Indian Commodity Futures Market - IPASJ

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Keyword: Commodity Futures, Contango, Normal Backwardation, Keynes Assumptions. Introduction: The commodity segment is more volatile with respect to ...
IPASJ International Journal of Management (IIJM) Web Site: http://www.ipasj.org/IIJM/IIJM.htm Email:[email protected] ISSN 2321-645X

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Volume 5, Issue 5, May 2017

Indian Commodity Futures Market: The convergence of future and spot price with the effect of Contango and Normal Backwardation B. S. ROUT1, Dr. K. Chandrasekhara Rao2 1

Research Scholar, Dept. of Banking Technology Pondicherry University, Puducherry -605014 2

Professor, Dept. of Banking Technology, Pondicherry University, Puducherry -605014

Abstract Indian commodity market has wider experience on price risk management through various derivative products. But in the same time we have unseen the relish of “Risk Premium”. In this paper we have emerged in exploring the existence and randomness of Contango and Normal Backwardation. We have focused on NCDEX and MCX for our data crunching and analyzed eight commodities including both Agricultural and Metal over six years period i.e. from 2010 to 2015. As we know, the “Near Month” contract are more volatile and sensitive as it is performs its activity on maturity month, so we have crunched “Near Month” contract for both Spot Price and Future expected Spot Price for our analysis. As a result, we are able to make out the existence of Contango and Normal Backwardation in both Agricultural and Metal segment, and seen the metal has more randomness than agricultural commodity. The metal segment have a Contango pattern and hence showing a Normal market condition over six years period, whereas except Soya bean, other four commodities i.e. Channa, Chilli, Jeera, Turmeric has a Backwardation pattern and hence treated as Abnormal Market Condition over six years’ time horizon.

Keyword: Commodity Futures, Contango, Normal Backwardation, Keynes Assumptions. Introduction: The commodity segment is more volatile with respect to Speculative and hedging activities. We normally assumes that, the Spot Price and Future Price are merged on the expire of the contract. Even if we closely focus the Near Month Contract, we can observe the unexpected price fluctuation due to economic demand and supply. Though convergence is expected and often happened in the Derivative segment, so we have to understand the complete micro structure of the each contract. The leading and lagging of Spot Price over Future Price often played hide and sick throughout the contract. So the loitering spillover of Spot Price versus Future Price gives birth of “Contango” and “Normal Backwardation”. There are seemingly two opposite theories proposed to explain the returns to speculative traders and significant price volatility in the futures market. One is the theory “Normal Backwardation” or “Contago” in opposite, which views speculative returns as directly linked to the bearing of risk. The other is called “Forecasting Theory “which considers returns to be determined by the ability of traders (in case of speculator) to forecast the price accurately. Although the above stated arguments are not mutually exclusive but they may be complement to each other. In this study, we want the present evidence on the extent to which each of these competing explanations may be operative in futures markets. (Jong W. Lee 2005) Why Contango Happened? Contango is a situation where the Future expected Spot Price is higher than the Current Spot Price. Sometime, Contango is called as “Normal Contango” as it is Normal for the market prospective. A farmer always wish to hedge his Price Risk, for such, he puts his leg in Derivative segment and merge in three months contract, where the Price, Quantity and Delivery date is fixed. If we clearly understand the chemistry behind Contango, then we have to proceed

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Volume 5, Issue 5, May 2017

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with Demand and Supply theory. The products which have less demand or which have ample amount of competitor, normally face a Price Risk i.e. the exact price which is fixed before auction does not enable the farmer to sell on the pre-determined price his product and a distress sell is observed in the spot market segment. This is the biggest reason, why farmers or producer prefer Derivative segment, where he can get a better price for his product. Why Backwardation Happened? “Backwardation” is otherwise called as “Normal Backwardation”. Normally this situation is widely seen in Commodity Derivative segment. If we look at the Security Trading segment, we do not find such type of situation. In Normal Backwardation the Spot Price is higher than the Future expected Spot Price. The farmer or hedger always wishes to mitigate the corresponding Price Risk by selling the product in Cash Market. If the product is sellable with better cash price, it is worth to sell it up in Spot Market. Here farmer performs both as hedger and speculator, where he could not only hedge his Price Risk but he also speculates the future price in compare to current price. Keynes’s Hypothesis: The theory of Speculation was explained by Keynes in 1948. He was also put an effort to explore the reason for Normal Backwardation. Backwardation is normally observed when Commodity is in Short supply. It gives an idea about “Seasonal” and “Off Seasonal” Product”. If a farmer going for a off-seasonal product he definitely finds a sustainable market for his product, where he can sell in a better price. Such market is much volatile and prefers Spot Cash Transaction. So in order to mitigate his price risk, farmer will approach the buyer for a Spot Cash Transaction rather a Future expected Spot Price. Such situation, expects a Backwardation as the Current Spot Price is higher than the Future Expected Spot Price. Cost of Carry: In a derivative market, Future Prices are normally higher for distant delivery period. Such highness is due to a combination of Storage Cost and an Opportunity Cost (i.e. net interest), incurred by the holder of underlying commodity and it is termed as Cost of Carry. If futures prices are accurately described by a full cost of carry relationship, the cost of carry is the difference between Futures Price and Spot Price on a given date. This scenario is consistent with Contango Market (Bodie, et al., 2003; Chance, 2004) If an underlying has obtained a negative cost of carry, the net interest is a net inflow, hence it will go above the cost of storage. With a positive cost of carry, futures prices are below for more distant delivery period. This scenario is consistent with Backwardation market (Bodie, et al., 2003; Chance, 2004). In Backwardation, normally the Spot Prices are higher than the Futures Price. The foremost reason would be the shortage of commodity supply in the market. The rare availability of the product gives free hand to the holder of the underlying to sell immediately for a better price. In such situation, many individuals take the advantages of shortsupply and tries to store it for a premium or abnormal profit in Future Date. Such premium is nothing but “Convenience Yield” (Jeong W Lee and Nancy; 2005) Risk Premium and Backwardation: The producer always finds a Price Risk involvement in his produced crop. It is only because of market demand and competitor present for selling the equivalent product. The producer who harvests an off-seasonal product has both the probability of gaining and losing the concerned product. If the crop is not get proper care from both irrigation and pesticides, there is a much chance of losing the crop at instant. On the other side, if the entire non-economic situation holds good, there is a huge chance for premium as an advantages for taking risk. When the product arrives at market, normally less competitors performs their job as very few of farmers are risk taker who involves their potential in harvesting off-seasonal product. If we look at the demand and supply aspect, the demand for off-seasonal product is quite higher than seasonal product, whereas supply is very less. So the market demand not only mitigates the price risk but at the same time gives an extraordinary premium for the challenge of growing offseasonal product. Market Micro-structure: The commodity market is much un-organized than security market as there are ample amount of chances of leakage of market information. Normally the spot market is regulated by various “Shadownomist”. Sometime the Efficient Market Hypothesis (EMH) does not work out properly due to involvement of such “Shadownomist”. This is the biggest reason behind the Normal Backwardation. “Shadownomist” forces producers to prioritize Spot Market rather Derivative Market. It not only hampers the price trend, but it also destroys the efforts of producer’s interest. *Shadownomics is a kind of black economy, where Cartel Risk is seen, and producers are not allowed to sell their product in derivative segment. The players are called “Shadownomist”

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Volume 5, Issue 5, May 2017

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Literature Scan: JeongW. Lee and Nancy Beneda (2005), the authors investigate on “Future Markets: Speculator Participation and Risk Premium”. The study aims at to explore whether changes in Futures Price are determined by the shifting of price risk and the presence of risk premiums in the transaction between Hedgers and Speculators. The author explained the two theories i.e. “Theory of Normal Backwardation” and “Forecasting Theory”, which gives return to speculative traders and significant price volatility in futures marker, he also pointed out the Theory of Convenience yield, and how speculators will benefit, when product is in short supply. Gary Garton and GeetRonnembor (2006) have conducted a study entitled “Facts and Fantasies about Commodity Futures”. The Study observes that commodity futures have historically offered the same return and Sharpe – ratio as equities. While risk premium on commodity futures is essentially same as equities, the study on commodity Futures with a sample of 32 commodities traded in London Metal Exchange during 1959 – 2004 observes that the returns of commodity markets are negatively correlated with equity returns and bond returns. The negative correlation between commodity futures and other asset classes in commodity futures are truly correlated with inflation and unexpected inflation, changes in expected inflation. Pratap Kumar (2016) has conducted a study entitled “Financialisation of Commodity Market in India: A closer look at the evidence”. The impact of financialisation of price risk and price volatility of Indian commodities market has been studied by using time series techniques. The commodity price index is related to stock index price and causality test indicated that commodity prices are Granger causes the stock prices in India. Suchismita Bose (2008) has explored a study on “Commodity futures market in India: Study of trends in the National Multi Commodity Indices. The characteristics of Indian commodity futures market has been studied through price efficiency functioning of market. The result based on Multi Commodity Indices shown at higher exposure to material and energy product with clear and efficient price dissemination in national and International Market. She has expected the nature of Contango and Normal Backwardation in her observation. The suggestion made on the base of trend of Spot and Future Index for 2005-2007. J. K. Das and GaurabChakroborty (2015), the author studied on “Hedging performances of Commodity Futures in India: An empirical Study on Some Agri Commodities”. This paper aims to measure optimal hedging ratio and hedging effectiveness for reducing the price risk. A positive base implies that, a Future Price lag behind or backward to Spot Price (Future Market is in Backwardation, whereas aa negative basis is termed as Contango). Potato price shows a mixed Pattern, with a greater incidence of Contango and Backwardation. Vijay Kumar Varadi (2012), the author explores in the topic of “An Evidence of Speculation in Indian Commodity Market”. He explains the price volatility is influenced by several factors like traditional supply and demand, excess global liquidity and financialization attitude of speculators and investors. The study has attempt to find the impact of the above said factors in Indian Commodity Futures Market. The result shows that, speculation played an important role in price volatility especially in the global crisis. He has pointed out how the the Theory of Normal Backwardation helpful in such regards. Data collected from FMC fortnightly from 2006-2010. Luca Fantacci et.al. (2010), the author makes an attempt to study on “Speculation in Commodities, Keynes practical acquaintance with future market”. Information like un-published letter, broker’s statement and speculation theory of Keynes have been used to analyze the speculative behavior in wheat future market, the observation shows that, Normal Backwardation applied only to well specified circumstances. It also observes that, Keynes actual behavior as a speculator is different from the theory suggested by him (Speculative Theory). Objective of the Study: The primary objective of our study is to explore the Existence of Contango and Normal Backwardation in the Commodity Derivative segment. In another insight, we aim tofind out the randomness of “Contango” and “Normal Backwardation” in the Indian Commodity Futures Market. Data Crunching: We have focused to identify the randomness as well as the existence of Contango and Normal Backwardation. We have undergone secondary data sources for our analysis. We prefer MCX (Multi Commodity Exchange Ltd.) and NCDEX

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(National Commodity and Derivative Exchange). We have focused both Agricultural and Metal Commodities for analysis. We have taken five agri commodities i.eChanna, Chili, Jeera, Soya bean, and Turmeric and three metal commodities i.e. Aluminum, Zinc and Lead. We have limited up to “Near Month” contract as “Near Month´ has a larger potential of price fluctuation in compare to “Far Month” and “Mid-month”. The price fluctuation motivates “Contango” and “Normal Backwardation” situation. The data period of our study is from 2010 to 2015. The “Spot Price” and “Future Price” are the basic component for analysis. So we have arranged Future Price and Future Price for six years’ time period. Methodology: Test of Randomness: The test of randomness is very much important to understand the wavering movement of values. In order to capture such wavering movements, we tried “Runs Test”. A run is a defined as a series of Decreasing Series or Increasing Series. The length is determined by the number of runs in that series. In a random data series, the probabilistic occurrence that the (I+1) th value is smaller or larger than I th value follows a Binomial Distribution, which is the basis of Runs Test.

Z

RR .......................................1 SR

R = Observed no. of Runs

R = Expected no. of Runs SR = Standard Deviation of runs. 2n1n2  1.................................(2) n1  n2 2n1n 2(2nin2  ni  n2) SR  ............(3) (n1  n2)2(n1  n 2  1) R

n1 and n2 = the positive and negative number in the series. We have collected near month contract cycles for the select commodities of our study. We have analyzed Spread (Spot Price – Future Price) to explore the Existence of Contango and Backwardation. The negative Spread gives Contango whereas Backwardation for Positive Spread. Interpretation of Result: Commodity Total Runs Test Value Significance 197 0.58 000 Channa 061 0.71 000 Chilli 164 0.81 000 Jeera 224 0.43 000 Soya bean 125 0.51 000 Turmeric 463 0.21 000 Aluminum Zinc Lead

568 657

0.26 0.31

000 000

(Table: 0.1) The above table gives an idea about the randomness of data series. We have taken both Agri and Metal commodities for our research point of view. Though all commodities are rejecting null hypothesis, it proves that, the commodities are not having randomness with respect to Contango and Normal Backwardation. Another biggest reason for non-randomness is “Contract Cycle”, as we have taken only “Near Month Contract”, so the repetition of “Contango” and “Normal Backwardation” are more and it is clearly observe by seeing the total number of runs happened in that particular commodity in the concerned maturity month. If we observe the above table, we can understand in Metal commodity the repetition of “Contango” and “Normal backwardation” are more than agricultural commodity. It shows the amount of “Market Efficiency”. Again, the existence of Contango and Normal Backwardation is clearly seen in (Table: 0.2). The commodities like Channa, Chili,Jeera and Turmeric shows an abnormal pattern in the market, where as Soya bean gives a Normal pattern in the agricultural commodity segment, that signifies, except Soya bean, other four commodities have Backwardation pattern in last six years. If we look at the Metals segment, all the three metals (Aluminum, Lead, Zinc) shows a Normal pattern in the market that signifies Contango dominates the Metal segment drastically.

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If we closely observe at total number of runs, we could understand the metal have more runs than agriculture commodities. it is the reason for Normal Market condition or Contango Pattern over the six years’ time horizon. The yearly pattern of Contango and Normal Backwardation utters a different story (Table: 0.3), in 2010, except Jeera rest of the Commodities (Including Agri and Metal) shows a Backwardation. The trend somehow reverses in other consecutive years. The metal segment shows a continuous Contango pattern in the remaining five year and Jeera shows a Contango Pattern. In the year 2015, all the agricultural commodities show a Backwardation Pattern except the Metal products. Conclusion: The study provides a drastic result on existence, pattern and randomness of Contango and Normal Backwardation in Indian commodity derivative market over the six years’ time span. We explore the randomness and pattern for both the agricultural and metal segment. As a result, we are able to make out the existence of Contango and Normal Backwardation in both Agricultural and Metal segment, and seen the metal has more randomness than agricultural commodity. The metal segment have a Contango pattern and hence showing a Normal market condition over six years period, whereas except Soya bean, other four commodities i.e. Channa, Chilli, Jeera, Turmeric has a Backwardation pattern and hence treated as Abnormal Market Condition over six years’ time horizon. if we again make in a closer insight, we could understand, the amount of fluctuation of price moments of Metal than Agri products. The higher amount of runs or randomness gives a constant Contango pattern in the Metal segment and makes the market Normal over the six years. Whereas, less amount of randomness, gives a fluctuate pattern to agricultural commodities. Another biggest reason for Backwardation in agricultural commodity is due to “Shadownomy”, the cartel does not allowed a free hand to the farmer for entering into a derivative contract. The cartel forced the farmer for distress sell of his product. So in such a situation expecting commodity market more effective in terms of price risk management is quite tough, but the pattern of Contango and Normal Backwardation gives a good signal for speculator to realize Risk Premium by technically involving in risky decisions. Annexure: Contango Vs. Backwardation Contango Commodity (%) 20.04 Jeera 41.94 Chana 57.29 Soya Been 49.14 Turmeric 30.49 Chilli 79.14 Aluminum 69.26 Lead 73.79 Zinc (Table: 0.2) Con-Back Pattern Commodity 2010 Jeera C Chana B Soya Been B Turmeric B Chilli B Aluminum B Lead B Zinc B C = Contango, B = Backwardation

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Backwardation (%) 79.96 58.06 42.71 50.86 69.51 20.86 30.74 26.21

2011 B C C B B C C C (Table: 0.3)

2012 B B C C B C C C

Market Condition Abnormal Abnormal Normal Abnormal Abnormal Normal Normal Normal

2013 B B B B C C C C

2014 B B B C C C C C

2015 B B B B B C C C

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Volume 5, Issue 5, May 2017

Contango

Backwardatio

Contango

Backwardatio

Contango

Backwardatio

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Contango

Backwardatio

Contango

Backwardatio

Contango

Backwardatio

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Contango

Backwardatio

Contango

Backwardatio References: • Gorton, Gary, and K. Geert Rouwenhorst. (2006), “Facts and Fantasies about Commodity Futures.” Financial Analysts Journal 62(2): 47–68. • JeongW. Lee and Nancy Beneda (2005), ““Future Markets: Speculator Participation and Risk Premium”, Management Research News, vol-28, iss-6, pp 1-17 • Pratap Kumar Jena2016 "FinancializationOf Commodity Market In India: A Closer Look At The Evidence”The Romanian Economic Journal, Pg. 147-167. • Prof. (Dr.) J. K. Das, Gourab Chakraborty2015 " The Hedging Performance Of Commodity Futures In India: An Empirical Study On Some Agricultural Commodities”International Journal Of Information, Business And Management. • Vijay Kumar Varadi2012 " An Evidence Of Speculation In Indian Commodity Markets “MPRA Journal. • Luca Fantacci, Maria Cristina Marcuzzo, and EleonoraSanfilippo. (2010), “Speculation in Commodities: Keynes’ ‘Practical Acquaintance’ With Futures Markets.” Journal of the History of Economic Thought 32(03): 397–418. • Maravi, Angad Singh. (2015), “Performance Analysis of Indian Agricultural Commodity Market.” International Journal of Commerce, Business and Management (IJCBM) 4(2): 1125–35. • Kaur, Harwinder P A L, and BimalAnjum (2013), “Agricultural Commodity Futures In India- A Literature Review.” Galaxy International Interdisciplinary Research Journal 1(1): 35–43. • Narinder, Archana Singh and (2015), “Testing Seasonality and Efficiency in Chana Futures Market.” Apeejay Business Review 14(2). • Singh, Archana (2014), “Commodity Futures Market Efficiency and Related Issues : A Review of Existing Literature.” Asian Journal of Business and Economics 4(4): 1–21.

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• Sehrawat and Sandeep (2015), “Impact Of Futures Contract On Agricultural Commodity Prices: An Indian Perspective.” International Journal Of Development Research 05(03): 3740–44. • Sendhil, R, AmitKar, V C Mathur, and Girish K Jha (2013), “Price Discovery , Transmission and Volatility : Evidence from Agricultural Commodity Futures.” Agricultural Economics Research Review 26(1): 41–54. • Shakeel, Moonis, and ShriramPurankar (2014), “Price Discovery Mechanism of Spot and Futures Market in India : A Case of Selected Agri-Commodities.” international research journal of business and managementVII(8): 50–61. • Takatsuki and Yasuo (2008), “The Formation of an Efficient Market in Tokugawa Japan.” ISS discussion paper series F-143. • Tobergte, David R., and Shirley Curtis (2013), “Price Discovery Process and Volatility Spillover of Chilli Spot and Futures Prices Evidence from National Commodity and Derivative Exchange Ltd (NCDEX).” International Journal of Engineering and Management Research (IJEMR) 3(12): 1–23. • Tripathy and Trilochan (2008), “Volatility and Price Integration in Primary Commodities Market : A Strategic Direction in India.” The Icfai Journal of Business Strategy, (Vol. V, No. 1, 2008): 7–21.

Author (s): B.S. ROUT is presently working as a Research Scholar at Department of Banking Technology, Pondicherry University. He has two Master’s degrees, i.e. M.Com (Business Finance) and MBA (HRM) and also certified from Bloomberg for BMC, Equity Essentials, Commodity Essential, Fixed Income Essential and Fx. Essential. He is specialized in Financial Economics, Risk Management, Derivative Management, Portfolio Management, Macro Economics, Econometrics, and Human Resource Management.

Dr. K. Chandrasekhara Rao is presently working as a Professor at Department of Banking Technology, Pondicherry University. He has a wider attribution towards Research Fraternity since thirty two years. He has a specialization on Financial Management, Security Analysis & Portfolio management, Global Financial Markets & International Banking.

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