SAMVAD: International Journal of Management

Open Access Open Access  Restricted Access Subscription Access

Empirical Study on Price Discovery Role in Non-Precious Metals Market in India


Affiliations
1 WISDOM, State Bank of India School of Commerce and Banking, Banasthali University, India
2 FLAME University, Pune, India
 

Demand for most industrial metals signifies the pick-up in the level of economic activity in the country. Industrial metals saw asubstantial increase in trading interest on Multi Commodity Exchange, which raises the need to analyse the market efficiency and the relationship between spot and futures market.Statistical tools like ADF, Johansen Co-integration Test and Vector Error Correction Model (VECM) are applied to see the lead lag relationship between spot and future market of various industrial metals like Copper, Aluminium, Nickel, Lead and Zinc. Empirical results prove bidirectional causality and Spot market adjusts at a faster pace to restore long-run equilibrium in most of the industrial metals.

Keywords

Future Price, Johansen Co-Integration Test, Metals, Spot Price, Vecm Granger Causality Test.
User
Notifications
Font Size

  • Arora, S., & Kumar, N. (2013). Role of futures market in price discovery. Decision, 40(3), 165-179.

  • Asteriou, D., & Hall, S. (2007). Applied Econometrics A modern Approach. Palgrave Macmillan.

  • Bekiros, S., & Diks, C. (2008). The Relationship between Crude Oil Spot and Futures Prices: Cointegration, Linear and Nonlinear Causality. Energy Economics, 30(5), 2673-2685.

  • Chauhan, A. K., & Singh, S. A. (2013). Market Efficiency and Volatility Spillovers in Futures and Spot Commodity Market: The Agricultural Sector Perspective. Samvad, VI(2), 61-84.

  • Chen, A., & Lin, J. (2004). Cointegration and detectable linear and nonlinear causality: analysis using London Metal Exchange lead contract. Applied Economics, 36, 1157-1167.

  • Chhajed, I., & Mehta, S. (2013). Market Behavior and Price Discovery in Indian Agriculture Commodity Market. International Journal of Scientific and Research Publications, 3(3), 1-4.

  • Choksi, S. (1984). Spot and Futures Prices in Copper: The Speculative Link. Journal of Post Keynesian Economics, 6(3), 433-448.

  • Chopra, A., & Bessler, D. (2005). Price Discovery in the Black Pepper Market in Kerala, India. Indian Economic Review, New Series, 40(1), 1-21.

  • Choudhary, K., & Bajaj, S. (2012). Intraday Lead/Lag Relationships between the Futures and Spot Market. Eurasian Journal of Business and Economics, 5(9), 165-186.

  • Dash, M., & Andrews, S. (2010). A study on market behaviour and price discovery in indian commodity markets. pp. 1-11.Retrieved from http://ssrn.com/abstract=1722770

  • Edwards. (1988). Futures Trading and Cash Market Volatility: Stock Index and Interest Rate Futures. Journal of Futures Markets, 8(4), 421-440.

  • Engle, R., & Granger, C. (1987). Co-Integration and Error Correction: Representation, Estimation and Testing. Econometrica 55, 251-276.

  • Figuerola-Ferretti, I., & Gonzelo, J. (2010). Modelling and measuring price discovery in commodity markets. Journal of Econometrics, 158, 95-107.

  • Forward Markets Commission. (2013). Annual Report 2012-13. Forward Markets Commission.

  • Garbade, K., & Silber, W. (1983). Price Movements and Price Discovery in Futures and Cash Markets. The Review of Economics and Statistics, 65(2), 289-297.

  • Iyer, V., & Pillai, A. (2010). Price Discovery and Convergence in the Indian Commodities Market. Indian Growth and Development Review, 3(1), 53 - 61.

  • Jackline, S., & Deo, M. (2011). Lead - lag relationship between the futures and spot prices. Journal of Economics and International Finance, 3(7), 424 - 427.

  • Johansen. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59, 1551-1580.

  • Johansen, S. (1995). Likelihood-based Inference in Cointegrated Vector Autoregressive Models.Oxford: Oxford University Press.

  • Kumar, V., Parvadavardini, S., & Dharani, M. (2013). Relationship between Futures and Spot Market for Selected Spices in India. Prajnan, 41(3), 219-232.

  • Lokare, S. (2007). Commodity Derivatives and Price Risk Management: An Empirical Anecdote from India. Reserve Bank of India Occasional Papers, 28(2), 28-77.

  • Multi Commodity Exchange of India. (2014). Aluminium. Retrieved October 11, 2014, from Multi Commodity Exchange of India: http://www.mcxindia.com/SitePages/Con- tractSpecification.aspx?Pro ductCo de=ALUMINIUM

  • Multi Commodity Exchange of India. (2014). Nickel. Retrieved October 11, 2014, from Multi Commodity Exchange of India: http://www.mcxindia.com/SitePages/Con- tractSpecification.aspx?ProductCode=NICKEL

  • Naik, G., & Jain, S. (2002). Indian Agricultural Commodity Futures Markets: A Performance Survey. Economic and Political Weekly, 37(30).

  • Nappi, C. (n.d.). The Global Aluminium Industry 40 years from 1972. Retrieved from www.thealuminiumstory.com.

  • Ng, V. K., & S., P. (1994). Fundamentals and Volatility: Storage, Spreads, and the Dynamics of Metals Prices. The Journal of Business, 67(2), 203-230.

  • Pugazhenthy, L. (2013). Lead & Zinc Industry in India : An Overview. Metalworld, 42-43.

  • Purohit, H., Chhatwal, H., & Puri, H. (2012). An empirical investigation into causal relationship between spot and future prices of crude oil. International Journal of Research in Commerce, Economics and Management. Technical Trading Strategy in Spot and Future Markets: Arbitrage Signaling. Capital Market Research Institute, The Stock Exchange of Thailand, Working Paper 6/2013.


Abstract Views: 439

PDF Views: 146




  • Empirical Study on Price Discovery Role in Non-Precious Metals Market in India

Abstract Views: 439  |  PDF Views: 146

Authors

Harsh Purohit
WISDOM, State Bank of India School of Commerce and Banking, Banasthali University, India
Shernaz Bodhanwala
FLAME University, Pune, India
Nidhi Choudhary
WISDOM, State Bank of India School of Commerce and Banking, Banasthali University, India

Abstract


Demand for most industrial metals signifies the pick-up in the level of economic activity in the country. Industrial metals saw asubstantial increase in trading interest on Multi Commodity Exchange, which raises the need to analyse the market efficiency and the relationship between spot and futures market.Statistical tools like ADF, Johansen Co-integration Test and Vector Error Correction Model (VECM) are applied to see the lead lag relationship between spot and future market of various industrial metals like Copper, Aluminium, Nickel, Lead and Zinc. Empirical results prove bidirectional causality and Spot market adjusts at a faster pace to restore long-run equilibrium in most of the industrial metals.

Keywords


Future Price, Johansen Co-Integration Test, Metals, Spot Price, Vecm Granger Causality Test.

References