The present study examines the arbitrage efficiency of the Indian equity futures market over the sample period June 2000 to December 2005. The results suggest that although stable and strong long-run relationship exists between futures and cash markets but futures show significant deviations from its cost-of-carry price, which offers exploitable arbitrage opportunities to the traders. Mispricing has been observed to be a direct function of time-to-maturity, stochastic behavior of interest rates, short sales restriction in the cash market, information asymmetry in both futures and cash markets and restricted exposure of institutional traders to the futures market. Moreover, basis shows significant mean reverting behavior, which indicates that early liquidation option as suggested by Neal (1996) may be helpful in improving the price discovery efficiency in futures as well as cash markets.

Price discovery and risk transfer (i.e. hedging) have been considered as the pivot functions of the futures market. A market is said to be weak form efficient if the current market price and past price are uncorrelated (i.e. the asset price movements are random). A market is known as semi-strong efficient, if it absorbs and reflects the market information as well as the public information (viz., corporate actions, political announcement, etc.). Strong form efficient market is one which neglects the chances of even insiders to make abnormal profits on the basis of first hand information. Efficient price discovery in the futures market has many advantages for the traders as well as for the regulators. The current study is an attempt to investigate whether Indian equity futures market is efficient and to study whether it provides any significant information during the highvolatility period.

The present study examines the impact of the 2008 financial crisis on the hedging effectiveness of three index futures contracts traded on the National Stock Exchange of India for near, next and far month contracts over the sample period of January 2000 – June 2014. The hedge ratios were calculated using eight methods; Naive hedging, Ederington’s Model, Autoregressive Integrated Moving Average, Vector Autoregressive, Vector Error Correction Methodology, Generalized Autoregressive Conditional Heteroskedasticity, Exponential Generalized Autoregressive Conditional Heteroscedasticity and Threshold Generalized Autoregressive Conditional Heteroskedasticity. The study finds an improvement in hedging effectiveness during the post-crisis period, which implies that during the high-volatility period hedging effectiveness also improves. It was also found that near month futures contracts are a more effective tool for hedging as compared to next and far month contracts, which imply that liquidity is a more important determinant of hedging effectiveness than hedge horizons. The study also finds that a time-invariant hedge ratio is more efficient than time-variant hedging. Therefore, knowledge of sophisticated econometrical tools does not help to improve hedge effectiveness.

The present study investigates the information dissemination efficiency of the Indian equity futures market. Daily log returns of all indices as well as individual stock futures contracts understudy have been found to be non-normal and responding asymmetrically to the information shocks. Volatility clustering in daily log returns of all indices and individual stock futures contracts has been identified, which suggests that Indian equity futures market is not an efficient price-discovery vehicle. In addition, the present study finds an evidence of leverage effect, which implies that traders assign more weightage to bad news, whereas, they cautiously react to positive news. Mean reversion in daily log returns of the Indian equity futures market further suggests that traders (especially retail traders) need to be overcautious while adding equity futures as leverage products in their portfolio because in a highly volatile market, framing a trading rule to earn super normal profit may be an easy task for big/institutional traders but may not be possible for small/uninformed traders.

The present study examines the long memory in stock liquidity and returns in Indian equity market by using data for broad indices from January, 1997 to December, 2019 by applying the hurst exponent (1951) rescaled range analysis. It is observed that time varying degree of persistence nature in individual and full series analysis of returns. Moreover, liquidity series exhibit long memory process in Nifty