BEHAVIOUR OF SPOT AND FUTURES PRICES OF AGRICULTURAL COMMODITIES VIS-À-VIS POLICY IMPACT

Transcription

1 BEHAVIOUR OF SPOT AND FUTURES PRICES OF AGRICULTURAL COMMODITIES VIS-À-VIS POLICY IMPACT Thesis submitted to the University of Agricultural Sciences, Dharwad In partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Agribusiness Management By CHIDANAND PATIL DEPARTMENT OF AGRIBUSINESS MANAGEMENT COLLEGE OF AGRICULTURE, DHARWAD UNIVERSITY OF AGRICULTURAL SCIENCES, DHARWAD JUNE, 2014

2 ADVISORY COMMITTEE DHARWAD JUNE, 2014 (BASAVARAJ BANAKAR) CHAIRMAN Approved by: Chairman: (BASAVARAJ BANAKAR) Members: 1. (H. BASAVARAJ) 2. (S. B. MAHAJANASHETTI) 3. (A. R. S. BHAT) 4. (R. A. YELEDHALLI) 5. (L. MANJUNATH)

3 CONTENTS Sl. No. Chapter Particulars CERTIFICATE ACKNOWLEDGEMENT LIST OF TABLES LIST OF FIGURES LIST OF APPENDICES 1. INTRODUCTION 2. REVIEW OF LITERATURE 2.1 Growth rate analysis 2.2 Estimation of Coefficient of variation, contango and backwardation analysis 2.3 Correlation analysis 2.4 Co-integration analysis 2.5 Regression analysis 2.6 Chow test technique 3. METHODOLOGY 3.1 Detailed programme of work 3.2 Analytical tools used 3.3 Terms and concepts used in the study 4. RESULTS 4.1 Growth rate in production of selected agricultural commodities 4.2 Behaviour of spot and futures prices of selected agricultural commodities 4.3 Interrelationship among production, spot prices and futures prices 4.4 Impact of volume of transactions on futures prices 4.5 Effect of futures ban of selected agricultural commodities on their spot prices 5. DISCUSSION 5.1 Growth rate in production of selected agricultural commodities 5.2 Behaviour of spot and futures prices of selected agricultural commodities 5.3 Interrelationship among production, spot prices and futures prices 5.4 Impact of volume of transactions on futures prices 5.5 Effect of futures ban of selected agricultural commodities on their spot prices 6. SUMMARY AND POLICY IMPLICATIONS REFERENCES APPENDICES

4 LIST OF TABLES Table No. Title 4.1 Compound growth rate in production of selected agricultural commodities in India 4.2 Behaviour of spot and futures prices of wheat during different periods 4.3 Measures of dispersion of spot prices of wheat in the commodity exchange during different periods 4.4 Measures of dispersion of futures prices of wheat in the commodity exchange during different periods 4.5 Behaviour of spot and futures prices of sugar during different periods 4.6 Measures of dispersion of spot prices of sugar in the commodity exchange during different periods 4.7 Measures of dispersion of futures prices of sugar in the commodity exchange during different periods 4.8 Behaviour of spot and futures prices of chana during different periods 4.9 Measures of dispersion of spot prices of chana in the commodity exchange during different periods 4.10 Measures of dispersion of futures prices of chana in the commodity exchange during different periods 4.11 Behaviour of spot and futures prices of turmeric 4.12 Measures of dispersion of spot and futures prices of turmeric in the commodity exchange 4.13 Correlation between average annual spot prices and production of wheat, sugar, chana and turmeric 4.14 Dickey-Fuller Test for stationarity of price series for futures and spot prices of wheat 4.15 Co-integration between futures price and spot prices of wheat 4.16 Dickey-Fuller Test for stationarity of price series for futures and spot prices of sugar 4.17 Co-integration between futures price and spot prices of sugar 4.18 Dickey-Fuller Test for stationarity of price series for futures and spot prices of chana 4.19 Co-integration between futures price and spot prices of chana 4.20 Dickey-Fuller Test for stationarity of price series for futures and spot prices of turmeric 4.21 Co-integration between futures price and spot prices of turmeric 4.22 Impact of volume of transaction of wheat on its futures prices during different periods 4.23 Impact of volume of transaction of sugar on its futures prices during different periods 4.24 Impact of volume of transaction of chana on its futures prices during different periods 4.25 Impact of volume of transaction of turmeric on its futures prices 4.26 Chow test showing structural break in daily spot prices before and during futures ban of wheat 4.27 Chow test showing structural break in daily spot prices before and during futures ban of sugar 4.28 Chow test showing structural break in daily spot prices before and during futures ban of chana

5 LIST OF FIGURES Figure No. Title 4.1 All India production of wheat 4.2 All India production of sugarcane 4.3 All India production of sugar 4.4 All India production of chana 4.5 All India production of turmeric 4.6 Co-integration between spot and futures prices of wheat 4.7 Co-integration between spot and futures prices of sugar 4.8 Co-integration between spot and futures prices of chana 4.9 Co-integration between spot and futures prices of turmeric LIST OF APPENDICES Appendix No. Title I. All India production of wheat II. All India production of sugarcane III. All India production of sugar IV. All India production of chana V. All India production of turmeric VI. Impact of volume of transaction of wheat on its futures prices during pre-ban period VII. Impact of volume of transaction on futures prices of wheat during reintroduction period VIII. Aggregate (pre-ban + reintroduction periods) impact of volume of transaction of wheat on its futures prices IX. Impact of volume of transaction of sugar on its futures prices during pre-ban period X. Impact of volume of transaction of sugar on its futures prices during reintroduction period XI. Aggregate (pre-ban + reintroduction periods) impact of volume of transaction on futures prices of Sugar XII. Impact of volume of transaction of chana on its futures prices during pre-ban period XIII. Impact of volume of transaction of chana on its futures prices during reintroduction period XIV. Aggregate (pre-ban + during ban periods) impact of volume of transaction of chana on its futures prices XV. Impact of volume of transaction of turmeric on its futures prices

6 INTRODUCTION The recent increases in the overall price rise of commodities have brought into the question of both the sustainability of current economic growth process and the efficiency of public management of price rise. The global rises in prices of commodities reached extremely higher levels were argued that, it had nothing to do with futures trading or speculation in the commodity exchange markets. Eminent economists joined bankers, financial market consultants and even policy makers in emphasizing these price rises were all about fundamentals that reflected in the real changes occurred in the demand and supply (Mahalakshmi, 2010). Here, in fact, the mismatch between demand and supply in important commodities such as Wheat, pulses and Sugar, suggesting that unexpected output shortfalls of these crops led to a temporary rise in prices, and that this increase would get mitigated once supplies were enhanced, for instance, through imports. However, it is misleading to considered only the crop failures for what happened, essentially a policy-created process that was subsequently mismanaged. Further, it is argued that the government allowed the entry of large (and multinational) private players into the grain trade and opened up the futures market for trading in these essential commodities, which all have a history of being hoarded. The rapid rise in prices was hard to explain without bringing empirical evidences about the role of futures trading and speculation in the commodity exchange markets. Commodity futures Commodity futures are agreements of contracts that are utilized to purchase or sell a specified amount of a given commodity. The agreement will commit the buyer and the seller to a fixed price that will be in effect on a specified future date. When this future date arrives the buyer is expected to have paid the agreed upon price for the futures, and the seller will have delivered ownership of the commodities to the buyer. Commodity futures are based on physical commodities that include items such as gold, silver, other precious metals and grains. Commodity futures are based on the perceived worth of the goods today and at some future point in time. Futures on these types of goods recognize two factors. First, the physical commodity already exists. Second, there is anticipation on the part of the buyer that the commodity will increase in value over time. When this is the case, a buyer will choose to enter into a commodity future agreement with a seller. The price that is ultimately paid is considered to be sufficient for the seller to make a profit from the venture. At the same time, the buyer is anticipating that the value of the goods will rise beyond the sale price and thus ultimately generate a return on the investment (Mahalakshmi, 2010). Futures market The participants in a commodities futures market can be divided broadly into hedgers and speculators depending on their attitude towards risk. While hedgers are those risk-aversive agents who try to shift the price risks associated with volatile nature of prices in a deal by opting for a fixed price decided in the present by the means of futures, speculators are those who are willing to take risks and intend to reap benefits out of the speculated changes in price of the derivative itself. While hedgers are concerned about protecting against wide fluctuations in prices and securing a fixed price for the commodity underlying the derivative speculators are concerned about possible fluctuations in the price of the derivative itself and the profits that can be reaped from them. Most of the times it is noticed in a real world market that though the same agent may act as hedger at one instance and a speculator at another, the general rule is that hedgers form the two extreme ends of a chain of transactions (the persons who really intend to buy or sell the commodity as such and not merely the derivative, that is mostly the producers and the final demanders of the commodity) the intermittent roles are filled by a number of speculators who may further be divided into a number of categories like arbitragers, day-traders, etc. So, in a way, a futures market is a forum for trade offs in risk between the risk aversive hedgers and the risk taking speculators. Both speculators and hedgers have their own demand and supply schedules and it is an interaction between these market forces that fix prices in a future market, if they are given a free hand. Though speculators and hedgers account for the demand and supply equations in a futures market, they are not the only entities that matter. Clearance houses and brokers are the people who really appear in the pit. Clearance firms ensure that the contracts are compiled with. In every deal between two parties, clearance houses stand between the parties, taking the stand opposite to what each party has taken. That is, the person taking short position sells the commodity to the clearance house and the person taking long position buys the contract from the clearance house. Clearance

7 houses require the parties to deposit a margin, proportional to the worth of the deal so that performance can be assured. Brokers are hired by parties to trade on their behalf in the market, in accordance to a range of orders that are exercised by the party from time to time. An issue of theoretical and academic interest and of regulatory concern is the gap between future and spot prices. This is a concern or the policy makers because a huge gap between spot and future prices may create a tilt in favour of either future or spot market at the expense of the other thereby affecting the demand and supply equations in the macroeconomic picture and causing consequent fluctuations in the related macroeconomic variables. The difference between spot and future prices is known as Basis. (Basis = P t P o where P t is future price and P o is spot price). In a normal market Basis is positive while in an inverted market Basis is negative. The difference in prices tends to decrease and the prices tends tend to converge bringing down Basis to zero as the month of delivery approaches. The convergence of prices occurs because any non-zero Basis at a period close to the month of delivery will provide the traders ample opportunities of arbitrage and as they reap these opportunities the Basis will come closer and closer to zero. Another feature of futures markets that calls for regulation is that traders in futures markets need merely a small proportion of the money that the trade is worth to be deposited as margins. This enables traders to enter into deals which are worth many times more than the money they have at their disposal. Such transactions are indeed undertaken by speculators who act as retail investors or day traders with the plans of reversing the trade position before the maturity of the future. But if such a reversal becomes impossible owing to huge fluctuations, a number of traders may face bankruptcy and even the presence of clearance houses may not be able to eliminate counter-party risks (Risk of non performance by the other party to the contract). History of commodity futures trading The history of organized commodity derivatives in India goes back to the nineteenth century when the Cotton Trade Association started futures trading in 1875, barely about a decade after the commodity derivatives started in Chicago. Over time the derivatives market developed in several other commodities in India. Following cotton, derivatives trading started in oilseeds in Bombay (1900), raw jute and jute goods in Calcutta (1912), wheat in Hapur (1913) and bullion in Bombay (1920). However, many fuelled that derivatives fuelled unnecessary speculation in essential commodities and were detrimental to the healthy functioning of the markets for the underlying commodities, and hence to the farmers. With a view to restricting speculative activity in cotton market, the Government of Bombay prohibited options business in cotton in Later in 1943, forward trading was prohibited in oilseeds and some other commodities including food grains, spices, vegetable oils, sugar and cloth. After Independence, the parliament passed Forward Contracts (Regulation) Act, 1952 which regulated forward contracts in commodities all over India. The Act applies to goods, which are defined as any movable property other than security, currency and actionable claims. The act prohibited options trading in goods along with cash settlements of forward trades, rendering a crushing blow to the commodity derivatives market. Under the act, only those associations/exchanges, which are granted recognition by the Government, are allowed to organize forward trading in regulated commodities. The act envisages three-tier regulation: (i) The Exchange which organizes forward trading in commodities can regulate trading on a day-to-day basis; (ii) the Forward Market Commission provides regulatory oversight under the powers delegated to it by the central Government, and (iii) the Central Government Department of Consumer Affairs, Ministry of Consumer Affairs, Food and Public Distribution is the ultimate regulatory authority. The already shaken commodity derivatives market got a crushing blow when in 1960s, following several years of severe draughts that forced many farmers to default on forward contracts (and even caused some suicides) ; forward trading was banned in many commodities considered primarily or essential. As a result, commodities derivative market dismantled and went underground where to some extent they continued as over the counter contracts at negligible volumes. Much later, in 1970s and 1980s the Government relaxed forward trading rules for some commodities, but the market could never regain the lost volumes. After the Indian economy embarked upon the process of liberalization and globalization in 1990, the Government set up a Committee in 1993 to examine the role of futures trading. The Committee (headed by Prof. K. N. Kabra) recommended allowing futures trading in 17 commodity groups. It also recommended strengthening of the Forward Markets Commission, and certain amendments to Forward Contracts (Regulation) Act 1952, particularly allowing options trading in goods and registration of brokers with Forward Markets Commission. The government accepted most

8 of these recommendations and a futures trading was permitted in all recommended commodities. Commodity futures trading in India remained in a state of hibernation for nearly four decades, mainly due to doubts about the benefits of derivatives. Finally a realization that derivatives do perform a role in risk management led the government to change its stance. The policy changes favouring commodity derivatives were also facilitated by the enhanced role assigned to free market forces under the new liberalization policy of the Government. Indeed, it was a timely decision too, since internationally the commodity cycle is on the upswing and the next decade is being touted as the decade of commodities (Tamaragundi et al., 2010). It was in 2003 that the union government lifted all prohibitions on futures trading and even allowed online trading of essential commodities in newly established commodity exchanges. The National Agriculture Policy announced in July 2000 and the announcements of Hon ble Finance Minister in the budget speech for were indicative of the Governments resolve to put in place a mechanism of futures trade/market. As a follow up the Government issued notifications on permitting futures trading in the commodities, with the issue of these notifications futures trading is not prohibited in any commodity. However, opposition to futures trading in essential commodities gathered momentum in the backdrop of high inflation being experienced in the country since 2006, particularly the sharp rise in prices of essential commodities. The Standing Committee on Food, Consumer Affairs and Public Distribution in its report on the Forward Contract Regulation (Amendment) Act submitted in December 2006 arrived at a unanimous conclusion: Agricultural commodity especially food grains including coarse grains, pulses and Sugar need not be permitted to be traded in the commodity markets including forward/future contract derivatives and options. The political heat generated on this issue coupled with sustained pressure forced the then union government to ban futures trading in four commodities wheat, rice, tur and urad, in early Alongside, a five-member committee was also constituted by the government to study the impact of futures trading on wholesale and retail prices of agricultural commodities. Expert committee report on futures trading in agricultural commodities The Expert Committee to study the Impact of Futures Trading on Agricultural Commodity Prices (ECFT), chaired by Planning Commission member Prof. Abhijit Sen, has recently submitted its report to the government. The main report, which has been agreed upon by all the committee members, states: current evidence available does not provide any conclusive evidence about whether there is any causal relationship between futures trading and rise in prices of the agricultural commodities. However, it needs to be noted that the evidence collated and analyzed by the ECFT report does not rule out the possibility of futures trading contributing to inflation. Both monthly and weekly data show that the annual trend growth rate in prices was higher in the post-futures period in 14 commodities, viz., chana, pepper, jeera, urad, chillies, wheat, sugar, tur, raw cotton, rubber, cardamom, maize, raw jute and rice; and lower in seven commodities, viz., soy oil, soybean, rape seed/mustard seed, potato, turmeric, castor seed and gur. The number of commodities in which inflation accelerated is double the number in which this decelerated, and their weights are also much higher in both futures trading and in the Wholesale Price Index (WPI). Also, significantly, all sensitive commodities (i.e., foodgrains and Sugar) recorded some acceleration in inflation after the start of futures trading. There is the problem that the period during which futures markets have been in operation is much too short to discriminate adequately between the effect of opening up futures markets and what might simply be normal cyclical adjustments. Thus, while the price rise of most of agricultural commodities in the post-futures trading period is clearly established, whether or how much futures trading has caused or contributed to the price rise could not be conclusively ascertained. Significance of Commodity Derivatives in the Indian Economy The gradual evolution of commodity markets in India has been of great significance for both the country s general economic prosperity and the financial sector in particular. From an investment standpoint, a commodity is considered as an alternate asset class and investing in commodity futures is appealing to investors as commodities have a significantly lower degree of association with other traditional asset classes and offer an effective hedge against inflation. Besides being a unique hedging instrument, it also provides for efficient portfolio management arising from diversification benefits, which result in improved returns to domestic as well as international investors. The commodity futures market as an asset class provides commercial commodities producers and consumers with a means to transfer price risk to speculators who have no direct commercial interest in the commodities themselves. Producers hedge price risk by taking short

9 positions in future contracts on the commodity that they produce. A similar hedge requires consumers to seize long positions in the futures contracts on their consumption commodities. Arbitrageurs and speculators choose to take either long or short positions on a commodity futures contract based on their market perception (Tamaragundi et al., 2010). Commodity exchanges in India National Multi Commodity Exchange (NMCE) was the first exchange to be granted permanent recognition by the government, where futures trading started from 26th November, 2002 in 24 commodities. Subsequently, Multi Commodity Exchange of India (MCX), National Commodity and Derivatives Exchange Limited (NCDEX), Indian Commodity Exchange (ICEX) and Ace Commodity Exchange (ACE) commenced their operations, respectively, from November 2003, December 2003, November 2009 and October 2010 respectively. Apart from these, there are about 16 recognized regional futures exchanges in India with more than 3000 registered members. Trading platforms can be accessed through terminals spread across 800 towns/cities across the country. Forward Markets Commission (FMC) under the Ministry of Consumer Affairs is the chief regulator of futures trading in India (Sendhil et al., 2013). Policy changes Government of India had banned the futures trading in wheat, sugar and chana on 27 th February 2007, 26 th May 2009 and 7 th May 2008 respectively. Again the government lifted the ban in these commodities on 15 th May 2009, 30 th September 2010 and 30 th November 2008 respectively. Importance of wheat, sugar, chana and turmeric in Indian economy Importance of wheat in Indian economy The world production of Wheat figures over million tons ( figures) from an area of million ha. Globally, India is the second largest producer next to China with maximum area under Wheat. However, in terms of productivity, it is ranked thirteenth in the world and marginally less relative to world average of 2717 Kg/ha. Wheat is a major crop in India covering about million ha with production around million tons ( ). Average yield of wheat in India is around 3119 kg/ha and around 90 per cent of Wheat area is irrigated. Uttar Pradesh is the major wheat producing state (30.30 million tons) followed by Punjab (16.10 million tons) and Madhya Pradesh (13.13 million tons). It is a major cereal consumed both directly and also in the processed form. Total wheat export in was 0.74 million tons and in it was 6.50 million tons. Increase in export was due to surplus production in and lack of storage to stock the surplus wheat. India has imported 22 tons of wheat in and 2944 tons in respectively. Market influencing factors of wheat Wheat is an annual, seasonal crop and prices usually tend to rise during the cultivation period, i.e. December to March due to scarcity in the market and dip during the peak arrival period (April and May). Weather has a profound influence on production, especially in Haryana and Punjab as temperature plays a crucial role in determining the yield. The government policies with regard to Minimum Support Price (MSP), buffer stocks, Public Distribution System (PDS) sales, Open Market Sales, imports / exports are very important influencing factor with regards to Indian Wheat prices. Despite international trade being limited, the several variations in production or consumption at various major or minor producing or consuming country, which influence global prices, which are reflected in the domestic long-term price trend. However, in the short-term normally there is no significant relation with international prices. Several international agencies like United States Department of Agriculture, International Grains Council, Food and Agricultural Organization release regular, periodic reports on global supply-demand situation, which is widely looked upon by the global players. Wheat futures contract was launched on National Commodity Derivative Exchange (NCDEX) platform in April NCDEX Wheat futures provide a hedging platform to those who are natural traders of the commodity. Even an arbitrager can trade using strategies like cash and carry and calendar spread. Speculators can take directional view on future prices and accordingly take position in Wheat futures.

10 Importance of sugar in Indian economy India is the second largest producer of sugar in the world followed by Brazil. India s share in world production is 13.6 per cent in Brazil is the largest exporter of sugar followed by Thailand and Australia. India is the fifth largest exporter of sugar. India s share in total global export is 4.9 per cent during Indonesia, European Union and United States are the major sugar importing countries. India s share in total global import in was 2.14 per cent. Sugarcane is a major crop covering about 5.06 million ha with production around million tons ( ). Average yield of sugarcane in India is around t/ha and around 90 per cent of sugar area is irrigated. Uttar Pradesh is the major sugar producing state (25 million tons) followed by Punjab (15 million tons). India produced around 248 lakh MT of sugar during India is the world s largest consumer of sugar, accounting for 15 per cent of global consumption. Sugar future started trading on NCDEX platform from August 2007 onwards. Factors influencing prices of sugar The Central Government fixes the Fair and Remunerative Price (FRP) for sugarcane. Some of the State Governments announce State Advised Prices (SAPs) for sugarcane, generally higher than the FRP. Ministry of Food and Consumer Affairs, every month give monthly quota for sugar mills to release amount of Sugar for sale in the open market. Mills have to sell 10 per cent of the quota to government for PDS (Public Distribution system) known as levy quota and rest for sale in the open market as non levy quota. The foreign trade policy of the government indicated that the controls over import and export of sugar under Open General License (OGL) and Advance License Scheme (ALS). The by-products will be allotted by government for ethanol and other by-products production. At the same time Stock holding and Turnover Limits fixed to the mills by the government. The other factors which influence the prices are command area, recovery, acreage and international markets. Apart from demand and supply, there are other major factors which influence and determine the sugar prices. The commodity falls under the purview of the essential commodities act, Market participants trading in sugar futures should track the market by tracking and analyzing demand and supply position including beginning stock, production, imports, consumption, exports and ending stocks and government policies such as sugarcane pricing, monthly levy and non levy sugar quota, stock holding limit, turnover limit and export policy. Importance of chana in Indian economy India is by far the largest chickpea producing country. Other important Chickpea producing countries are Pakistan, Turkey, Mexico, Canada and Australia covering an area of 120 lakh ha at globe. South Asian countries such as India, Pakistan, Bangladesh and Sri Lanka are all importers of pulses. India, the world s largest producer, importer and consumers of a wide range of pulses is obviously a focus of attention, especially for exporting countries such as Canada, Australia, United States and Myanmar. India is the largest producer of chana followed by Pakistan, Turkey and Iran. India produced around 8.88 million tons of chana during and contributes around 70 per cent of the total world production. India exported 1.70 lakh MT of chana during and imported 2.06 lakh MT during the same period. Madhya Pradesh is the largest producer of chana (3.29 million tons) followed by Rajasthan (0.99 million tons) and Maharashtra (0.82 million tons). Chana is the most largely produced pulse crop in India, accounting about 40 per cent of the total pulse production. Chana Future started trading on NCDEX platform from April 2004 onwards. Factors influencing prices of chana Chana can withstand moisture stress to a certain extent. However, the production is highly fluctuates between years, depending on the rains received and the moisture availability in the soil. The sentiments of traders play a significant role currently, as a consequence of the lack of freeflow of information. Stocks present with stockiest and the stocks-to-consumption ratio. Imports and the crop situation in the countries from where imports originate, viz., Canada, Australia, Myanmar and there is high substitutability between pulses in India among the consumers. So the prices of other major pulses like tur, yellow peas, green peas etc also influence the prices of chana. Importance of turmeric in Indian economy At the global level, turmeric production is distributed across the Asian region and Nigeria in Africa. Among the Asian countries, turmeric is widely cultivated in India, China, Myanmar and

11 Bangladesh. India is the largest producer, consumer and exporter of turmeric. Other producers in Asia include Pakistan, Taiwan, and Indonesia. Turmeric is also produced in the Caribbean and Latin America: Jamaica, Haiti, Costa Rica, Peru, and Brazil. Global production of turmeric is estimated around 6 to 7 lakh tons. India exports about 10 per cent of its Turmeric per annum. The key export destination for Indian turmeric are UAE - 17 per cent, USA 10 per cent, Bangladesh 9 per cent, Sri Lanka - 7 per cent, Japan - 7 per cent, Malaysia 6 per cent and UK - 6 per cent. All these countries together account for 65 per cent of the India s exports. Remaining 25 per cent is being shipped to Europe, North America, Central and Latin American Countries. The turmeric production in India during was 1167 thousand tons. The turmeric production in was more than 85 lakh bags (1 bag = 75 kg), a historic high. With a carry forward stock of 15 lakh bags, total availability was around one crore bags, which was double the domestic demand of 50 lakh bags. It was believed that the available stock can even meet the requirement of also. The important turmeric growing states in India are Andhra Pradesh, Tamil Nadu, Orissa, Maharashtra, Assam, Kerala, Karnataka and West Bengal, in which Andhra Pradesh occupies 40 per cent of total turmeric area followed by Orissa and Tamil Nadu occupying 17 per cent and 13 per cent of total turmeric area respectively. In terms of production Andhra Pradesh accounts 60 per cent of total Turmeric production in India followed by Tamil Nadu (13%) and Orissa (12%). Turmeric futures contract was launched on NCDEX platform in April 2004 and since then it has witnessed considerable participation from various supply chain participants. Using futures platform, producers can minimize their price risk. With ever increasing export demand exporters can insure themselves against price risk. Good stocks of turmeric provide good arbitrage opportunities to the various market participants. Being highly liquid contract speculators can easily enter or exit the market. Thus the turmeric contract provides space for every investor category. Factors influencing prices of turmeric Price influencing factors are the area under turmeric, weather progress, final crop output, stock level - carry forward stocks and stock with farmers/traders/warehouses and domestic and export demand. The study is intended to assess the effect/impact/relationship of futures prices with spot prices and production along with the changes in the policy of the government in allowing agricultural commodities to trade in futures market. Therefore, it is planned to select one commodity from cereals, pulses, spices and commercial products for detailed analysis, because continuation of futures trading in spices and prohibiting futures trade in pulses and sugar in some years and allowing in some years was seen. Finally it wants to delineate the reasons for high fluctuations in prices in the domestic markets due to futures prices or due to mismatch between supply (production) and demand or due to illegitimate speculation in futures market. Specific objectives 1. To analyse the growth in production of selected agricultural commodities considered for futures trading 2. To analyse the behaviour of domestic (spot) prices and futures prices of selected agricultural commodities in the commodity exchange 3. To study the interrelationship among production, spot prices and futures prices 4. To study the impact of volume of transactions on futures prices 5. To study the impact of ban on futures trading in the selected agricultural commodities in commodity exchange on spot prices Hypotheses 1. There is positive growth in production of selected agricultural commodities due to the introduction of futures trading 2. There is a stability in wholesale prices of selected agricultural commodities after the introduction of futures trading 3. There is a positive relationship exists among production, spot and futures prices 4. Volume of transactions depends on the futures prices 5. There is a change in the price behaviour of spot prices due to the ban of futures trading

12 Presentation of the study The entire study has been presented in seven chapters. Chapter I highlights the introduction to the topic, significance of commodity derivatives in the Indian economy, policy changes, importance of wheat, sugar, chana and turmeric in Indian economy, specific objectives of study and hypotheses of the study. Chapter II includes the review of earlier studies connected with present investigation. Chapter III explains the methodology i.e., selection of markets, nature and sources of data, and the tools and techniques of analysis adopted for evaluating the objectives of the study. Chapter IV is devoted to the analysis of the data through a variety of tables into which relevant details have been compressed and summarized under appropriate heads and presented in the tables. Chapter V provides the casual relationship between certain variables and the outcome which they produced. Chapter VI briefs the summary of the main findings along with the policy implications that emerged from the findings of the study. Chapter VII the final chapter lists the references cited while undertaking the research.

13 REVIEW OF LITERATURE A review of concepts and empirical studies related to the present study would be helpful to project the current thinking on the subject matter of study as well as to formulate relevant concepts and design of the study to draw meaningful conclusions. This would help the researcher to have better and precise understanding of the current research problem and would also facilitate to modify and improve the present study. This chapter briefly reviews the concepts, analytical tools and findings of the past studies, which are relevant for the present study. The reviews of the past studies were classified under the following headings. 2.1 Studies related to the growth rate analysis 2.2 Studies related to the coefficient of variation, contango and backwardation analysis 2.3 Studies related to the correlation analysis 2.4 Studies related to the co-integration analysis 2.5 Studies related to regression analysis 2.6 Studies related to chow test technique. 2.1 Studies related to the growth rate analysis Asfaw (2000) in his study on agricultural performance in Sub-Saharan African countries reported that during period both area and yield contributed to increase total foodgrain production. Countries during , all the countries had negative growth in area and production. During the third period ( ) all the countries experienced expansion in area and production under food grains. This is attributed to Structural Adjustment Policy (SAP) initiatives. Lakhana (2003) in his study on production, price behaviour and export of groundnut in India with special reference to Gujarat state, for pre- Technology Mission of Oilseeds (TMO) ( to ), post-tmo (Technology Mission of Oilseeds) ( to ) and for the entire period ( to ) of selected markets Rajkot, Junagadh, Kalawad and Amrelin. The post-tmo period had witnessed positive growth rates in area, yield and production. Growths rates of area for Junagadh and Rajkot districts as well as for the state of Gujarat as a whole were positive and significant. However, growth rates of yield were negative throughout the study area during pre-tmo. During post-tmo, growth rates of all variables were found to be positive. Varghese (2004) worked out the trend in area, production and productivity of cardamom in Kerala for a period from to using semi-logarithmic growth equation. The area under cardamom registered a negative growth rate (-1.216%) which was significant. The output and yield registered average annual growth rate of 4.14 per cent and 5.51 per cent respectively. Lathika and Kumar (2005) analyzed the growth trends in area, production and productivity of coconut for different coconut producing states/union territories in India for two sub-periods; phase I (1951 to 1995) and phase II (1996 to 2002). Area showed positive growth in both phases for selected states except for the Andaman and Nicobar Islands where the growth was negative (-9.69) in II phase. Production also showed a positive growth in all the states in both the phases and Andhra Pradesh had highest growth in II phase (16.69%). The growth rate of productivity showed negative growth in Kerala and Orissa in the I phase, Karnataka in the II phase. Jose and Jayasekhar (2008) studied the growth trends in area, production and productivity of arecanut in India during the period from 1971 to 2004 and revealed that the area and the production of arecanut in India increased tremendously at the rate of 2.20 per cent and 3.20 per cent respectively. The rate of increase in both area and production is mainly due to favourable price prevailed during the period. Patil (2009) studied the growth in area and production of chilli in India. The results revealed that the country as a whole experienced significant growth in chilli production and yield, whereas area registered negative growth rate during period and also for pre and post WTO scenarios positive significant growth in production and yield was observed, but area experienced negative growth. The magnitude of area, production and yield instability for between pre and post WTO periods shows that the variability had decreased.

14 Angles et al. (2011) analysed the compound growth rate in production of Indian turmeric. They observed the compound growth rates of 7.97 per cent, 3.42 per cent and 5.86 per cent for preliberalization period ( to ), post-liberalization period ( to ) and overall period ( to ) respectively at one per cent level of significance. Bandi (2011) analysed the compound growth rate in area, production and productivity of sugarcane and sugar in India for the period to He found the CAGR of 0.77 per cent, 0.28 per cent and per cent for area, production and productivity of sugarcane in India respectively. However, he observed CAGR of 2.46 per cent in production of sugar in India. Veeranagouda et al. (2011) studied the growth rate scenario of chilli in Northern Karnataka. The study revealed that Northern Karnataka as a whole registered positive compound growth rate for area (13.76%), production (13.88%) and productivity (12.20%). These registered values were nonsignificant at both ten and five per cent level of significance. Trivedi (2012) analyzed the growth and trends in area, production and productivity of mango in India. She reported that the area under mango cultivation was increasing in all the states over the period of time except Bihar and Kerala. Annual increase in mango production was highest in Uttar Pradesh with a yearly increment of MT. In the long run, on all India basis, country experienced an yearly increment of MT in mango production and this increment was fairly explained by the time variable (R 2 value 0.79) during the study period. Over the years, productivity of mango was noticed to increase only in the states of Karnataka, Uttar Pradesh and Kerala. In rest all the states, mango productivity was declining over the years. The outcome of this decline was that productivity of mango crop in India as a whole came down by 0.14 MT every year. Prem et al (2012) investigated the performance of vegetable crops in different agro-climatic zones of Rajasthan with specific objective of studying growth in area, production and productivity of vegetable crops. Compound growth rates were used to estimate growth rates for the period from to The growth rates estimated indicated that there was much variability in the productivity of vegetable crops as compared to growth in area, under vegetable crops. peas, cabbage, onion, bottle gourd, bitter gourd, ridge gourd and tinda were some of the important crops which showed good performance in the state. Zone III B performed best in vegetable products. Subrahmanyam and Nagasree (2012) analysed the trends in growth of area, production and yield of pulses in India. They indicated that there was a slight increase in the compound growth rate in area under total pulses which, from negative growth rate of 0.09 per cent per annum during to , had increased to 1.17 per cent during to whereas the production growth rate increased to 2.61 per cent per annum during the period to as compared to 1.52 per cent during the period to The yield growth rate had increased marginally to 1.64 per cent from 1.61 per cent per annum during the same period. Because of the low growth rates as compared to population growth, the per capita production had decreased resulting in abnormal increase of prices forcing government to import pulses from other countries. 2.2 Studies related to the coefficient of variation, contango and backwardation analysis Sharma and Kumar (2001) studied the price behaviour of the selected agricultural commodities viz., wheat, rice, groundnut seed and groundnut oil. In their study on variations in Monthly (Nominal) Price Index of wheat, rice, groundnut seed and groundnut oil, they found the highest coefficient of variation in monthly (Nominal) price index in case of groundnut seed (23.2%), followed by groundnut oil (7.7%), wheat (6.4%) and rice (4.3%). Worthington and Higgs (2004) examined the relationship between futures and spot electricity prices for two of the Australian electricity regions in the National Electricity Market (NEM): namely, New South Wales and Victoria for the period 1999 to During peak periods the coefficient of variation of spot and futures prices of New South Wales were and and that of Victoria were and respectively. But during the off-peak periods the coefficient of variation of spot and futures prices of New South Wales were and and that of Victoria were and respectively. Dash and Andrews (2010) studied market behaviour and price discovery in Indian commodity markets by using contango and backwardation. The sample used for the study was a sample consisting of twenty-one commodities which were actively traded on NCDEX in the study period of January 2005 to April They found that the commodities that showed contango to a marked

15 extent, with average spot prices significantly lower than average futures prices, were as follows: guar seeds (99.63%), castor seeds (96.21%), cotton (94.87%), cashew (87.18%), groundnut oil (82.76%), arabica coffee (82.39%), masoor (81.15%), silver (79.56%), mustard seeds (74.36%), maize (71.89%) and aluminium ingot (69.01%). In fact, potato and sesame seeds were also found to show contango to a marked extent (67.57 per cent and per cent, respectively), but the difference in their average spot prices and their average futures prices was not statistically significant. On the other hand, it was found that the commodities that showed significant backwardation, with average futures prices significantly lower than average spot prices, were as follows: wheat (87.22%), gur (69.71%), barley (69.31%) and mentha oil (66.08%). In fact, groundnut (in shell) was also found to show backwardation to a marked extent (65.93%), but the difference in average futures prices and average spot prices was not statistically significant. Also, chilli and gold were found to show backwardation to a moderate extent only (48.82 per cent and per cent, respectively), though their average futures prices were significantly lower than their average spot prices. Finally, it was found that one commodity, viz. jeera, showed mixed tendencies of contango and backwardation, with no significant difference in average spot prices and average futures prices. Ajjan et al. (2011) studied the price movement of turmeric in Tamil Nadu. They found that a five year price cycle with regard to turmeric prices in India and Tamil Nadu. This cyclical price behaviour was the causal agent for changes in area under turmeric i.e., when the price are slump in current year, area under turmeric will be less in succeeding year. This supply side reduction causes prices in upward direction and next year more area under turmeric leads to downward pressure on price. The crop prices in the cash and futures markets are usually lowest near harvest due to supply pressure. Conversely, they are usually the highest near the end of the marketing year when supplies are less abundant. Shakila et al. (2012) studied price behaviour of major cereal crops in Bangladesh. They selected boro paddy and wheat according to their ascendancy in agriculture in terms of production and area coverage. They found that the coefficient of variation of boro paddy were 12.69, 11.34, 7.46 and 10.07, and wheat were 8.49, 7.55, 2.28 and 5.63 for the periods to , to , to and overall period to respectively. Coefficient of variation was higher for boro paddy than wheat. Chhajed and Mehta (2013) studied the market behaviour in Indian agricultural commodity market with the help of backwardation and contango for the period from 1 st April 2009 to 31 st March In terms of market behaviour, it was found that the commodities that showed contango to a marked extent, with average spot prices significantly lower than average futures prices, were chana (58.33%), rubber (91.67%), soybean oil (58.33%), but the difference in their average spot prices and their average futures prices was not statistically significant. On the other hand, the commodities that showed significant backwardation, with average futures prices significantly lower than average spot prices, were Jute (58.33%), mentha oil (91.67%). It was found that some commodities, viz., crude palm oil, wheat, potato and cardamom showed mixed tendencies of contango and backwardation, with no significant difference in average spot prices and average futures prices. 2.3 Studies related to the correlation analysis Behura and Pradhan (1998) used bivariate price series correlation and Engle-Granger test to analyze the market integration in the marine fish markets in Orissa. The bivariate correlation coefficient for six selected market pairs ranged between 0.60 and The cointegration test statistic revealed that all the pair wise markets were found to be less than the asymptotic critical value even at 10 per cent level. Therefore the marine fish markets in Orissa were found to be not integrated which was attributed to poor infrastructural facilities at landing centers as well as at the terminal secondary markets. Thus poor market integration observed in Orissa revealed that marine fish markets were quite uncompetitive which necessitated strong and extensive government intervention to enhance market efficiency. Balappa and Hugar (2000) have made an attempt to examine the extent of price integration of onion and potato in the selected markets of North Karnataka, comprising Belgaum, Bijapur, Dharwad, Gulbarga, Raichur and Hubli markets. Zero order correlation and coefficient of variation techniques were used. The correlation matrix of prices of different markets was worked out to know their integration. The zero order correlation matrix between average wholesale price of onion clearly indicated the integration among the selected markets, except Bijapur with other markets. However, the magnitude of integration was found to be higher between Belgaum and Raichur (0.9447), between