Study on Efficiency of Stock Futures Market in India

In a market economy, efficient functioning of the markets becomes a pre-condition for attaining the desired goal of economic welfare. Ideally, any market is expected to be efficient in its functioning; however, the reality may be far from it. In fact, efficient futures market is a pre-condition for risk management through hedging operations. Hedging is the most important purpose behind the existence of futures market. So, the very purpose of its existence would get defeated if inefficiency prevails in the futures market. The efficiency of futures market is revealed in the ability of spot market and futures market to move in tandem with each other exhibiting the desired economic relationship between the two. This study aims at examining whether the financial futures market in India is functioning efficiently or not. Poor liquidity in the market acts as a limiting factor on the efficiency. So, we have chosen to examine the efficiency of Index Futures of NSE on NIFTY 50 and BANKNIFTY as both of them enjoy a very high liquidity. The study is based on five different time intervals spanning from 1-minute to 120-minutes. Data analysis is performed using EViews 6 software for regression analysis and conducting necessary tests like Augmented Dickey-Fuller Test, Phillips-Perron Test, and Engle – Granger Test for Error Correction Model. The results show that the two price series are cointegrated, and reveal an excellent state of affairs in terms of the desired economic relationship in long-run for the market efficiency in both the indices across all the five time intervals. However, the state of affairs in the short-run is just opposite. The speed of adjustment in short-run is too slow. It takes 35 minutes to completely return to the desired relationship once a drift has taken place. As such, theoretically, the phenomenal increase in algorithmic trading was expected to help the market get rid of this problem; however, the reality seems to be just opposite. Therefore, we wonder whether the algorithmic trading has worked towards solving the problem, or aggravating it.