order to compare the structure of the two markets, the futures contract written on the ISE .. This thesis on lead-lag relationship between spot and derivatives markets .. () deal with information linkage between Greek. lead–lag relationship between spot and futures markets do not last for (i.e. whether futures discover spot prices) using data from Greece. The. abstract = "This paper examines the lead-lag relationship between futures and spot markets in Greece. For both available stock index futures contracts.
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Furermore Cn 99 rgue led-lg relon ymmerc. He ugge under good new c ndex prce lg uure prce nd more mporn wen ock re movng ogeer c nd uure mrke provde uppor o e ymmerc led-lg relon. In ddon Cng e l. Alo Pzz e l. The base data of spot and futures prices was converted into continuous daily return series by taking natural logarithm. Natural logarithm of daily prices was taken to minimize the heteroscedasticity in data Sehgal et.
However the base data of spot and futures prices was also used at appropriate stages of the analysis. The data was analyzed using MS Excel and Eviews-9 econometric software package. The lead-lag relationship between futures and spot prices of the sample agricultural commodity derivatives is examined using the following econometric tools: This is done to make sure that the data is integrated at first difference [I 1 ] and hence does not exhibit unit root property Kumar and Shollapur, In practice many financial variables contain unit root and are thus said to be integrated at first difference [I 1 ].
Vector Error Correction Model VECM Once the long-term equilibrium relationship is established through co integration, it is necessary to understand the long run price discovery role and short term price dynamics Kumar and Shollapur, If the price series are not stationary, then the Vector Auto Regression VAR framework needs to be modified to allow consistent estimation of the relationships among them.
Granger states that if two variables are [I 1 ] and co integrated, there must be causality in at least one direction. Bidirectional causality is also possible. This is due to the error correction mechanism between the two series that keeps bringing them back to equilibrium at regular intervals Kumar and Shollapur, Besides, GhoshLien www. Mahendran and Luo and Lien argued that if the two price series are found to be cointegrated, then there exist valid error correction representations of the price series that includes short-term dynamics and long run information Srinivasan, Hence, the causality between futures and spot returns is estimated by using the following VECM: Error correction term, f,i and s,i: Short term coefficients, s,i and f,i: Short term coefficients, ft and st: The short term coefficients f,i, s,i, s,i and f,i represent the short run influence of the returns of one market on the returns of the other.
After estimating Equations 1 and 2Wald F-test is conducted on the coefficients to check whether they are jointly significant. Granger Causality Test After the pre-requisite testing of the stationarity is done, the widely accepted Granger Causality test is deployed to detect the direction of relationship or causation between two variables Granger, If the time series are cointegrated, then the aforesaid VECM can be used to determine the short run deviation from the long run equilibrium, otherwise Granger Causality can be employed to navigate the direction of causation Brahmasrene and Jiranyakul, This test is considered to be a very strong test against unit roots and is a classic choice in econometric literature whenever two series are of the order [I 0 ] Foresti, Intercepts, ai and bj: Coefficients on the lagged F and S values respectively, ci and dj: Coefficients on the lagged S and F values respectively, i and j: Similarly in the reverse case futures return F Granger causes spot return S.
The futures and spot price series were tested for the presence of unit root at the base level as well as at the first difference level. It could be observed from the estimated results that both futures and spot price series in case of refined soya oil, chana, and soya bean and castor seed were exhibiting the presence of unit root when tested using their level data.
The same estimation procedure was conducted for both the price series at their first difference and it could be observed that there was no unit root in the data. Therefore the price series at first difference was found to be stationary in both the futures and spot markets for refined soya oil, chana, and soya bean and castor seed.
However the case was not the same in case of futures and spot price series of guar seed as they were found to be stationary when tested using their level data itself. The detailed results of the ADF test are presented in the Annexure 1. The test was conducted for the existence of number of hypothesized cointegrating equations. It could be inferred that the futures and spot price series for refined soya oil, chana, soya bean and castor seed were cointegrated and exhibiting a long run equilibrium relationship.
The presence of cointegrating relationship also confirmed that there was a causal relationship between the futures and spot price series, at least in one direction. The coefficients of VECM were estimated in case of panel 1 wherein futures return was taken as dependent variable and spot return as explanatory variable.
Similarly in case of panel 2, spot return was taken as dependent variable and futures return as explanatory variable. Mahendran in case of all the aforesaid commodities. This suggested a long term bidirectional causality in futures and spot return series of all these commodities which meant that whenever these cointegrated series were to be in disequilibrium in the short run, both the futures and spot return series would adjust in order to re-establish the equilibrium.
However, the error correction term in the spot return equation was found to be greater in magnitude than that of futures return equation in case of refined soya oil and chana. In other words, futures return was leading the spot return in case of price discovery in the long run. On the other hand, spot return was leading the futures return in case of price discovery in the long run in case of soya bean and castor seed. The short run causality was captured by the short term coefficients s1, s2, f1 and f2.
Here the spot returns with 2 lags were seen influencing the futures return which could be observed from the statistical significance of spot return on futures return both at one and two lags in case of refined soya oil, chana and soya bean.
Similarly futures return with 2 lags was seen influencing the spot return which could be observed from the statistical significance of futures return on spot return at both one and two lags in case of the aforesaid commodities. Further the joint significance of all the short term coefficients was tested using Wald F test. The presence of bi-directional causality in the short run was confirmed by the statistical significance of the Wald F statistic in both panel 1 and panel 2 respectively.
Therefore there existed a bi- directional lead-lag relationship between the futures and spot returns of refined soya oil, chana and soya bean in the short run.
However in case of castor seed the spot returns with 2 lags were seen influencing the futures return which could be observed from the statistical significance of spot return on futures return both at one and two lags.
On the contrary, there was no short term causality flowing from futures to spot as there was no statistical significance found both at one and two lags.
Lead-Lag Relationship between Futures and Spot Markets in Greece: - PDF
Further the unidirectional causality from spot to futures was confirmed by the statistical significance of the Wald F statistic in panel 1 and hence it could be inferred that in short term spot return of castor seed was leading the futures return. Granger Causality Test As there was no long run equilibrium relationship between the two price series in case of guar seed, the futures and spot return series were tested for the presence of short term causality using Granger Causality test and the results are presented in the Table 6.
Spot return does not granger-cause futures return and futures return does not granger-cause spot return were the formulated null hypothesis. At lag 2, the null hypothesis of futures return does not granger-cause spot return was rejected at 5 per cent level of significance and the alternative hypothesis being futures return granger-cause spot return was accepted.
Hence there was a short term unidirectional causality flowing from futures market to spot market of guar seed and therefore it could be inferred that futures return was leading the spot return in the short run. The results of the lead-lag relationship obtained from all the sample agricultural commodity derivatives explained the role of futures market as well as spot markets in price discovery mechanism.
These results were similar to the findings of the study conducted by Vasantha and MallikarjunappaKumar and Shollapur These results were similar to the findings of the study conducted by Srinivasan and Prasanna Overall futures market in case of refined soya oil, guar seed and chana was successful in achieving its intended primary objective of price discovery.
But in case of soya bean and castor seed spot market was found to be leading the futures market and the reasons were obvious that there were comparatively less number of market participants which was reflected in the trading volume as well as value over the years and also the lack of awareness among the participants about the futures market. These findings could help the market participants dealing in the agricultural commodity derivatives farmers, traders etc.
In case of refined soya, guar seed and chana futures market price could be considered as a base price by the hedgers and similarly spot market price could be used in case of soya bean and castor seed. Futures Return Panel 2: Standard Error Table 6: MacKinnon-Haug-Michelis p-values www. The commodity derivatives viz. Hence the price discovery mechanism between the futures and spot prices will be keenly observed by the participants who would like to hedge their spot price risk using the futures contracts of these agricultural commodities.
In case of refined soya oil and chana, futures market was found to be leading the spot market in long run.
Lead-Lag Relationship between Futures and Spot Markets in Greece:
On the other hand, the long-run causality has been flowing from spot market to futures market in case of soya bean and castor seed. The existence of a bidirectional lead-lag relationship in the short run was confirmed in case of refined soya oil, chana and soya bean. Castor seed encountered unidirectional causality from spot to futures and hence spot market of castor seed was leading the futures market in the short run.
Similarly guar seed also encountered unidirectional causality, but here futures market was found to be leading the spot market in the short run.
Apart from helping the hedgers dealing in the futures contracts of select agricultural commodity derivatives, the results of this study also provides vital inputs to policy makers as well as to the futures market regulator SEBI. As the price discovery mechanism becomes more efficient, the hedgers dealing in agricultural commodities will start to reap more benefits and hence this has the potential to attract more farmers towards futures trading.
This combo of risk reduction and assured profit will be an alluring factor which could bring the farming community and futures market on a single platform. Even though the commodity futures market in India have been performing well off late in the process of price discovery, but still there is a lot of scope to improve in terms of their efficiency which can be done by keeping the speculators in check.
Neeraj Mahajan and Kavaljit Singh Price Discovery in Indian Commodity Market: A Study of Red Chilli Futures. Christos Floros and Dimitrios V. International Research Journal of Finance and Economics, 7 Hedging with Stock Index Futures: Estimation and Forecasting with Error Correction Model.