Authority 69
  15. 15. 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 agriculture70
  16. 16. WEATHER DERIVATIVES IN INDIAconsidered the macro hedge for aggregated micro insurance schemes.” Healso added that this can be achieved only if “significant correlations arederived between the pay-off of the derivative and the pay-outs of the insur-ance settlement. If the desired correlation is achieved, the socio-economiccause of achieving 100% agriculture insurance may become a reality.” Forthe re-insurers, weather derivatives are a hedge to their portfolios. It mayalso extend their portfolios to provide re-insurance to a wider array of insur-ance schemes.Banks and financial institutions that lend to farmersBanks and rural finance institutions could also purchase weather derivativesto protect their portfolios against defaults caused by weather events. Byhedging against potential bad debts, financial institutions might find them-selves in a better position to offer extended credit facilities and improvedschemes/policies (loans could be extended for development purposes suchas rainfall harvesting, improved irrigation technology, etc.).InvestorsWeather derivatives could provide liquidity and diversification benefits tothe entire gamut of investors, including hedge fund operators, commoditytraders 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; andJ no direct hedge against weather variables exists other than taking a counter position on the same variable itself (Sharma and Vashishtha 2007).GovernmentThe government may use weather derivatives to hedge financial setbacks thatarise due to weather hazards. For example, Indian electricity, which is largelya monopoly, incurs high costs in power generation. This is an importantfactor that contributes to the ever-rising fiscal deficit of the country. Applyingweather derivatives may provide a possible solution to this problem.Estimated market sizeIt is estimated that trading capital of approx. Rs250–300 billion (US$5–6billion) could be employed in agricultural equity and commodity derivatives, 71
  17. 17. 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
  18. 18. WEATHER DERIVATIVES IN INDIAPANEL 4.7 HIGHLIGHTS OF THE FORWARD CONTRACTS (REGULATION)AMENDMENT BILL, 2008J 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 issuesJ 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) 73
  19. 19. 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.74
  20. 20. WEATHER DERIVATIVES IN INDIABasis risk. Given a high level of basis risk that is inherent in indexed basedcontracts, it is imperative to be aware, if these derivatives were to be perfecthedges for the farmer, that derivatives should be defined on rainfall in eachdistrict or some finer unit of aggregation. However, this will adversely affectthe liquidity of these contracts given that there are about 600 districts inIndia. For instance, traders in Mumbai, the financial capital of India, mightnot 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 andinsurance markets closer to each other. Hence, in the interest of increasingliquidity, a broader unit of aggregation needs to be found. Efficient ways of handling the basis risk that arises from such a scenarioneed to be devised by market participants. It seems evident that such knowl-edge is more likely to reside with an insurance company seekingreinsurance and less likely to reside with a farmer. This, however, is notunique to the Indian context; for instance, when the CME introducedexchange-traded weather derivatives, it was linked to a mere 10 cities in theUS (Wei et al, 2003).CONCLUSIONAt this stage, with the Indian economy on an accelerated growth path, thecountry cannot overlook the problems associated with unfavourableweather. Given the complexity and the multitude of the issues and chal-lenges in managing weather risks, and the critical co-movement betweenweather parameters and sectoral outputs, the existing “wide gaps” need tobe bridged. As and when the regulations are in place, the market will see a diverserange of participants taking offsetting positions in weather-indexed deriva-tive contracts. The real challenge is to be able to offer customised productsand effective hedges that bring down the level of basis risk. It is also imper-ative that various stakeholders understand that exchange-traded weatherderivatives are not a substitute for crop insurance programmes – theyshould co-exist with such insurance programmes. We are seeing the tip of an iceberg in terms of the weather derivativesmarket in India is concerned. In view of the significance of agriculture,power and other key sectors of the Indian economy and their vulnerabilityto weather factors, the need to evolve an adequate, sustainable weather riskmanagement system has now been recognised. Conscientious efforttowards planning, designing and implementing weather derivative prod-ucts at the grass root level are an immediate requirement. The very fact that 75
  21. 21. 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: 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). REFERENCES Campbell, S. and F. Diebold, 2000, “Weather Forecasting for Weather Derivatives”, The Wharton Financial Institutions Center Working Paper series. Cao, M., A. Li and J. Zhanshun Wei, 2003, “Weather Derivatives: A New Class of Financial Instruments” URL: 1016123.76
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