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Transcript

An Enquiry into Efficiency of Futures Trading in Agricultural Commodities in India Ashwini Kumar, IES Ministry of Agriculture Economics of Futures Trading Objectives Price discovery Hedge against risk Trade facilitation Heterogeneity of firms’ behaviour Zero-sum nature Representative individual? Perspectives Risk Management Perspective Interaction between hedgers ( risk avert) and risk premium earners Transaction cost / Arbitrage Perspective Firms benefit from arbitrage because of their better position in terms of transaction cost. Speculators? Contribute to liquidity and forecasting ability. Commodity Futures Markets in India Indian Agriculture Prominent sector Source of livelihood for majority Susceptible to weather fluctuations Fragmented Agricultural Markets Inequality in distributional benefits Commodity Futures Markets in India Long History Reference in Kautilya’s Arthashastra Several forward markets/ Satta in late 19th-early 20th century Cotton Trade Association, Bombay, 1875 Specialised in trading of a particular commodity/ group of commodities Commodity Futures Markets in India Independent India Forward Contracts (Regulation) Act, 1952 Forward Makets Commission in 1953. 1966- futures trade banned in all major agricultural commodities 1980- Khusro Committee 1993- Kabra Committee Recommended forward trading in 17 commodity groups. Commodity Futures Markets in India National Agricultural Policy, 2000. Envisaged use of futures contracts. Watershed year- 2003 Ban on futures trading of all commodities lifted. 3 new Nation-wide multi-commodity exchanges, MCX, NCDEX & NMCE. Electronic trading. Phenomenal growth in turnover since 2003-04. Efficiency of Futures Markets Efficient market => Market prices reflect all informations Nobody can earn excess profits in a systematic manner. Random walk. Data and Methodology Two indices of NCDEX NCDEXAGRI- index of spot prices FUTEXAGRI- index of futures prices Identical basket of commodities and same base. FUTEXAGRI constructed on prices of the nearest month expiry contract. Data from 01/Jan/2007 to 03/Oct/2007- 232days Opening values of every day. Descriptive Statistics FUTEXAGRI NCDEXAGRI MEAN 1512.593 1513.816 MEDIAN 1489.600 1495.495 MAXIMUM 1651.560 1667.130 MINIMUM 1401.440 1411.980 STD DEV 63.48507 69.40974 SKEWNESS 0.397568 0.446115 KURTOSIS 2.007449 2.088885 Econometric tests Tests for stationarity Augmented Dickey Fuller (ADF) Test Philips-Peron (PP) Test Johansen’s Cointegration Test Granger Causality Test Impulse Response Function Findings Unit Root tests Both indices are not stationary in level form. First Difference of log form, i.e., rates of growth series of these indices are stationary. It implies that while it may not be possible to predict future values, the rate of growth of either of the two series is predictable. Findings Contd.. Johansen Cointegration test Assuming Linear deterministic trend , and Assuming no deterministic trend. There are two cointegrating equations implying that rates of growth of the two indices have long-term relationship. Causality Findings Granger Causality Test results imply No causality in any direction Rate of growth in futures prices do not depend on rate of growth in spot prices and similarly the other way round. Impulse Response Function Results imply that Rate of growth of futures prices get affected by any exogenous shock in rate of growth in spot prices but not vice versa. In case of an exogenous shock to rate of growth in spot prices futures prices take longer to stabilize than the spot prices themselves. Conclusions Futures market not efficient in short run. Change in spot prices are found to affect futures prices. Effect of change in futures prices on spot prices is found to be minimal. Thank You Unit Root Tests Results Variables ADF Statistic PP Statistic Critical Values FUTEXAGRI Level Form -1.28 -1.31 -1.13 -1.81 -9.32 -14.12 Level Form -1.47 -1.49 Level form of Log -1.42 -1.44 Level form of Log First Difference form of Log ADF PP 1% -4.28 -4.27 5% -3.56 -3.55 10% -3.21 -3.21 NCDEXAGRI First Difference form of Log -8.54 -14.49 Johansen cointegration test result Hypothesized No. of CE(s) Eigen value Likelihood Ratio 5% Critical Value 1% Critical Value None** 0.223629 96.15476 15.41 20.04 At most 1** 0.158306 38.94846 3.76 6.65 Eigen value Likelihood Ratio 5% Critical Value 1% Critical Value None** 0.221714 94.00665 12.53 16.31 At most 1** 0.152359 37.35732 3.84 6.51 Hypothesized No. of CE(s) Granger Causality Test result Null Hypothesis: Obs F-Statistic Probability LN_NCDEX_101 does not Granger Cause LN_FUTEX_101 229 0.12940 0.87869 1.66731 0.19109 LN_FUTEX_101 does not Granger Cause LN_NCDEX_101