Whether commodity futures market in agriculture is efficient in price discovery? - An econometric analysis

In any agriculture-dominated economy, like India, farmers face not only yield risk but price risk as well. Commodity futures and derivatives have a crucial role to play in the price risk management process, especially in agriculture. The present study is an investigation into the futures markets in agricultural commodities in India. The statistical analysis of data on price discovery in a sample of four agricultural commodities traded in futures exchanges have indicated that price discovery does not occur in agricultural commodity futures market. The econometric analysis of the relationship between price return, volume, market depth and volatility has shown that the market volume and depth are not significantly influenced by the return and volatility of futures as well as spot markets. The Bartlett’s test statistic has been found insignificant in both the exchanges, signifying that the futures and spot markets are not integrated. The exchange-specific problems like thin volume and low market depth, infrequent trading, lack of effective participation of trading members, non-awareness of futures market among farmers, no well-developed spot market in the vicinity of futures market, poor physical delivery, absence of a well-developed grading and standardization system and market imperfections have been found as the major deficiencies retarding the growth of futures market. The future of futures market in respect of agricultural commodities in India, calls for a more focused and pragmatic approach from the government. The Forward Markets Commission and SEBI have a greater role in addressing all the institutional and policy level constraints so as to make the agricultural commodity futures and derivatives a meaningful, purposeful and vibrant segment for price risk management in the Indian agriculture.Agricultural Finance,

Using skewness and the first-digit phenomenon to identify dynamical transitions in cardiac models

Disruptions in the normal rhythmic functioning of the heart, termed as arrhythmia, often result from qualitative changes in the excitation dynamics of the organ. The transitions between different types of arrhythmia are accompanied by alterations in the spatiotemporal pattern of electrical activity that can be measured by observing the time-intervals between successive excitations of different regions of the cardiac tissue. Using biophysically detailed models of cardiac activity we show that the distribution of these time-intervals exhibit a systematic change in their skewness during such dynamical transitions. Further, the leading digits of the normalized intervals appear to fit Benford's law better at these transition points. This raises the possibility of using these observations to design a clinical indicator for identifying changes in the nature of arrhythmia. More importantly, our results reveal an intriguing relation between the changing skewness of a distribution and its agreement with Benford's law, both of which have been independently proposed earlier as indicators of regime shift in dynamical systems.Comment: 11 pages, 6 figures; incorporating changes as in the published versio