This issue contains five research papers. The first paper, “Information, Price Discovery and Causality in the Indian Stock Index Futures Market”, by Pratap Chandra Pati and Purna Chandra Padhan, examines the price discovery process and lead-lag relationship between NSE S&P CNX Nifty stock index futures and its underlying spot index, using daily data from January 1, 2004 to December 31, 2008.

It investigates the long-term and short-term dynamics of prices between spot and futures markets, using Johansen-Juselius cointegration test, Vector Error Correction Model (VECM), impulse response functions and variance decomposition. In addition to it, the recently developed Granger non-causality tests of Toda and Yamamoto (1995) and Dolado and Lutkepohl (1996) have also been applied to examine the causal relationship between spot and futures markets. The obtained results support the existence of a long-run relationship between spot and futures prices. Further, VECM indicates short-run unidirectional causality from futures to spot market. In addition, the study finds unidirectional Granger causality from futures market to spot market through Toda-Yamamoto-Dolado-Lutkepohl causality test. The shape of the impulse response graphs shows that spot market has a larger response to shocks to the futures index than the futures responses to spot innovations. The results of variance decomposition indicate that the futures market shocks dominate over spot market in explaining the variation in spot market. However, disturbance originating from spot market contributes very less percentage variability to futures market. The obtained results have important implications for traders, regulatory bodies and practitioners.

The second paper, “Price Discovery in NSE Spot and Futures Markets of Selected Oil and Gas Industries in India: What Causes What?”, by P Srinivasan, employs the Johansen’s cointegration technique followed by the VECM to examine the causal relationship between National Stock Exchange (NSE) spot and futures markets prices of selected nine oil and gas industry stocks of India. The empirical analysis was conducted on the daily data series from May 12, 2005 to January 29, 2009. The analysis reveals that there exists a long-run relationship between spot and futures prices of each of the selected individual securities. Besides, the study also indicates a bidirectional relationship between spot and futures markets prices in the case of four oil industry stocks, spot leading the futures prices in the case of three stocks, and the futures leading the spot prices in the case of two selected gas and oil industry stocks.

The third paper, “Estimating the Optimal Hedge Ratio in the Indian Equity Futures Market”, by Kapil Gupta and Balwinder Singh, attempts to suggest an optimal hedge ratio for Indian traders through the examination of three indices, namely, Nifty, Bank Nifty and CNXIT, and 84 most liquid individual stock futures traded on the NSE of India, over the period January 2003 to December 2006. The study compares the efficiency of hedge ratios estimated through OLS, VAR, VECM, GARCH(p, q), TARCH(p, q) and EGARCH(p, q) in the minimum variance hedge ratio framework, as suggested by Ederington (1979).

The findings of the study conform to the theoretical properties of futures markets and suggest that unconditional hedge ratio, after controlling for basis risk, outperforms the conditional hedge ratio. The results favor the hedge ratios estimated through VAR or VECM because both the markets are cointegrated in Engle and Granger (1987) framework, and the findings are consistent with that of Alexander (1999).

The fourth paper, “Determinants of Hedging: An Empirical Investigation for Mauritius”, by Indranarain Ramlall, attempts to fill an important gap in the empirical literature pertaining to the determinants of hedging by focusing on an upper-income developing country, Mauritius. From the data on Mauritian firms for the year 2005-06, it transpires that managers’ incentives to hedge and the tax convexity motive to hedge, along with financial and operational explanations underlying hedging, are basically not applicable in the case of Mauritius. The size and age of firms are found to be positively related to hedging, endorsing the fact that high fixed costs and knowledge in establishing a derivative framework are important.

The last paper, “A Study on the Dependence Structure of Aggregate Loss Distributions Based on Frequency Dependence”, by Woohwan Kim and Seungbeom Bang, discusses the critical issues in the determination of bank-wide operational risk capital under Advanced Measurement Approach (AMA). Especially, Loss Distribution Approach (LDA), which is one of the main methods in AMA, involves statistical inference on the frequency and severity distribution, and then loss distribution is generated via Monte-Carlo simulation. The paper proposes a methodology for generating firm-wide loss distribution based on frequency dependence, which is a primary source of the dependence structure. It especially highlights how to model the frequency dependence of loss distribution via copula, which is a function that links marginal and joint distributions. The main contribution of this paper is that it provides a very flexible method for modeling the dependence of individual loss distribution. It finds that bank-wide capital increases at about 15% as the dependence becomes stronger, and this empirical result is consistent with changes in the severity distribution of marginal loss distributions.

- - Nupur Hetamsaria
Consulting Editor