This article investigates the potential for portfolio diversification benefits of commodity futures in the Indian context. For this purpose, we have estimated dynamic conditional correlations (DCC) between returns of four commodity futures indices and traditional asset class indices such as stock index, long-term bond index and Treasury bill index, separately for the pre-crisis and crisis period using the DCC–GARCH model and daily data ranging from June 2005 to September 2011. Empirical results reveal that there exist very low dynamic conditional correlations between commodity futures indices returns and traditional asset indices returns, an evidence illustrating the potential for portfolio diversification benefits of commodity futures. Commodity futures become more segmented from the traditional asset market; thus they can be effectively used for strategic asset allocation. Further, the conditional correlation between agriculture commodity future returns with long-run and short-run bond returns declined during the crisis period. Similarly, the conditional correlations of commodity futures indices returns (agriculture, energy and metal) with the stock index declined in periods of high volatility in the equity markets. These two findings indicate that the diversification benefits of commodity futures are most realized when the risks in traditional asset markets rise.

Commodity Futures Indices and Traditional Asset Markets in India: DCC Evidence for Portfolio Diversification Benefits

This study examines the weak form efficiency (random walk model) and the unbiasedness of two commodities futures market in India. While data for spot and futures prices of Aluminum and Copper is collected from the Multi Commodity Exchange of India Ltd. (MCX). The data regarding the volumes of futures traded is also collected from the websites of the respective Exchanges. The study is analysed by using econometric tools. The spot prices are regressed on the near month, middle month and far month futures prices to test the weak form of efficiency and unbiasedness. The effect of speculation on the unexpected movement of spot prices is also examined. Co-integration and Error correction model are applied to know the long run relationship and deviations from such equilibrium. The impulse response model is used to know the impact of shock of futures prices on the spot prices. Cholesky’s Decomposition model is used to understand the forecast variance. Wald test is performed to check the coefficient restrictions. Durbin-Watson test is done to check the random walk theory at the maturity of contracts. The results show that all the commodity futures prices and spot prices are related in the long run hence, errors of short deviations are corrected to maintain the equilibrium. The random walk theory does not hold good as the contract maturity comes closer. The results conclude that two commodities, considered in the study are inefficient. However, the market efficiency cannot be rejected at all the time. Thus, being India a nascent market in commodities derivatives, there is a scope for better price discovery (efficiency and unbiasedness).

Evaluation of efficiency form of the commodities market: an empirical study of the indian scenario

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Hedging effectiveness of rubber market in thailand

This paper attempts to study the growth in agricultural commodity derivatives market and its impact on economic growth in India. Commodity forward market has witnessed radical changes since independence. Government of India formed many committees to review working of forward trading in the country. Prof. A D Shroff Committee was constituted to propose a bill on forward contracts and finally in December 1952 Forward Contracts (Regulation) Act, was enacted. Dantwalla committee was appointed in 1966 to assess the working of co-operative marketing system. The Khusro Committee in June 1980 gave recommendations to reintroduce commodity futures trading in most of the major commodities. In 1994 Prof K N Kabra committee gave recommendations for reopening of futures trading in major commodities. The committee also suggested the pepper and castor seed trading exchanges to upgrade their operations to the level of international futures markets. The impact of growth in agricultural commodity futures on agricultural GDP is test by taking last ten years quarterly data of aggregate traded agricultural commodity futures across major exchanges and economic growth as measured by the sectoral quarterly GDP has been taken for study. The time series stationarity of commodity trade volume and GDP quarterly data has been tested using Augmented Dickey Fuller (ADF) and Phillip Perron (PP) tests and confirmed that the data is stationary. Linear regression results confirm significant influence of agricultural commodity futures trading on agricultural GDP in India. Keywords: Forward market, Economic growth, Committees, stationarity test, linear regression JEL category: G23, G21

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Causal Nexus between Commodity Derivatives Market Reforms and Economic Growth - Evidence from Indian Agricultural Sector

This study investigates price volatility and hedging behavior of four notional commodity futures indices which represent the relevant sectors like Agriculture (AGRI), Energy (ENER), Metal (META) and an aggregate of Agricultural, Energy and Metal commodities (COMDX), retrieved from the commodity futures exchange market, Multi Commodity Exchange (MCX), of India. After adjusting for dates and missing observations, due to holidays, a total of 1,563 daily closing prices over the period of June 8, 2005 to August 31, 2010 have been employed to measure the volatility and hedge ratio. A GARCH (1, 1) model was employed to measure the spot return volatility of respective indices. DVECH-GARCH, BEKK-GARCH and CCC-GARCH were utilized to estimate the time varying hedge ratio. Further, we went for an in-sample performance analysis of the hedge ratios estimated from bivariate GARCH models by employing hedged return and variance reduction approaches. The empirical evidence confirms that all the models were able to reduce the exposure to spot market as perfectly as possible in comparison to the unhedged portfolio.

Spot Return Volatility and Hedging with Futures Contract: Empirical Evidence from the Notional Commodity Futures Indices of India

A safe haven can be broadly defined as an asset allowing the preservation of wealth during financial turmoil. This can be characterized by looking at its negative correlations with risky assets specifically during crises. The present paper employs a Dynamic Conditional Correlation Autoregressive Conditional Heteroskedasticity (GARCH) Dynamic Conditional Correlation (DCC) (DCC-GARCH) model proposed by Engel (2002) to test the safe haven property of gold against stock market in India during the recent financial crisis. For the purpose we utilize 3001 daily observations (after adjusting for the dates and missing observations due to holidays) on gold price and BSE SENSEX index closing price from 1 st January, 1998 to 30 th September, 2009. The empirical evidence is consistent with the study by Baur and Lucey (2010) that gold is a safe haven and hedge in extreme stock market conditions.

Santhosh Kumar

Papers

Spot Return Volatility and Hedging with Futures Contract: Empirical Evidence from the Notional Commodity Futures Indices of India

DCC Analysis of the ‘Safe Haven’ Property of Gold against Stock Market: Indian Scenario