Time-varying price discovery in Bahar-e-Azadi Gold Coin spot and futures contracts
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Author(s)Elham FarzaneganLink to ORCID Index: https://orcid.org/0000-0002-3725-3189
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DOIhttp://dx.doi.org/10.21511/imfi.19(3).2022.13
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Article InfoVolume 19 2022, Issue #3, pp. 153-166
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Creative Commons Attribution 4.0 International License
This paper aims to analyze the daily price discovery of Bahar-e-Azadi Gold Coin (GC) spot and futures contracts in Iran, using the fractionally cointegrated error-correction model (FCECM). The residuals of the FCECM are modeled by the BEKK-GARCH specification to calculate the time-varying conditional information share between GC spot and futures prices. Using data covering December 21, 2008 to April 14, 2018, the paper establishes the novel finding that the GC spot and futures price series are fractionally integrated of orders 0.98347 and 0.95169, respectively. This implies the long memory behavior in the price series. Further, the results show that the series are fractionally cointegrated of order 0.542. The empirical findings from the methodology indicate that in the price discovery process, the GC spot market dominates the GC futures market. This analysis is robust to alternative construction of futures price series and sub-samples decomposed based on structural breaks. One possible explanation could be the higher trading volume associated with the GC spot market compared to the GC futures market. Incompleteness and market frictions also can cause a delay in the process of information incorporation into the futures market and may discourage market players from trading in these markets.
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JEL Classification (Paper profile tab)C32, G13
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References69
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Tables9
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Figures3
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- Figure A1. Daily movements of log prices of GC spot and GC futures during the whole sample period
- Figure A2. Monthly average of information share of GC spot (above) and futures (below)
- Figure A3. Time series of information share of GC spot (above) and futures (below)
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- Table 1. Unit root and Johansen cointegration test results
- Table 2. Results of local LW test for order of fractional integration
- Table 3. Results of lag selection for FCECM model
- Table 4. Results of cointegration rank test and fractional cointegration parameter d
- Table 5. Adjustment coefficient matrix
- Table 6. Estimation results of the FCECM model
- Table 7. Results of testing the CVAR model against alternative FCVAR model
- Table 8. Descriptive statistics (Panel A) and static price discovery (Panels B & C) for GC spot and (adjusted) futures price series.
- Table 9. Time-varying price discovery for GC spot and (unadjusted) GC futures price series for the whole sample
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- Al-Shboul, M., & Anwar, S. (2016). Fractional integration in daily stock market indices at Jordan’s Amman stock exchange. The North American Journal of Economics and Finance, 37, 16-37.
- Atilgan, Y., Demirtas, K. O., Gunaydin, A. D., & Oztekin, M. (2022). Price discovery in emerging market ETFs. Applied Economics.
- Avino, D., Lazar, E., & Varotto, S. (2015). Time varying price discovery. Economics Letters, 126, 18-21.
- Aye, G. C., Carcel, H., Gil-Alana, L. A., & Gupta, R. (2017). Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016. Resources Policy, 54, 53-57.
- Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22.
- Baillie, R. T. (1996). Long memory processes and fractional integration in econometrics. Journal of Econometrics, 73(1), 5-59.
- Baillie, R. T., Geoffrey Booth, G., Tse, Y., & Zabotina, T. (2002). Price discovery and common factor models. Journal of Financial Markets, 5(3), 309-321.
- Bekaert, G., Harvey, C. R., & Lumsdaine, R. L. (2002). Dating the integration of world equity markets. Journal of Financial Economics, 65(2), 203-247.
- Black, F. (1976). The pricing of commodity contracts. Journal of Financial Economics, 3(1), 167-179.
- Caporale, G. M., Ciferri, D., & Girardi, A. (2014). Time-varying spot and futures oil price dynamics. Scottish Journal of Political Economy, 61(1), 78-97.
- Cavaliere, G., Nielsen, M. O., & Taylor, A. M. R. (2015). Bootstrap score tests for fractional integration in heteroskedastic ARFIMA models, with an application to price dynamics in commodity spot and futures markets. Journal of Econometrics, 187(2), 557-579.
- Chai, E. F., Lee, A. D., & Wang, J. (2015). Global information distribution in the gold OTC markets. International Review of Financial Analysis, 41, 206-217.
- Chen, W. P., & Chung, H. (2012). Has the introduction of S&P 500 ETF options led to improvements in price discovery of SPDRs? Journal of Futures Markets, 32(7), 683-711.
- Chen, Y. L., & Gau, Y. F. (2010). News announcements and price discovery in foreign exchange spot and futures markets. Journal of Banking & Finance, 34(7), 1628-1636.
- Chinn, M. D., & Coibion, O. (2014). The predictive content of commodity futures. Journal of Futures Markets, 34(7), 607-636.
- Choudhary, K., & Bajaj, S. (2013). Price discovery process in nifty spot and futures markets. Global Business Review, 14(1), 55-88.
- Coakley, J., Dollery, J., & Kellard, N. (2011). Long memory and structural breaks in commodity futures markets. Journal of Futures Markets, 31(11), 1076-1113.
- Ding, D. K., Harris, F. H. D., Lau, S. T., & McInish, T. H. (1999). An investigation of price discovery in informationally-linked markets: equity trading in Malaysia and Singapore. Journal of Multinational Financial Management, 9(3), 317-329.
- Dolatabadi, S., Narayan, P. K., Nielsen, M. Ø., & Xu, K. (2018). Economic significance of commodity return forecasts from the fractionally cointegrated VAR model. Journal of Futures Markets, 38(2), 219-242.
- Dolatabadi, S., Ørregaard, N. M., & Ke, X. (2015). A fractionally cointegrated VAR analysis of price discovery in commodity futures markets. Journal of Futures Markets, 35(4), 339-356.
- Elder, J., Miao, H., & Ramchander, S. (2014). Price discovery in crude oil futures. Energy Economics, 46, S18-S27.
- Fassas, A. P., & Siriopoulos, C. (2019). Intraday price discovery and volatility spillovers in an emerging market. International Review of Economics & Finance, 59, 333-346.
- Figuerola-Ferretti, I., & Gilbert, C. L. (2005). Price discovery in the aluminum market. Journal of Futures Markets, 25(10), 967-988.
- Figuerola-Ferretti, I., & Gonzalo, J. (2010). Modelling and measuring price discovery in commodity markets. Journal of Econometrics, 158(1), 95-107.
- Garbade, K. D., & Silber, W. L. (1983). Price movements and price discovery in futures and cash markets. The Review of Economics and Statistics, 65(2), 289-297.
- Gil-Alana, L. A., Yaya, O. S., & Awe, O. O. (2017). Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach. Resources Policy, 53, 117-124.
- Gonzalo, J., & Granger, C. (1995). Estimation of common long-memory components in cointegrated systems. Journal of Business & Economic Statistics, 13(1), 27-35.
- Gupta, A., & Varma, P. (2016). Impact of futures trading on spot markets: an empirical analysis of rubber in India. Eastern Economic Journal, 42(3), 373-386.
- Hasbrouck, J. (1995). One security, many markets: determining the contributions to price discovery. The Journal of Finance, 50(4), 1175-1199.
- Hasbrouck, J. (2003). Intraday price formation in U.S. equity index markets. The Journal of Finance, 58(6), 2375-2399.
- Hauptfleisch, M., Putniņš, T. J., & Lucey, B. (2016). Who sets the price of gold? London or New York. Journal of Futures Markets, 36(6), 564-586.
- Hou, K., & Moskowitz, T. J. (2005). Market frictions, price delay, and the cross-section of expected returns. The Review of Financial Studies, 18(3), 981-1020.
- Inani, S. K. (2018). Price discovery and efficiency of Indian agricultural commodity futures market: an empirical investigation. Journal of Quantitative Economics, 16(1), 129-154.
- Ivanov, S. I. (2013). The influence of ETFs on the price discovery of gold, silver and oil. Journal of Economics and Finance, 37(3), 453-462.
- Johansen, S. (2008). A Representation theory for a class of vector autoregressive models for fractional processes. Econometric Theory, 24(3), 651-676.
- Johansen, S., & Nielsen, M. Ø. (2010). Likelihood inference for a nonstationary fractional autoregressive model. Journal of Econometrics, 158(1), 51-66.
- Johansen, S., & Nielsen, M. Ø. (2012). Likelihood inference for a fractionally cointegrated vector autoregressive model. Econometrica, 80(6), 2667-2732.
- Karabiyik, H., Narayan, P. K., Phan, D. H. B., & Westerlund, J. (2017). Islamic spot and index futures markets: Where is the price discovery? Pacific-Basin Finance Journal.
- Kuiper, W. E., Pennings, J. M., & Meulenberg, M. T. (2002). Identification by full adjustment: evidence from the relationship between futures and spot prices. European Review of Agricultural Economics, 29(1), 67-84.
- Lehmann, B. N. (2002). Some desiderata for the measurement of price discovery across markets. Journal of Financial Markets, 5(3), 259-276.
- Liu, Q., & An, Y. (2011). Information transmission in informationally linked markets: Evidence from US and Chinese commodity futures markets. Journal of International Money and Finance, 30(5), 778-795.
- Liu, Q., Wong, I., An, Y., & Zhang, J. (2014). Asymmetric information and volatility forecasting in commodity futures markets. Pacific-Basin Finance Journal, 26, 79-97.
- Lucey, B. M., Larkin, C., & O’Connor, F. A. (2013). London or New York: where and when does the gold price originate? Applied Economics Letters, 20(8), 813-817.
- Mahalik, M. K., Debashis, A., & Babu, M. S. (2014). Price discovery and volatility spillovers in futures and spot commodity markets: some Indian evidence. Journal of Advances in Management Research, 11(2), 211-226.
- Malkiel, B. G., & Fama, E. F. (1970). Efficient capital markets: a review of theory and empirical work. The Journal of Finance, 25(2), 383-417.
- Mallika, M., & Sulphey, M. M. (2018). Gold Exchange Traded Fund-Price discovery and performance analysis. Scientific Annals of Economics and Business, 65(4), 477-495.
- Mattos, F., & Garcia, P. (2004). Price discovery in thinly traded markets: Cash and futures relationships in Brazilian agricultural futures markets. Paper presented at the NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. St. Louis, MO.
- McCullough, K., & Strydom, B. (2013). The efficiency of the South African white maize futures market. Agrekon, 52(3), 18-33.
- Merton, R. C. (1987). A simple model of capital market equilibrium with incomplete information. The Journal of Finance, 42(3), 483-510.
- Naik, G., & Jain, S. K. (2002). Indian agricultural commodity futures markets: a performance survey. Economic and Political Weekly, 37(30), 3161-3173.
- Narayan, S., & Smyth, R. (2015). The financial econometrics of price discovery and predictability. International Review of Financial Analysis, 42, 380-393.
- Nielsen, M. Ø., & Popiel, M. K. (2014). A matlab program and user’s guide for the fractionally cointegrated VAR model (Queen’s Economics Department Working Paper No 1330). Ontario, Canada, K7L3N6.
- O’Connor, F. A., Lucey, B. M., Batten, J. A., & Baur, D. G. (2015). The financial economics of gold – A survey. International Review of Financial Analysis, 41, 186-205.
- Pavabutr, P., & Chaihetphon, P. (2010). Price discovery in the Indian gold futures market. Journal of Economics and Finance, 34(4), 455-467.
- Peri, M., Baldi, L., & Vandone, D. (2013). Price discovery in commodity markets. Applied Economics Letters, 20(4), 397-403.
- Pradhan, R. P., Hall, J. H., & Du Toit, E. (2021). The lead–lag relationship between spot and futures prices: Empirical evidence from the Indian commodity market. Resources Policy, 70, 101934.
- Robinson, P. M. (1995). Gaussian semiparametric estimation of long range dependence. The Annals of Statistics, 23(5), 1630-1661.
- Salisu, A. A., & Vo, X. V. (2020). Predicting stock returns in the presence of COVID-19 pandemic: The role of health news. International Review of Financial Analysis, 71, 101546.
- Shleifer, A., & Vishny, R. W. (1997). The limits of arbitrage. The Journal of Finance, 52(1), 35-55.
- Stein, J. L. (1961). The simultaneous determination of spot and futures prices. The American Economic Review, 51(5), 1012-1025.
- Taylor, M. P. (1989). Covered interest arbitrage and market turbulence. The Economic Journal, 99(396), 376-391.
- Theissen, E. (2012). Price discovery in spot and futures markets: a reconsideration. The European Journal of Finance, 18(10), 969-987.
- Tse, Y., & Xiang, J. (2005). Market quality and price discovery: introduction of the E-mini energy futures. Global Finance Journal, 16(2), 164-179.
- Wu, J., Xu, K., Zheng, X., & Chen, J. (2021). Fractional cointegration in bitcoin spot and futures markets. Journal of Futures Markets, 41(9), 1478-1494.
- Xiyu, X. T. C. (2006). The study of dynamic linkages between international and domestic futures market priceand spot price [J]. Journal of Financial Research, 2, 012.
- Yang, J., & Leatham, D. J. (1999). Price discovery in wheat futures markets. Journal of Agricultural and Applied Economics, 31(2), 359-370.
- Yang, J., Bessler, D. A., & Leatham, D. J. (2001). Asset storability and price discovery in commodity futures markets: A new look. Journal of Futures Markets, 21(3), 279-300.
- Zhang, Y. J., & Ma, S. J. (2021). Exploring the dynamic price discovery, risk transfer and spillover among INE, WTI and Brent crude oil futures markets: Evidence from the high-frequency data. International Journal of Finance & Economics, 26(2), 2414-2435.
- Zhang, Y., & Liu, L. (2018). The lead-lag relationships between spot and futures prices of natural gas. Physica A: Statistical Mechanics and its Applications, 490, 203-211.
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