Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Relation between Open Interest and Volatility in Commodities Markets.


Affiliations
1 Assistant Professor, Institute of Management, Nirma University, Ahmedabad, Gujarat, India
2 Director, Shanti Business School, Ahmedabad, Gujarat, India
3 Assistant Professor, Shanti Business School, Ahmedabad, Gujarat, India
     

   Subscribe/Renew Journal


The purpose of this paper is to examine the consequence of open interest on volatility of futures markets. This paper emphasises on investigating the relation between open interest and the commodities futures. An effort was made to capture the size and change in speculative behaviour in futures markets by examining the behaviour of futures prices due to open interest. The findings show that the depth of market has an effect on the futures market’s volatility, but the direction of this effect depends on the type of contract. The sample includes daily data covering the period 2010-2020 from the Indian commodities futures markets (including crude oil futures). A two-stage methodology was employed by the authors: first, the authors investigate the relation between open interest and volatility. Next, the authors employ the E-GARCH model and considers the asymmetric response of volatility to shocks of different signs. Finally, the authors consider a regression framework to scrutinise the contemporaneous relationships between open interest and futures prices (volatility).

Keywords

Futures, Commodities, E-GARCH, Volatility, Open Interest
Subscription Login to verify subscription
User
Notifications
Font Size


  • Aghazadeh, T., Kangarlouei, S. J., & Motavassel, M. (2014). The effect of earnings forecasts quality on risk taking and firm’s value in firms listed in Tehran stock exchange. Journal of Commerce & Accounting Research, 3(3), 1-8.
  • Bessembinder, H., & Seguin, P. J. (1993). Price volatility, Gannon, trading volume, and market depth: Evidence from futures markets. Journal of Financial and Quantitative Analysis, 28(1), 21-39.
  • Bessembinder, H., Chan, K., & Seguin, P. S. (1996). An empirical examination of information, differences of opinion and trading activity. Journal of Financial Economics, 40(1), 105-134.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 31, 307-327.
  • Brailsford, T. J. (1996). The empirical relationship between trading volume, return and volatility. Accounting and Finance, 36(1), 89-111.
  • Chang, E., Chou, R. Y., & Nelling, E. F. (2000). Market volatility and the demand for hedging in stock index futures. Journal of Futures Markets, 20(2), 105-125.
  • Chang, K., Wang, S., Ke, P., Yu-Rong, H., & Zhen, Y. (2012). The valuation of futures options for emissions allowances under the term structure of stochastic multi-factors. WSEAS Transactions on Systems, 11(12), 661-670.
  • Chang, K., & Yu, Z. (2013). One-factor and two-factor dynamic hedging of futures contracts with different maturities for emissions allowances. Proceedings of the 2nd International Conference on Systems Engineering and Modeling (ICSEM- 13), 217-224.
  • Chen, N., Cuny, C. J., & Haugen, R. A. (1995). Stock volatility and the levels of the basis and open interest in futures contracts. Journal of Finance, 50(1), 281-300.
  • Chopra, N. (2019). Sensitivity analysis using GARCH model: Evidence from Indian stock market. Journal of Commerce & Accounting Research, 8(2), 39-47.
  • Ciner, C. (2002). Information content of volume: An investigation of Tokyo commodity futures market. Pacific-Basin Finance Journal, 10(2), 201-215.
  • Clark, P. K. (1973) A subordinated stochastic process model with finite variance for speculative prices. Econometrica: Journal of the Econometric Society, 41(1), 135-155.
  • Copeland, T. E. (1976). A model of asset trading under the assumption of sequential information arrival. The Journal of Finance, 31(4), 1149-1168.
  • Desai, J. M., & Joshi, N. (2021). Volatility analysis and volatility spillover across equity markets between India and selected global indices. Journal of Commerce & Accounting Research, 10(4), 95-103.
  • Ender, W. (1995). Applied econometric time series. New York: John Wiley & Sons.
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50, 987-1007.
  • Epps, T. W., & Epps, M. L. (1976). The stochastic dependence of security price changes and transaction volumes: Implications for the mixture-of-distributions hypothesis. Econometrica: Journal of the Econometric Society, 305-321.
  • Ferris, S. P., Park, H. Y., & Parks, K. (2002). Volatility, open interest, volume, and arbitrage: Evidence from the S&P 500 futures market. Applied Economics Letters, 9, 369-372.
  • Floros, C. (2007). Price and open interest in Greek stock index futures market. Journal of Emerging Market Finance, 6(2), 191-202.
  • Fung, H., & Patterson, G. A. (1999). The dynamic relationship of volatility, volume, and market depth in currency futures markets. Journal of International Financial Markets, Institutions and Money, 9(1), 33-59.
  • Gallant, A. R., Rossi, P., & Tauchen, G. (1992). Stock prices and volume. Review of Financial Studies, 5, 199-242.
  • Girma, P. B., & Mougoue, M. (2002). An Empirical examination of the relation between futures spreads volatility, volume and open interest. Journal of Futures Markets, 22(11), 1083-1102.
  • Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424-438.
  • Hendershott, T., Jones, C. M., & Menkveld, A. J. (2011). Does algorithmic trading improve liquidity? The Journal of Finance, 66(1), 1-33.
  • Jennings, R. H., Starks, L. T., & Fellingham, J. C. (1981). An equilibrium model of asset trading with sequential information arrival. The Journal of Finance, 36(1), 143-161.
  • Kamara, A. (1993). Production flexibility, stochastic separation, hedging, and futures prices. Review of Financial Studies, 6(4), 935-957.
  • Karpoff, J. M. (1987). The relation between price changes and trading volume: A survey. Journal of Financial and Quantitative Analysis, 22(1), 109-126.
  • Kumar, B., & Pandey, A. (2010). Price volatility, trading volume and open interest: Evidence from Indian commodity futures markets. Social Science Research Network, 1-56.
  • Mahadevan, S. (2021). Predicting the likelihood of hedging by companies in India - A logit model approach. Journal of Commerce & Accounting Research, 10(3), 1-12.
  • Neri, F. (2012). Quantitative estimation of market sentiment: A discussion of two alternatives. WSEAS Transaction on Systems, 11(12), 691-702.
  • Neri, F. (2010). Software agents as a versatile simulation tool to model complex systems. WSEAS Transactions on Information Science and Applications, 7(5), 609-618.
  • Ragunathan, V., & Peker, A. (1997). Price variability, trading volume and market depth: Evidence from the Australian futures market. Applied Financial Economics, 7, 447-454.
  • Schwert, G. W. (1990). Stock volatility and crash of 87. Review of Financial Studies, 3(1), 77-102.
  • Sharma, J. L., Mougoue, M., & Kamath, R. (1996). Heteroscedasticity in stock market indicator return data: volume versus GARCH effects. Applied Financial Economics, 6(4), 337-342.
  • Sutcliffe, C. M. S. (1993). Stock index future: Theories and international evidence. London, UK: Chapman & Hall.
  • Wang S. S., Huang J. M., Chang, K., Huang, J.-Y., & Yang, X. (2013). Idiosyncratic volatility has an impact on corporate bond spreads: Empirical evidence from Chinese bond markets. WSEAS Transactions on Systems, 12(5), 280-289.
  • Watanabe, T. (2001). Price volatility, trading volume, and market depth: Evidence from the Japanese stock index futures market. Applied Financial Economics, 11, 651-658.
  • Yang, J., Bessler, D. A., & Fung H. G. (2004). The information role of open interest in futures markets. Applied Economics Letters, 11(9), 569-573.
  • Yen, S. M., & Chen, M. (2010). Open interest, volume, and volatility: Evidence from Taiwan futures markets. Journal of Economics and Finance, 34(2), 113-141.

Abstract Views: 5

PDF Views: 0




  • Relation between Open Interest and Volatility in Commodities Markets.

Abstract Views: 5  |  PDF Views: 0

Authors

Nisarg A. Joshi
Assistant Professor, Institute of Management, Nirma University, Ahmedabad, Gujarat, India
Neha Sharma
Director, Shanti Business School, Ahmedabad, Gujarat, India
Anurodh Singh Khanuja
Assistant Professor, Shanti Business School, Ahmedabad, Gujarat, India

Abstract


The purpose of this paper is to examine the consequence of open interest on volatility of futures markets. This paper emphasises on investigating the relation between open interest and the commodities futures. An effort was made to capture the size and change in speculative behaviour in futures markets by examining the behaviour of futures prices due to open interest. The findings show that the depth of market has an effect on the futures market’s volatility, but the direction of this effect depends on the type of contract. The sample includes daily data covering the period 2010-2020 from the Indian commodities futures markets (including crude oil futures). A two-stage methodology was employed by the authors: first, the authors investigate the relation between open interest and volatility. Next, the authors employ the E-GARCH model and considers the asymmetric response of volatility to shocks of different signs. Finally, the authors consider a regression framework to scrutinise the contemporaneous relationships between open interest and futures prices (volatility).

Keywords


Futures, Commodities, E-GARCH, Volatility, Open Interest

References