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Price informativeness and predictability: how liquidity can help

Author

Listed:
  • William Lin
  • Shih-Chuan Tsai
  • David Sun
Abstract
Information asymmetry and liquidity concentration has been widely discussed in literatures. This study shows how liquidity influences not only forecasting performances of term structure estimation, but also information transmission and price adjustment across markets. Our analysis helps understanding how extreme market movements affect one another. This study examines, and provides a rationale for incorporating, liquidity in estimating term structure. Forecasting performance can be greatly enhanced when conditioning on trading liquidity. It reduces information asymmetry in the sense of Easley and O'Hara (2004) and Burlacu et al. (2007). We adopt a time series forecasting model following Diebold and Li (2006) to compare behaviour of forecasted price errors. Our findings indicate that forecasted price errors in markets with less depth would influence those with more. Information asymmetry induces volatile trading first and then price adjustment is transmitted to another market due to insufficient market depth. Cross-market price adjustment could be as much as 21 bps on average. Compared with previous studies, our results establish a valid reason to condition on liquidity when forecasting prices.

Suggested Citation

  • William Lin & Shih-Chuan Tsai & David Sun, 2011. "Price informativeness and predictability: how liquidity can help," Applied Economics, Taylor & Francis Journals, vol. 43(17), pages 2199-2217.
    • Handle: RePEc:taf:applec:v:43:y:2011:i:17:p:2199-2217
    DOI: 10.1080/00036840903153812
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    References listed on IDEAS

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    1. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    2. Kathy Yuan, 2005. "The Liquidity Service Of Benchmark Securities," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 1156-1180, September.
    3. David Goldreich & Bernd Hanke & Purnendu Nath, 2005. "The Price of Future Liquidity: Time-Varying Liquidity in the U.S. Treasury Market," Review of Finance, Springer, vol. 9(1), pages 1-32, March.
    4. Favero, Carlo A. & Sala, Luca & Niu, Linlin, 2007. "Term Structure Forecasting: No-Arbitrage Restrictions vs Large Information Set," CEPR Discussion Papers 6206, C.E.P.R. Discussion Papers.
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    6. William T. Lin & David S. Sun, 2007. "Liquidity-Adjusted Benchmark Yield Curves: A Look at Trading Concentration and Information," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 491-518.
    7. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
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    10. Sarig, Oded & Warga, Arthur, 1989. "Bond Price Data and Bond Market Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(3), pages 367-378, September.
    11. David Goldreich & Bernd Hanke & Purnendu Nath, 2005. "The Price of Future Liquidity: Time-Varying Liquidity in the U.S. Treasury Market," Review of Finance, European Finance Association, vol. 9(1), pages 1-32.
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    More about this item

    JEL classification:

    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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