Purpose -The purpose of this paper is to examine whether futures markets play a dominant role in the price discovery process. The rate of convergence of information from one market to another is analyzed to infer the efficiency of futures as an effective hedging tool. Design/methodology/approach -The paper uses a two-regime threshold vector autoregression (TVAR) and a two-regime threshold autoregression for six commodities. The regimes (or states) are defined around the expiration week of the futures contract. Findings -This paper finds evidence for price discovery process happening in the futures market in five out of six commodities. However, the rate of convergence of information is slow, particularly in the non-expiration weeks. For copper, gold and silver, the rate of convergence is almost instantaneous during the expiration week of the futures contract affirming the utility of futures contracts as an effective hedging tool. In case of chickpeas, nickel and rubber the convergence worsens during the expiration week indicating the non-usability of futures contract for hedging. Originality/value -This paper extends the framework developed by Garbade et al. by superimposing a two-regime TVAR model to quantify the price discovery process. It is the first paper to analyze the differential impact of price discovery and convergence during expiration week (compared to non-expiration weeks) for the Indian commodities market.

Juvenile myoclonic epilepsy (JME) is a common form of epilepsy with a substantial genetic basis to its etiology. While earlier studies have identified EFHC1 as a causative gene for JME, subsequent studies have suggested that ethnicity may play a role in determining expression of the JME phenotype among individuals carrying EFHC1 mutations. Here, we report on our studies on EFHC1 in JME patients from India. We examined the complete structure of the EFHC1 transcript from 480 JME patients and 700 control chromosomes by direct sequencing. Functional correlates of mutations were studied by immunolocalization experiments in cultured mammalian cells and protein homology modeling by in silico methods. Thirteen mutations, of which 11 were previously not known, were identified in 28 JME patients. These mutations accounted for about 6% of the patients examined. Functional studies suggest that these EFHC1 mutations result in microtubule-related abnormalities during cell division. In silico analysis for a subset of mutations suggests that they may affect EFHC1 protein domains, compromising its ability to interact with other proteins. Our observations strengthen the evidence supporting a role for EFHC1 in JME in a population ethnically and geographically distinct from the one in which the gene was initially identified, and broaden the extent of allelic heterogeneity in the gene.

The present study attempts to track the transmission of volatility across major international stock markets over a span of 20 years, which includes both crisis (contagion form) and non-crisis periods. It also investigates whether global transmission of volatility follows a pattern. The study uses bi-variate EGARCH model in order to capture spillover between a pair of stock markets and the estimation window is one year with a sliding frequency of one quarter. The results show that, there is a spillover of volatility between international stock markets at all times. Results also indicate that in almost all cases, the pattern of spillover is non-random. Finally, the study characterizes the spillover pattern between international stock markets using suitable theoretical distributions.

The present study attempts to track the transmission of volatility across 11 international stock markets in the Asia-Pacific region over a period of 20 years, which includes both crisis (i.e., contagion form) and non-crisis periods. It also investigates whether the global transmission of volatility follows a pattern. The study contributes to the literature in two ways: (a) it provides a historical map of volatility transmission in the Asia-Pacific region and (b) it identifies the path and pattern of volatility spillover across stock markets in the Asia-Pacific region.

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