Investigation the Reciprocal Effects of Saffron warehouse Receipt and Saffron Future Contracts in Iran Mercantile Exchange (IME)
Subject Areas : Agricultural Economics ResearchSEYED MEYSAM JALILI 1 , AKBAR MIRZAPOUR BABAJAN 2 , Beitollah Akbari Moghadam 3 , Arash Hadizade Miyarkolaee 4
1 - Accounting & Management , Qazvin Islamic Azad University, Qazvin, Iran
2 - Assistant Proffesor, Faculties Accounting & Management , Qazvin Islamic Azad University, Qazvin, Iran.
3 - Assistant Proffesor, Faculties Accounting & Management , Qazvin Islamic Azad University, Qazvin, Iran.
4 - Assistant Proffesor, Faculties Accounting & Management , Qazvin Islamic Azad University, Qazvin, Iran.
Keywords: Neural network, price fluctuations, non-linear granger causality, warehouse receipt, Futures,
Abstract :
Introduction: The Present article examines factors that have effect on saffron warehouse receipt and on saffron futures in Iran commodity exchange. This study tries to identify the import of saffron future price and the two-way communication between these two financial instruments (saffron warehouse receipt and saffron futures) to saffron market.
Materials and Methods: In this regard, this study seeks to answer the existence of the relationship between linear and non-linear causality between these two financial instruments. The data were obtained daily in the period from June 2018 to July 2019 using price fluctuations in saffron warehouse receipt and saffron futures. Descriptive – analytical research methods and library data collection methods, regression models and the concept of neural networks with the help of Eviews software and R Economic Statistical Software were used. The price fluctuations of saffron warehouse receipt have been extracted using Arch family models.
Findings: Results indicate that there is a two linear causality relationship between warehouse receipt’s price fluctuation and future’s price fluctuation. To investigate the existence of non-linear causality between the two under studied, variables VAR model residual was used. The BDS test result show the existence of a non-linear relationship between the mentioned variables. The results of the non-linear granger causality test based on neural network show that futures price are the cause for price fluctuations in saffron warehouse receipt.
Conclusion: It can be stated that price discovery is formed in saffron future market and saffron warehouse receipt market follows the futures market.
1- Fabozzi F, Neave E, Guofu Z. Ttranslated by: Taleblou R, Oryani B. 2015, Financial Economics.
2- Iran Mercantile Exchange. The World's Commodity Exchanges Past-Present-Future, a Joint Publication of: United Nations Conference on Trade and Development Swiss Futures and Options Association.2003.
3- Soltaninejad H, Naserpour A, Fallah J, Naru M. Supportive Agriculture Sector Policies Focusing on Market-Based Approaches through Commodity Exchanges. Second edition. Tehran: Exchange Publications. 2016; p. 272.
4- Gupta A, Varma P. Impact of Futures Trading on Spot Markets: An Empirical Analysis of Rubber in India, Eastern Economic Journal, 2016, 42, (373–386).
5- Banerjee, S, Graveline, J. Trading in derivatives when the underlying is scarce, 2014, Elsevier, Journal of Financial Economics 111, 589–608.
6- Broock, W. A., Scheinkman, J. A., Dechert, W. D., and LeBaron, B. 1996. “A Test for Independence Based on the Correlation Dimension.” Journals in Its Journal Econometric Reviews 15 (3): 197-235.
7- BAL DP, Rath BN. Nonlinear Causality between Crude Oil Price and Exchange Rate: A Comparative Study of China and India, 2015, Energy Economics, 2015, 51, 149-156.
8- Ahmad W, Sehgal S. The investigation of destabilization effect in India’s Agriculture commodity futures market an alternative viewpoint, Emerald, Journal of Financial Economic Policy.2015.
9- Huchet N, Gueye FAM P. The role of speculation in international futures markets on commodity prices, science direct, Research in International Business and Finance. 2015.
10- Geman H, Smith W. Theory of storage, inventory and volatility in the LME base metals, Elsevier, Resources Policy, 2013, 38, 18–28.
11- Tank A, Ian C, Nicholas J, Emily B, Shojaie A. Neural Granger Causality for Nonlinear Time Series, University of Washington, www. researchgate.net
12- Hernandez M, Torero M. Examining the Dynamic Relationship between Spot and Future Prices of Agricultural Commodities, ResearchGate. 2010.
13- Yang J, Balyeat R, Leatham D. Futures trading activity and commodity cash Price volatility. Financ. Account. 2005, 32, 297–323.
14- Ibbotson Associates, Strategic asset allocation and commodities. 2006. Availableat:http://www.pimco.com/leftNav/Viewpoints/2006/Ibboston+Commod ity+Study.htm.
15- UNCTAD. Development Impacts of Commodity Exchanges in Emerging Markets. 2009.
16- Hmamouche Y. NlinTS: Models for non Linear Causality Detection in time series. URL https: //CRAN.R-project.org/package=NlinTS. R package version, 2020, 1.4.2. [p].
17- Hazell P. the future of small farms for poverty reduction and growth. 2007, IFPRI 2020 discussion paper 42.May2007
18- Agricultural Statistics. Iran’s Minister of Agriculture, Department of Planning and Economy. 2018, http://www.maj.ir/. History and Importance of Saffron.
19- Dinesh Kumar S, Meenakshi M. Impact of futures trading on volatility of spot market-a case of guar seed, Agricultural Finance Review, 2015, 75(3), 3, 416-431
20- Ghodrati l. Estimation of the demand function of Iranian saffron exports to selected countries using panel data (for the period 2001-2008)
21- Bisaglia L, Gerolimetto M. Testing for (none) linearity in economic time series: A Montecarlo comparison. Quaderni 21 Di Statistica, 2014, 16(16), 5-32.
22- Iran Mercantile Exchange, 2020, www. https://www.ime.co.ir/
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