×

High frequency market microstructure noise estimates and liquidity measures. (English) Zbl 1160.62089

Summary: Using recent advances in the econometrics literature, we disentangle from high frequency observations on the transaction prices of a large sample of NYSE stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to observable characteristics of the underlying stocks and, in particular, to different financial measures of their liquidity. We find that more liquid stocks based on financial characteristics have lower noise and noise-to-signal ratio measured from their high frequency returns. We then examine whether there exists a common, market-wide, factor in high frequency stock-level measurements of noise, and whether that factor is priced in asset returns.

MSC:

62P05 Applications of statistics to actuarial sciences and financial mathematics
91B28 Finance etc. (MSC2000)
91B24 Microeconomic theory (price theory and economic markets)
62G05 Nonparametric estimation

References:

[1] Aït-Sahalia, Y. and Kimmel, R. (2007). Maximum likelihood estimation of stochastic volatility models. Journal of Financial Economics 83 413-452.
[2] Aït-Sahalia, Y., Mykland, P. A. and Zhang, L. (2005a). How often to sample a continuous-time process in the presence of market microstructure noise. Review of Financial Studies 18 351-416.
[3] Aït-Sahalia, Y., Mykland, P. A. and Zhang, L. (2005b). Ultra high frequency volatility estimation with dependent microstructure noise. Discussion paper, Princeton Univ. · Zbl 1441.62577
[4] Aït-Sahalia, Y., Mykland, P. A. and Zhang, L. (2006). Comments on “Realized variance and market microstructure noise.” J. Bus. Econom. Statist. 24 162-167.
[5] Aït-Sahalia, Y. and Yu, J. (2009). Supplement to “High frequency market microstructure noise estimates and liquidity measures.” DOI: 10.1214/08-AOAS200SUPP. · Zbl 1160.62089
[6] Amihud, Y., Mendelson, H. and Pedersen, L. H. (2005). Liquidity and asset prices. Foundations and Trends in Finance 1 269-364. · Zbl 1140.91006
[7] Andersen, T. G., Bollerslev, T., Diebold, F. X. and Labys, P. (2001). The distribution of exchange rate realized volatility. J. Amer. Statist. Assoc. 96 42-55. · Zbl 1015.62107 · doi:10.1198/016214501750332965
[8] Ang, A., Hodrick, R. J., Xing, Y. and Zhang, X. (2006). The cross-section of volatility and expected returns. Journal of Finance 51 259-299.
[9] Bandi, F. M. and Russell, J. R. (2003). Microstructure noise, realized volatility and optimal sampling. Discussion paper, Univ. Chicago Graduate School of Business. · Zbl 1138.91394
[10] Barndorff-Nielsen, O. E. and Shephard, N. (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. J. Roy. Statist. Soc. Ser. B 64 253-280. · Zbl 1059.62107 · doi:10.1111/1467-9868.00336
[11] Brennan, M. J. and Subrahmanyam, A. (2002). Market microstructure and asset pricing: On the compensation for illiquidity in stock returns. Journal of Financial Economics 41 441-464.
[12] Cao, C., Choe, H. and Hatheway, F. (1997). Does the specialist matter? Differential execution costs and intersecurity subsidization on the New York stock exchange. Journal of Finance 52 1615-1640.
[13] Chan, L. and Lakonishok, J. (1997). Institutional equity trading costs: NYSE versus Nasdaq. Journal of Finance 52 713-735.
[14] Chordia, T., Roll, R. and Subrahmanyam, A. (2000). Commonality in liquidity. Journal of Financial Economics 56 3-28.
[15] Chordia, T., Roll, R. and Subrahmanyam, A. (2001). Market liquidity and trading activity. Journal of Finance 56 501-530.
[16] Delattre, S. and Jacod, J. (1997). A central limit theorem for normalized functions of the increments of a diffusion process, in the presence of round-off errors. Bernoulli 3 1-28. · Zbl 0882.60017 · doi:10.2307/3318650
[17] Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation. Econometrica 50 987-1007. · Zbl 0491.62099 · doi:10.2307/1912773
[18] Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33 3-56. · Zbl 1131.91335 · doi:10.1016/0304-405X(93)90023-5
[19] Fama, E. F. and French, K. R. (1997). Industry costs of equity. Journal of Financial Economics 43 143-193.
[20] Gençay, R., Ballocchi, G., Dacorogna, M., Olsen, R. and Pictet, O. (2002). Real-time trading models and the statistical properties of foreign exchange rates. Internat. Econom. Rev. 43 463-491.
[21] Glosten, L. R. (1987). Components of the bid-ask spread and the statistical properties of transaction prices. Journal of Finance 42 1293-1307. · doi:10.1111/j.1540-6261.1987.tb04367.x
[22] Glosten, L. R. and Harris, L. E. (1988). Estimating the components of the bid/ask spread. Journal of Financial Economics 21 123-142.
[23] Goncalves, S. and Meddahi, N. (2005). Bootstrapping realized volatility. Discussion paper, Univ. Montréal. · Zbl 1160.91397
[24] Gottlieb, G. and Kalay, A. (1985). Implications of the discreteness of observed stock prices. Journal of Finance 40 135-153.
[25] Hansen, P. R. and Lunde, A. (2006). Realized variance and market microstructure noise. J. Bus. Econom. Statist. 24 127-161.
[26] Härdle, W. and Linton, O. (1994). Applied nonparametric methods. In Handbook of Econometrics (R. F. Engle and D. L. McFadden, eds.) 4 2295-2339. Elsevier, Amsterdam.
[27] Harris, L. (1990a). Estimation of stock price variances and serial covariances from discrete observations. Journal of Financial and Quantitative Analysis 25 291-306.
[28] Harris, L. (1990b). Statistical properties of the roll serial covariance bid/ask spread estimator. Journal of Finance 45 579-590.
[29] Hasbrouck, J. (1993). Assessing the quality of a security market: A new approach to transaction-cost measurement. Review of Financial Studies 6 191-212.
[30] Hasbrouck, J. (2005). Trading costs and returns for US equities: Evidence from daily data. Discussion paper, New York Univ.
[31] Hasbrouck, J. and Seppi, D. J. (2001). Common factors in prices, order flows, and liquidity. Journal of Financial Economics 59 383-411.
[32] Huang, R. and Stoll, H. (1996). Dealer versus auction markets: A paired comparison of execution costs on NASDAQ and the NYSE. Journal of Financial Economics 41 313-357.
[33] Huberman, G. and Halka, D. (2001). Systematic liquidity. Journal of Financial Research 24 161-178.
[34] Jacod, J. (1994). Limit of random measures associated with the increments of a Brownian semimartingale. Discussion paper, Univ. Paris-6.
[35] Jacod, J. (1996). La Variation Quadratique du Brownien en Présence d’Erreurs d’Arrondi. Astérisque 236 155-162. · Zbl 0861.60085
[36] Jacod, J. and Protter, P. (1998). Asymptotic error distributions for the Euler method for stochastic differential equations. Ann. Probab. 26 267-307. · Zbl 0937.60060 · doi:10.1214/aop/1022855419
[37] Madhavan, A., Richardson, M. and Roomans, M. (1997). Why do security prices change? Review of Financial Studies 10 1035-1064.
[38] Newey, W. K. and West, K. D. (1987). A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica 55 703-708. · Zbl 0658.62139 · doi:10.2307/1913610
[39] Oomen, R. C. (2006). Properties of realized variance under alternative sampling schemes. J. Bus. Econom. Statist. 24 219-237.
[40] Pastor, L. and Stambaugh, R. F. (2003). Liquidity risk and expected stock returns. Journal of Political Economy 111 642-685.
[41] Roll, R. (1984). A simple model of the implicit bid-ask spread in an efficient market. Journal of Finance 39 1127-1139.
[42] Zhang, L. (2006). Efficient estimation of stochastic volatility using noisy observations: A multi-scale approach. Bernoulli 12 1019-1043. · Zbl 1117.62119 · doi:10.3150/bj/1165269149
[43] Zhang, L., Mykland, P. A. and Y. Aït-Sahalia (2005a). Edgeworth expansions for realized volatility and related estimators. Discussion paper, Princeton Univ. · Zbl 1441.62912
[44] Zhang, L., Mykland, P. A. and Y. Aït-Sahalia (2005b). A tale of two time scales: Determining integrated volatility with noisy high-frequency data. J. Amer. Statist. Assoc. 100 1394-1411. · Zbl 1117.62461 · doi:10.1198/016214505000000169
[45] Zhou, B. (1996). High-frequency data and volatility in foreign-exchange rates. J. Bus. & Econom. Statist. 14 45-52.
[46] Zumbach, G., Corsi, F. and Trapletti, A. (2002). Efficient estimation of volatility using high frequency data. Discussion paper, Olsen & Associates.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.