Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues

Langedijk, Sven and Monokroussos, George and Papanagiotou, Evangelia (2015): Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues.

Abstract

We revisit a central task of the extant liquidity literature, which is to identify effective measures of liquidity. We critically assess the influential practice of identifying the best liquidity measures based on monthly correlations by comparing and contrasting correlations between monthly and daily averages of high-frequency benchmarks and low-frequency proxies of liquidity, as well as by examining the coherences between such measures. Furthermore, we propose MIDAS regressions as a way of investigating the bilateral relationships between benchmarks and proxies without averaging out potentially valuable high-frequency information, as is common practice. We conclude that the empirical correlations between benchmarks and proxies in general become weaker as the frequency over which these relationships are examined becomes higher, and that standard practices may lead to misleading conclusions. One implication of our results is that any liquidity measure needs to be assessed against the relevant timeframe for conversion into cash.

• Item Type: MPRA Paper
• Language: English
• Keywords: Liquidity; Market Microstructure; High-Frequency Data; Sovereign Bonds; MIDAS; Coherence.
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C58 - Financial Econometrics; G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing ; Trading Volume ; Bond Interest Rates; G - Financial Economics > G2 - Financial Institutions and Services > G28 - Government Policy and Regulation

References

Aitken, M. and C. Comerton-Forde, 2003. “How should liquidity be measured?” Pacific-Basin Finance Journal 11 (1): 45–59.

Amihud, Y., 2002. “Illiquidity and stock returns: cross-section and time-series effects.” Journal of Financial Markets 5 (1): 31–56.

Andreou, Ghysels, and Kourtellos, 2010. “Regression models with mixed sampling frequencies,” Journal of Econometrics, 158, 246-261.

Basel Committee on Banking Supervision, 2013. “The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools.” http://www.bis.org/publ/bcbs238.htm.

Beber, A., M. Brandt, and K. Kavajecz, 2009. “Flight-to-Quality or Flight-to-Liquidity? Evidence from the Euro-Area Bond Market.” Review of Financial Studies 22 (3): 925–957.

Dobrev and Szerzen, 2010. “The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk,” Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 1005, September 2010.

Dunne, P., M. Moore, and R. Portes, 2006. “European government bond markets: Transparency, liquidity, efficiency.” Centre for European Policy Research, May 2006. http://qcite.qub.ac.uk/handle/123456789/12811.

Earne J. and L. Sherk, 2013. “Funding.” The New Microfinance Handbook: A Financial Market System Perspective, J. Ledgerwood, with J. Earne and C. Nelson (eds.), Chapter 16.

European Banking Authority (2013a). “Report on Impact Assessment for Liquidity Measures under Article 509 (1) of the CRR,” December 20.

European Banking Authority, (2013b), “Report on appropriate uniform definitions of extremely high quality liquid assets (extremely HQLA) and high quality liquid assets (HQLA) and on operational requirements for liquid assets under Article 509(3) and (5) CRR,” European Banking Authority Report, December 2013 (http://www.eba.europa.eu/documents/10180/16145/EBA+BS+2013+413+Report+on+definition+of+HQLA.pdf).

Fong, K., C. Holden, and C. Trzcinka, 2011. “What Are The Best Liquidity Proxies For Global Research?” http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1558447.

Galliani, C., G. Petrella and A. Resti, 2013. “The liquidity of European corporate and government bonds: drivers and sensitivity to different market conditions,” http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/32394/1/lbna26498enn.pdf

Ghysels, Santa-Clara and Valkanov, 2004. “The MIDAS touch: mixed data sampling regression models,” Discussion Paper, University of North Carolina at Chapel Hill and UCLA.

Goyenko, R., C Holden, and C. Trzcinka, 2009. “Do liquidity measures measure liquidity?” Journal of Financial Economics 92 (2): 153–181.

Hamilton, James D., 1994: Time Series Analysis, Princeton University Press, Princeton.

Holden, C., 2009. “New low-frequency spread measures.” Journal of Financial Markets 12 (4): 778–813.

Hollo, D., M. Kremer and M. Lo Duca, 2012. "CISS - A Composite Indicator of Systemic Stress in the Financial System,” ECB Working Paper No. 1426, March. 27

De Jong, F. and J. Driessen, 2012. “Liquidity risk premia in corporate bond markets.” The Quarterly Journal of Finance 2 (02). http://www.worldscientific.com/doi/pdf/10.1142/S2010139212500061.

Korajczyk and Sadka, 2007. “Pricing the commonality across alternative measures of liquidity,” mimeo. http://dx.doi.org/10.2139/ssrn.900363.

Lesmond, D. and C. Trzcinka, 1999. “A New Estimate of Transaction Costs.” Review of Financial Studies. doi:10.1093/rfs/12.5.1113. http://dx.doi.org/10.1093/rfs/12.5.1113.

Pelizzon, L., M.G. Subrahmanyam, D. Tomio and J. Uno. 2013. “The Microstructure of the European Sovereign Bond Market: A Study of the Euro-zone Crisis,” mimeo, Copenhagen Business School.

Roll, R., 1984. “A simple implicit measure of the effective bid-ask spread in an efficient market.” Journal of Finance: 1127–1139.

Schestag, R, P. Schuster, and M. Uhrig-Homburg, 2013. “Measuring Liquidity in Bond Markets”, http://dx.doi.org/10.2139/ssrn.2328370