Time-varying price discovery in Bahar-e-Azadi Gold Coin spot and futures contracts

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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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    • 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)
    • 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
    • Conceptualization
      Elham Farzanegan
    • Data curation
      Elham Farzanegan
    • Formal Analysis
      Elham Farzanegan
    • Funding acquisition
      Elham Farzanegan
    • Investigation
      Elham Farzanegan
    • Methodology
      Elham Farzanegan
    • Project administration
      Elham Farzanegan
    • Resources
      Elham Farzanegan
    • Software
      Elham Farzanegan
    • Supervision
      Elham Farzanegan
    • Validation
      Elham Farzanegan
    • Visualization
      Elham Farzanegan
    • Writing – original draft
      Elham Farzanegan
    • Writing – review & editing
      Elham Farzanegan