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A Structural Analysis of Price Discovery Measures

  • Bingcheng Yan

    (Numeric Investors, Boston MA)

  • Eric Zivot

    (University of Washington)

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    We analyze the structural determinants of two widely used measures of price discovery between multiple markets that trade closely-related securities. Using a structural cointegration model, we show that both the information share (IS) and component share (CS) measures account for the relative avoidance of noise trading and liquidity shocks, but that only the IS can provide information on the relative informativeness of individual markets. In particular, the IS of one market is higher if it incorporates more new information and/or impounds less liquidity shocks. Use of the CS in conjunction with the IS can help sort out the confounding effects of the two types of shocks. Furthermore, we find that the IS only accounts for the immediate (one-period) responses of market prices to the news innovation which implies that the IS estimates based on high sampling frequencies may be distorted by transitory frictions and may miss important price discovery dynamics.

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    Paper provided by University of Washington, Department of Economics in its series Working Papers with number UWEC-2006-08-FC.

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    Date of creation: Apr 2007
    Date of revision: Apr 2007
    Publication status: Forthcoming in Journal of Financial Markets
    Handle: RePEc:udb:wpaper:uwec-2006-08-fc
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