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Testing Efficiency Of The Copper Futures Market: New Evidence From London Metal Exchange

Author

Listed:
  • Dimitris Kenourgios

    (Athens University of economics & Business)

  • Aristeidis Samitas

    (University of Aegean)

Abstract

This paper investigates the joint hypothesis of market efficiency and unbiasedness of futures prices for the copper futures contract traded on the London Metal Exchange. This contract is of particular importance given the usage and properties of the underlying commodity and its highest share of trading during the last decade, in an exchange which is the centre of the world’s trading in copper. The data contain prices from two different copper futures contracts (three and fifteen months maturity) covering the decade of 1990s, a very volatile and turbulent period for the copper market worldwide. Unlike previous studies, it tests for both long-run and short-run efficiency using cointegration and error correction model. Our results show that the market is not efficient and do not provide unbiased estimates of future copper spot prices, which has important implications for the users of this market.

Suggested Citation

  • Dimitris Kenourgios & Aristeidis Samitas, 2005. "Testing Efficiency Of The Copper Futures Market: New Evidence From London Metal Exchange," Finance 0512010, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0512010
    Note: Type of Document - pdf; pages: 18
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/fin/papers/0512/0512010.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Copper Futures Market; Market Efficiency; Unbiasedness Hypothesis; London Metal Exchange;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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