An Empirical Study on the Lead－Lag Relationship among Trading Volume, Returns and Volatility of Coffee Futures Market

In early 2007, the Government of India (GoI) banned futures trading on some essential agro-commodities such as wheat, rice, and two varieties of lentils due to rising food inflation. However, futures trading in agri-commodities such as chana (chickpea), soy oil, rubber, and potato were temporarily suspended. Professor Abhijit Sen’s committee, constituted to study the relationship between futures trading and agricultural commodities inflation, did not find sufficient evidence of inflationary impact of futures trading in India due to too short period of commodity futures trading. Also, an efficient futures market is required for the producers, traders, and consumers to hedge their price risk. Thus, in this study, we analyze the market efficiency of agricultural futures market and the effect of futures trading on inflation with special reference to chana (chickpea) market in India. This study is for a time frame of 10 years from 2005–2014. The data on closing prices of chana in futures and spot markets and futures trading volume has been collected from National Commodity and Derivatives Exchange, and chana wholesale price index (WPI) monthly data from Office of the Economic Adviser, GoI. The collected data is analyzed for efficiency using Johansen cointegration approach and vector error correction (VEC) restrictions and inflationary effect using Toda Yamamoto (TY) version of Granger causality test. From the results, we find that the spot and futures prices for chana are cointegrated and unbiased, that is, the chana (chickpea) futures market is efficient. But, the futures trading of chana has inflationary impact, that is, futures trading volume of chana affects chana WPI. This research has got direct implications for government and market participants. India is the largest consumer of chana (chickpea)—the third most important pulse crop produced in the world. Thus, the inflationary impact of chana futures trading is a matter of concern for GoI.

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Volatility persistence and trading volume in an emerging futures market

The Journal of Risk Finance ◽

10.1108/15265941011043666 ◽

2010 ◽

Vol 11 (3) ◽

pp. 296-309 ◽

Cited By ~ 10

Author(s):

Pratap Chandra Pati ◽

Prabina Rajib

Keyword(s):

Capital Market ◽

Trading Volume ◽

Price Volatility ◽

Futures Market ◽

Market Volatility ◽

Leverage Effect ◽

Time Varying ◽

Conditional Volatility ◽

Content Type ◽

Futures Contract

PurposeThe purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.Design/methodology/approachTo estimate the volatility and capture the stylized facts of fat‐tail distribution, volatility clustering, leverage effect, and mean‐reversion in futures returns, appropriate ARMA‐generalized autoregressive conditional heteroscedastic (GARCH) and ARMA‐EGARCH models with generalized error distribution have been used. The ARMA‐EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time‐varying conditional volatility.FindingsThe paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish.Practical implicationsResearch findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume‐price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions.Originality/valueEquity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set.

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