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Detecting Forecast Power in Gold Coin Futures Contracts in Iran

Baghernejad, Amir | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53381 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Barakchian, Mahdi
  7. Abstract:
  8. One function of futures markets is to signal about future spot prices. This role is accommodated by creating a way for future tradings. In futures markets, different types of investors, including speculators, arbitrators, and hedgers, trade based on their expectations of the future. The better the agents are in pricing, the more significant this role of financial markets. Therefore, it is possible that futures prices contain information that helps to predict maturity spot prices. This study examines the performance of using gold coin futures prices in forecasting with the help of data from December 2008 to July 2016. Studying the cointegration relationships between futures and maturity prices shows that there is a significant and almost one-to-one co-movement between these variables in the horizons of less than 100 working days. Hence, futures prices in these horizons contain information on maturity prices. This study considers two forecasting models that use futures prices in forecasting. The first model uses the futures price itself, and the second model uses its linear transformation. The coefficients of this transformation are determined by regressing maturity prices on futures prices. Forecasts obtained from these models are compared with the models of random walk, autoregressive, moving average, and ARMA using root mean squared percentage error and the fixed-b asymptotic version of the Diebold-Mariano test. Comparison of futures forecasts with benchmark models shows that in the short term, futures performance is better, and this advantage decreases with horizons, but still predicts as well as the other models. The Linear transformation of futures prices with rolling windows performed relatively better in the horizons above 100 days and weaker in the horizons less than 100 days. The Linear transformation of futures prices with expanding windows performed weaker in all horizons than the benchmarks. Comparison of futures prices with the average of benchmark models shows that their performance is very close to each other in almost all horizons. Therefore, it seems that agents in the futures market make use of past information in spot prices well
  9. Keywords:
  10. Forecasting ; Future Contract ; Contegratio ; Error Correction ; Gold Coin Futures Contract ; Gold Coin Futures Market ; Diebold-Mariano Test ; Autoregressive-Moving Average Models

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