Transcript Presentation - NCDEX Institute of Commodity Markets and Research

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

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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

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Cotton Trade Association, Bombay, 1875
Specialised in trading of a particular commodity/
group of commodities
Commodity Futures Markets in
India
 Independent India

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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

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
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 =>
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
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Market prices reflect all informations
Nobody can earn excess profits in a systematic
manner.
Random walk.
Data and Methodology
 Two indices of NCDEX



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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

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Augmented Dickey Fuller (ADF) Test
Philips-Peron (PP) Test
 Johansen’s Cointegration Test
 Granger Causality Test
 Impulse Response Function
Findings
 Unit Root tests

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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
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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
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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
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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