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The purpose of this paper is to demonstrate importance of usage of sector indices which provides insight for sector specific investment strategies and direction for suitable policy formulation for the Indian industry. It investigates long run, short run and causality relationships between eight identified sector indices and Sensex for the post subprime period.

The study uses Vector Error Correction Model (VECM) for econometric analysis. It employs Generalized Impulse Response and Variance Decomposition analysis for developed multivariate framework in order to provide information about precise interplay of the sector indices.

Long-term relationships between sector indices were determined by the usage of VECM indicating minimal benefits from diversifying investments to different sectors. Limited lead – lag short run relationships between sector indices were observed. Banking index played a predominant and integrating role in moving other indices. During this period of recovery; most sectors were protected and provided marginally better returns due to robust Banking policy. Realty and Metal were other significant drivers influencing remaining sectors contemporaneously. The study for the post subprime crisis period helps to understand the importance and behavior of interrelated sector indices and Sensex in the dynamic economic environment.

The study clearly provides direction for sector specific investment strategies and policy formulation.

The study highlights utility and importance of usage of sector indices. No study using sector indices for the Indian economy have been done earlier employing VAR for the post subprime crisis period.

The purpose of this paper is to examine cross-correlation in stock returns of SAARC countries, conditional and unconditional volatility of stock markets and to test efficient market hypothesis (EMH).

Stock indices of India, Bangladesh, Sri Lanka and Pakistan are considered to serve as proxy for stock markets in SAARC countries. Data consist of daily closing price of stock indices from 2000 to 2011. Since preliminary testing indicated presence of serial autocorrelation and volatility clustering, family of GARCH models is selected.

Results indicate presence of serial autocorrelation in stock market returns, implying dependence of current stock prices on stock prices of previous times and leads to rejection of EMH. Significant relationship between stock market returns and unconditional volatility indicates investors’ expectation of extra risk premium for exposing their portfolios to unexpected variations in stock markets. Cross-correlation revealed level of integration of South Asian economies with global market to be high.

Business cycles and other macroeconomic developments affect most companies and lead to unexplained relationships. The paper finds stock markets to exist at different levels of development as economic liberalization started at different points of time in SAARC countries.

Correlation between stock indices of SAARC economies are found to be low which is in line with intra-regional trade being one of lowest as compared to other regional groups. Results point towards greater need for economic cooperation and integration between SAARC countries. Greater financial integration leads to development of markets and institutions, effective price discovery, higher savings and greater economic progress.

The paper focuses on EMH and risk return relation for SAARC nations.

The purpose of this paper is to study the market efficiency, unbiasedness and the direction of causality among four agricultural commodity futures contracts for a forecasting horizon of 28 days, 56 days and 84 days which are traded at National Commodity and Derivatives Exchange Ltd.

To analyse the efficiency of futures market in Indian scenario, we focus on maize, chickpea, soybean and wheat which are among the most important agricultural commodities traded in India. In the first step, Augmented Dickey-Fuller test and nonparametric Phillips-Perron approaches have been used to examine the stationarity of all futures and spot price series. After testing the presence of cointegration in futures and spot series using Johansen’s Cointegration approach, the joint restrictions of β ₀=0, β ₁=1 and β ₁=1 on the cointegrating vectors were imposed to test whether the futures price is an unbiased predictor of spot at contract maturity. In the next step, linear Toda and Yamamoto (1995) and the nonparametric Diks and Panchenko (2006) causality tests were applied to examine the direction of causality. Finally, nonlinear test were applied on the vector error correction model (VECM) residuals to investigate whether any remaining causality is strictly nonlinear in nature.

The results of cointegration tests between futures and spot prices of the selected agricultural commodities indicated a long term relationship do exist in three out of four futures contracts. However, the Wald tests results on the cointegrating vectors indicate markets as inefficient and biased. Further, analysis of short-term relationship using alternate tests of causality do not give consistent results for same commodity series indicating that results may vary due to alternate measures and specifications. Finally, if we consider the results of Diks-Panchenko test on the filtered VECM-residuals, results provide evidence that if cointegration is taken into account; neither spot nor future leads or lags the other consistently.

The results are based on the sample of four agricultural futures commodity contracts. The study can be extended to a larger sample of contracts and relative efficiency of each contract can be explored.

There are very few studies that have explored the efficiency, unbiasedness and direction of causality using both linear and nonlinear techniques for Indian agriculture commodity futures market for different forecasting horizons.