Price informativeness and predictability: how liquidity can help
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, Fontaine and Jimenez-Garces (2007). We adopt a time series forecasting model following Diebold and Li (2006) to compare behavior 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.
|Date of creation:||25 Feb 2008|
|Date of revision:||18 Oct 2009|
|Publication status:||Published in Applied Economics 43.17(2011): pp. 2199-2217|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Henker, Thomas & Wang, Jian-Xin, 2006. "On the importance of timing specifications in market microstructure research," Journal of Financial Markets, Elsevier, vol. 9(2), pages 162-179, May.
- 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.
- Carlo A. Favero & Linlin Niu & Luca Sala, 2007.
"Term Structure Forecasting: No-arbitrage Restrictions vs. Large Information Set,"
318, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Favero, Carlo A. & Niu, Linlin & Sala, Luca, 2007. "Term Structure Forecasting: No-Arbitrage Restrictions vs Large Information Set," CEPR Discussion Papers 6206, C.E.P.R. Discussion Papers.
- Edwin J. Elton & T. Clifton Green, 1998. "Tax and Liquidity Effects in Pricing Government Bonds," Journal of Finance, American Finance Association, vol. 53(5), pages 1533-1562, October.
- 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.
- Sarig, Oded & Warga, Arthur, 1989. "Bond Price Data and Bond Market Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(03), pages 367-378, September.
- Diaz, Antonio & Merrick, John Jr. & Navarro, Eliseo, 2006. "Spanish Treasury bond market liquidity and volatility pre- and post-European Monetary Union," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1309-1332, April.
- T. Clifton Green, 2004. "Economic News and the Impact of Trading on Bond Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1201-1234, 06.
- Bolder, David & Streliski, David, 1999. "Yield Curve Modelling at the Bank of Canada," Technical Reports 84, Bank of Canada.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:20226. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter)
If references are entirely missing, you can add them using this form.