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Trading volumes and transaction costs in the foreign market - evidence from daily dollar-yen spot data

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  • Hartmann, Philipp

Abstract

A Generalized Method of Moments estimation of the determinants of dollar/yen bid-ask spreads is undertaken. In particular, a long time-series of daily spot foreign exchange trading volumes is used for the first time. In line with standard spread models and volume theories, it can be shown that unpredictable foreign exchange turnover (a measure of the rate of information arrival) increases spreads, while predictable turnover decreases them. Both effects are strongly significant when employing spot turnover instead of proxies like forward turnover as in previous studies (Bessembinder, 1994). The results are also found to be robust when unpredictable Reuters quoting frequency is used as an instrument for unpredictable trading volumes to cope with their endogeneity. Spread estimations with plain (non-decomposed) volumes are rejected as misspecified. Finally, there is evidence for the conditional heteroscedasticity of unpredictable spot foreign exchange volumes.

Suggested Citation

  • Hartmann, Philipp, 1996. "Trading volumes and transaction costs in the foreign market - evidence from daily dollar-yen spot data," LSE Research Online Documents on Economics 119171, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:119171
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    File URL: http://eprints.lse.ac.uk/119171/
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    More about this item

    Keywords

    foreign exchange markets; bid-ask spreads; trading volumes; time-series analysis; generalized method of moments estimation;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • 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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