Indian agricultural commodity derivatives market: in conversation with S Sivakumar, divisional chief executive, agri business division, Itc Ltd.

Though the agricultural sector contributes significantly to the Indian economy, it faces several bottlenecks, one of those being the antiquated laws governing agricultural marketing and price discovery, leading to low price realization by Indian farmers. In India, six national level exchanges offer commodity derivatives contracts on commodities, with some having electronic spot exchanges to facilitate spot trading of commodities. However, farmers' participation in these exchanges has been poor. ITC-ABD, one of the largest aggregators and exporters of Indian agri-commodities, has started using these exchange platforms to hedge price risk. With experience of over three decades in the agricultural sector, Mr. S. Sivakumar has a deep understanding of the commodity markets and the needs of Indian farmers. This interview aims to get an insight into his views on increasing farmers' participation in commodity derivatives trading and more importantly, to understand ITC-ABD's commodity hedging strategy

Do VaR exceptions have seasonality? An empirical study on Indian commodity spot prices

This paper compares three models namely RiskMetrics's EWMA, ARMA-GARCH and APARCH with normal and Student's t-distribution. These models have been applied to spot prices of seven commodities: aluminium, copper, gold, soyabean, guar seed, chana and cardamom. For these seven commodities, daily value-at-risk (VaR) has been computed for different time horizons and VaR exceptions at 99% confidence interval have been calculated. These models are then compared on the basis of number of VaR exceptions and loss function. Commodity prices tend to exhibit higher volatility during certain time of the year due to seasonality in production and consumption. In this context, we test whether VaR exceptions have any relationship with seasonality in spot prices. Keywords: VaR, GARCH, APARCH, RiskMetrics's EWMA, Commodity spot prices, Commodity seasonalit

Post-issue promoter groups holding, signalling and IPO underprice: evidence from Indian IPOs

This paper attempts to specify the relationship between post-issue promoter groups' retention and Initial Public Offering (IPO) underprice. We also investigate the impact of signalling and financial variables, i.e. offer size, times subscribed, age of the firm, book value, leverage, market volatility and ex-ante uncertainty along with post-issue promoter groups holding on IPO underprice. On using a sample of 92 IPOs, we find IPOs are underpriced at an average of 46.55% during 2002 to 2006. We document a positive relationship between post-issue promoter group holding and IPO underprice. Our results indicate offer size, times subscribed and post-issue promoter group holding are statistically significant in explaining underprice. We also document positive initial day return for IPOs across all industries, while manufacturing sector IPOs are less underpriced than non-manufacturing sector IPOs.IPO underprice; initial public offering; post-issue promoter groups holding; signalling; offer size; age; book value; ex-ante uncertainty; times subscribed; leverage; volatility; India; manufacturing IPOs.

Intraday return dynamics and volatility spillovers between NSE S&P CNX Nifty stock index and stock index futures

Using 5-min intraday transaction prices, this study investigates the relationship between the National Stock Exchange (NSE) S&P CNX Nifty futures and its underlying spot index in terms of both return and volatility. By applying Johansen-Juselius (J-J) cointegration analysis, we find evidence of single common stochastic trend, to which spot and futures prices move together in a long-run equilibrium path. The vector error correction model (VECM) and Granger causality test find that there is unidirectional causality running from futures to spot market. To examine the volatility spillovers between the markets, this study has used bivariate Generalized Autoregressive Conditional Heteroscedastic (GARCH) (1, 1) model with Baba, Engle, Kraft and Kroner (BEKK) parameterization and finds evidence of bidirectional volatility spillovers between spot and futures markets. However, there is pronounced spillover effect of a previous shock and volatility from the futures market to spot market. Hence, we conclude that Nifty futures prices lead spot prices and futures market largely contributes to price discovery. These findings have significant implications for traders in implementing hedging and arbitrage trading strategies, for portfolio managers in managing risk and also for policymakers in assessing market stability.