Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices

2019 ◽  
Vol 77 ◽  
pp. 92-112 ◽  
Author(s):  
Duminda Kuruppuarachchi ◽  
Hai Lin ◽  
I.M. Premachandra
Keyword(s):  
Market Efficiency ◽  
Futures Market ◽  
Commodity Futures ◽  
Time Varying ◽  
Risk Premiums

An Empirical Analysis of Market Efficiency and Price Discovery in Indian Commodity Market

2018 ◽  
Vol 19 (3) ◽  
pp. 771-789 ◽  
Author(s):  
Shashi Gupta ◽  
Himanshu Choudhary ◽  
D. R. Agarwal
Keyword(s):  
Error Correction ◽  
Market Efficiency ◽  
Price Discovery ◽  
Correction Term ◽  
Futures Market ◽  
Commodity Futures ◽  
Spot Price ◽  
Futures Prices ◽  
Short Term ◽  
Important Indicator

The present article is an attempt to empirically investigate the long-term market efficiency and price discovery in Indian commodity futures market. The study has been conducted with eight commodities which include two agricultural commodities, two industrial commodities, two precious metal and two energy commodities. Sophisticated statistical methods like restricted cointegration and vector error correction model (VECM) are used to analyse the spot and futures prices time series. Restricted cointegration test shows that near-month futures prices for all the commodities are cointegrated with the spot prices but futures prices of all the commodities are inefficient to predict the future spot price. Indian commodity futures market evidenced as the thinly traded market (Kumar & Pandey, 2013, Journal of Indian Business Research, 5(2), 101–121) rejects the null hypothesis of efficiency and unbiasedness for all the eight commodities which reconfirms the result of Fortenbery and Zapata (1997, Journal of Futures Markets, 17(3), 279–301). The presence of short-term biases in the Indian futures market is evidenced in the results of VECM model which indicates the presence of informational efficiency. The statistically significant value of past prices of spot and futures confirm the short-term inefficiency and biasedness. The significant value of error correction term (ECT) of futures prices suggests that commodity futures are the most important indicator of commodity price movements. The important implication of the results is for market traders. They can use the futures prices to discover the new equilibrium and earn profits by transmitting it to the spot market. The better understanding of the interconnectedness of these market would be useful for policymakers who try to establish stability in the financial markets.

Price Discovery and Market Efficiency of Commodities Futures Market in India- A Cointegration and Causality Analysis

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Shaik Masood ◽  
T. Satyanarayana Chary
Keyword(s):  
Market Efficiency ◽  
Price Discovery ◽  
Spot Market ◽  
Futures Market ◽  
Commodity Futures ◽  
Causality Analysis ◽  
Long Run ◽  
Integration Test ◽  
Short Run

The paper studies the Indian commodity futures market in order to determine the price discovery, long run market efficiency and short run dynamics in futures market using by time series analysis tools. To test the market efficiency and long run equilibrium, tools like Engle and Granger co-integration test (1987) and Johansen co-integration test (1988) have been applied. The Granger Causality (1969) test is used test the market efficiency to infer cause and affect relationship between spot and futures market in India. To examine efficiency of commodity futures and spot market the MCXs1 four spot and futures commodity indices data are used. The paper observes that the role of commodity futures is very significant in price discovery, and improving efficiency of the market.

Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India

2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan
Keyword(s):  
Banking Sector ◽  
Stock Exchange ◽  
Research Work ◽  
Futures Market ◽  
Least Square ◽  
Time Varying ◽  
Hedge Ratio ◽  
Hedging Effectiveness ◽  
Out Of Sample ◽  
Optimal Hedge

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets

Sign in / Sign up

Export Citation Format

Share Document