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An Enquiry into Efficiency of Futures Trading in Agricultural Commodities in India

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

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An Enquiry into Efficiency of Futures Trading in Agricultural Commodities in India

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  1. An Enquiry into Efficiency of Futures Trading in Agricultural Commodities in India Ashwini Kumar, IES Ministry of Agriculture

  2. Economics of Futures Trading • Objectives • Price discovery • Hedge against risk • Trade facilitation • Heterogeneity of firms’ behaviour • Zero-sum nature • Representative individual?

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  8. Efficiency of Futures Markets • Efficient market => • Market prices reflect all informations • Nobody can earn excess profits in a systematic manner. • Random walk.

  9. 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.

  10. 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 Descriptive Statistics

  11. Econometric tests • Tests for stationarity • Augmented Dickey Fuller (ADF) Test • Philips-Peron (PP) Test • Johansen’s Cointegration Test • Granger Causality Test • Impulse Response Function

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Thank You

  18. Variables Critical Values ADF Statistic PP Statistic FUTEXAGRI ADF PP Level Form -1.28 -1.31 1% -4.28 -4.27 Level form of Log -1.13 -1.81 5% -3.56 -3.55 10% -3.21 -3.21 First Difference form of Log -9.32 -14.12 NCDEXAGRI Level Form -1.47 -1.49 Level form of Log -1.42 -1.44 First Difference form of Log -8.54 -14.49 Unit Root Tests Results

  19. Hypothesized No. of CE(s) Hypothesized No. of CE(s) Eigen value Eigen value Likelihood Ratio Likelihood Ratio 5% Critical Value 5% Critical Value 1% Critical Value 1% Critical Value None** None** 0.223629 0.221714 96.15476 94.00665 12.53 15.41 20.04 16.31 At most 1** At most 1** 0.158306 0.152359 38.94846 37.35732 3.76 3.84 6.51 6.65 Johansen cointegration test result

  20. Null Hypothesis: Obs F-Statistic Probability LN_NCDEX_101 does not Granger Cause LN_FUTEX_101 229 0.12940 0.87869 LN_FUTEX_101 does not Granger Cause LN_NCDEX_101 1.66731 0.19109 Granger Causality Test result

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