A Study on Empirical Analysis of Price Discovery and Causality between NSE Spot and Future Market in India

2011 ◽  
Author(s):  
Jaheer Mukthar
2018 ◽  
Vol 9 (4) ◽  
pp. 117
Author(s):  
Maoguo Wu ◽  
Zhehao Zhu

Restrictive measures implemented by governments have a great impact on the price discovery function of stock index futures. This study compares the price discovery function of CSI 500 stock index futures and CSI 500 stock index before and after the implementation of restrictive measures based on the reaction speed to new information, the price ratio of new information and the price contribution of both future market and spot market. It also analyzes the difference between the price discovery function of the future market and that of the spot market and thus proposes policy implications accordingly.Utilizing data of CSI 500 stock index futures in the period of the stock market crash, this study compares the price discovery function before and after the implementation of restrictive measures. By means of the VECM model and common factor analysis, it further investigates the difference in the price contribution of the two markets. Contributing to existing literature on the relationship between the future market and the spot market, this study explores the change in the price contribution of the two markets and therein studies the impact of restrictive measures on the price discovery function. Empirical evidence finds that before the implementation of restrictive measures, the price discovery function worked more efficiently, while, however, after the implementation of restrictive measures, the price discovery function did not work. Hence, stock index futures do assist in the price discovery of the spot market. In some special time periods, however, due to the impact of restrictive policies, the price contribution of the spot market exceeded that of the future market, implying that the price discovery function of the CSI 500 stock index future market is unstable.


Author(s):  
Suraj E. S ◽  
Ojasvi Gupta

This paper focused on studying the agricultural commodity prices in India and it's extreme volatility due to many reasons such as government interference, growth, market forces factors, regular floods and droughts, transport and warehousing problems, etc. These are contributing factors to demand fluctuations. In this case, the future market plays an important role in the economy. The demand for commodity futures has three particular economic functions: price discovery, price risk management, and price volatility. The future market plays a key role in the process of price discovery. The main aim of this system is to regulate prices to minimize uncertainty, to provide price signals to market traders for futures spot prices through the price discovery phase. So, this study emphasized the role of the derivative market in reducing the volatility of agricultural commodity prices in the Indian market. Keywords: volatility, future market, derivatives


2009 ◽  
Vol 34 (2) ◽  
pp. 41-56 ◽  
Author(s):  
Madhusudan Karmakar

In a perfectly functioning world, every piece of information should be reflected simultaneously in the underlying spot market and its futures markets. However, in reality, information can be disseminated in one market first and then transmitted to other markets due to market imperfections. And, if one market reacts faster to information than the other, a lead-lag relation is observed The lead-lag relationship in returns and volatilities between spot and futures markets is of interest to academics, practitioners, and regulators. In India, there are very few studies which have investigated the lead-lag relationship in the first moment of the spot and futures markets This study investigates the lead-lag relationship in the first moment as well as the second moment between the S&P CNX Nifty and the Nifty future. It also investigates how much of the volatility in one market can be explained by volatility innovations in the other market and how fast these movements transfer between these markets. It conducts Multivariate Cointegration tests on the long-run relation between these two markets. It investigates the daily price discovery process by exploring the common stochastic trend between the S&P CNX Nifty and the Nifty future based on vector error correction model (VECM). It examines the volatility spillover mechanism with a bivariate BEKK model. Finally, this study captures the effects of recent policy changes in the Indian stock market. The results reveal the following: The VECM results show that the Nifty futures dominate the cash market in price discovery. The bivariate BEKK model shows that although the persistent volatility spills over from one market to another market bi-directionally, past innovations originating in future market have the unidirectional significant effect on the present volatility of the spot market. The findings of the study thus suggest that the Nifty future is more informationally efficient than the underlying spot market. These findings may provide insights on the information transaction and index arbitrage between the CNX Nifty and futures markets.


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