Measuring Transaction Costs in the Absence of Timestamps
Author
Abstract
Suggested Citation
DOI: 10.17016/FEDS.2017.045
Download full text from publisher
References listed on IDEAS
- Benos, Evangelos & Wetherilt, Anne & Zikes, Filip, 2013. "Financial Stability Paper No 25: The structure and dynamics of the UK CDS market," Bank of England Financial Stability Papers 25, Bank of England.
- Kim Christensen & Mark Podolskij & Mathias Vetter, 2009.
"Bias-correcting the realized range-based variance in the presence of market microstructure noise,"
Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
- Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2006. "Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise," Technical Reports 2006,52, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
- Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
- Ole E. Barndorff‐Nielsen & Neil Shephard, 2002.
"Econometric analysis of realized volatility and its use in estimating stochastic volatility models,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
- Ole E. Barndorff-Nielsen & Neil Shephard, 2000. "Econometric analysis of realised volatility and its use in estimating stochastic volatility models," Economics Papers 2001-W4, Economics Group, Nuffield College, University of Oxford, revised 05 Jul 2001.
- Neil Shephard & Ole E. Barndorff-Nielsen & University of Aarhus, 2001. "Econometric Analysis of Realised Volatility and Its Use in Estimating Stochastic Volatility Models," Economics Series Working Papers 71, University of Oxford, Department of Economics.
- Yacine Aït-Sahalia & Jean Jacod, 2014. "High-Frequency Financial Econometrics," Economics Books, Princeton University Press, edition 1, number 10261.
- Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
- Michael W. Brandt & Francis X. Diebold, 2006.
"A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations,"
The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
- Michael W. Brandt & Francis X. Diebold & April, "undated". "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," Center for Financial Institutions Working Papers 03-15, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Michael W. Brandt & Francis X. Diebold, 2003. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," NBER Working Papers 9664, National Bureau of Economic Research, Inc.
- Michael W. Brandt & Francis X. Diebold, 2001. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," PIER Working Paper Archive 03-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Apr 2003.
- Brandt, Michael W. & Diebold, Francis X., 2004. "A no-arbitrage approach to range-based estimation of return covariances and correlations," CFS Working Paper Series 2004/07, Center for Financial Studies (CFS).
- Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
- Benos, Evangelos & Payne, Richard & Vasios, Michalis, 2020.
"Centralized Trading, Transparency, and Interest Rate Swap Market Liquidity: Evidence from the Implementation of the Dodd–Frank Act,"
Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(1), pages 159-192, February.
- Benos, Evangelos & Payne, Richard & Vasios, Michalis, 2016. "Centralized trading, transparency and interest rate swap market liquidity: evidence from the implementation of the Dodd-Frank Act," Bank of England working papers 580, Bank of England.
- Madhavan, Ananth & Richardson, Matthew & Roomans, Mark, 1997.
"Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks,"
The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 1035-1064.
- Ananth Madhavan & Matthew Richardson & Mark Roomans, "undated". "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," Rodney L. White Center for Financial Research Working Papers 20-94, Wharton School Rodney L. White Center for Financial Research.
- Ananth Madhavan & Matthew Richardson & Mark Roomans, 1996. "Why Do Security Prices Change? A Transaction-Level Analysis of NYSE Stocks," New York University, Leonard N. Stern School Finance Department Working Paper Seires 96-34, New York University, Leonard N. Stern School of Business-.
- Paul Schultz, 2001. "Corporate Bond Trading Costs: A Peek Behind the Curtain," Journal of Finance, American Finance Association, vol. 56(2), pages 677-698, April.
- Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
- Amy K. Edwards & Lawrence E. Harris & Michael S. Piwowar, 2007. "Corporate Bond Market Transaction Costs and Transparency," Journal of Finance, American Finance Association, vol. 62(3), pages 1421-1451, June.
- Foucault, Thierry & Pagano, Marco & Roell, Ailsa, 2013.
"Market Liquidity: Theory, Evidence, and Policy,"
OUP Catalogue,
Oxford University Press, number 9780199936243.
- Thierry Foucault & Marco Pagano & Ailsa Röell, 2013. "Market Liquidity: Theory, Evidence and Policy," Post-Print hal-00793694, HAL.
- Bessembinder, Hendrik & Maxwell, William & Venkataraman, Kumar, 2006. "Market transparency, liquidity externalities, and institutional trading costs in corporate bonds," Journal of Financial Economics, Elsevier, vol. 82(2), pages 251-288, November.
- Bessembinder, Hendrik, 2003. "Issues in assessing trade execution costs," Journal of Financial Markets, Elsevier, vol. 6(3), pages 233-257, May.
- Jankowitsch, Rainer & Nashikkar, Amrut & Subrahmanyam, Marti G., 2011. "Price dispersion in OTC markets: A new measure of liquidity," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 343-357, February.
- Benos, Evangelos & Zikes, Filip, 2016. "Liquidity determinants in the UK gilt market," Bank of England working papers 600, Bank of England.
- Liudas Giraitis & George Kapetanios & Anne Wetherilt & Filip ŽIKEŠ, 2016. "Estimating the Dynamics and Persistence of Financial Networks, with an Application to the Sterling Money Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 58-84, January.
- Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
- Michael J. Fleming & John Jackson & Ada Li & Asani Sarkar & Patricia Zobel, 2012. "An analysis of OTC interest rate derivatives transactions: implications for public reporting," Staff Reports 557, Federal Reserve Bank of New York.
- Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
- Goyenko, Ruslan Y. & Holden, Craig W. & Trzcinka, Charles A., 2009. "Do liquidity measures measure liquidity?," Journal of Financial Economics, Elsevier, vol. 92(2), pages 153-181, May.
- Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
- Chen, Xiaohong & Linton, Oliver & Schneeberger, Stefan & Yi, Yanping, 2019. "Semiparametric estimation of the bid–ask spread in extended roll models," Journal of Econometrics, Elsevier, vol. 208(1), pages 160-178.
- Joseph, Andreas & Vasios, Michalis & Maizels, Olga & Shreyas, Ujwal & Tanner, John, 2019. "OTC microstructure in a period of stress: a multi‑layered network approach," Bank of England working papers 832, Bank of England.
- Henning Fischer & Ángela Blanco‐FERNÁndez & Peter Winker, 2016. "Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(2), pages 113-146, March.
- Joseph, Andreas & Vasios, Michalis, 2022. "OTC Microstructure in a period of stress: A Multi-layered network approach," Journal of Banking & Finance, Elsevier, vol. 138(C).
- Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015.
"Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes,"
Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
- Kevin Sheppard & Lily Liu & Andrew J. Patton, 2013. "Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes," Economics Series Working Papers 645, University of Oxford, Department of Economics.
- Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
- Gao, Yang & Li, Yunhai & Wang, Yaojun & Wang, Chao & Liu, Chao, 2019. "Asymptotic comparison of three spread estimators based on Roll’s model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 420-432.
- Robert Ślepaczuk & Grzegorz Zakrzewski, 2009. "High-Frequency and Model-Free Volatility Estimators," Working Papers 2009-13, Faculty of Economic Sciences, University of Warsaw.
- Benos, Evangelos & Žikeš, Filip, 2018. "Funding constraints and liquidity in two-tiered OTC markets," Journal of Financial Markets, Elsevier, vol. 39(C), pages 24-43.
- Yaming Chang, 2025. "Improving volatility forecasts of the Nikkei 225 stock index using a realized EGARCH model with realized and realized range-based volatilities," Papers 2502.02695, arXiv.org, revised Feb 2025.
- Díaz, Antonio & Escribano, Ana, 2020. "Measuring the multi-faceted dimension of liquidity in financial markets: A literature review," Research in International Business and Finance, Elsevier, vol. 51(C).
- Han, Song & Huang, Alan Guoming & Kalimipalli, Madhu & Wang, Ke, 2022. "Information and liquidity of over-the-counter securities: Evidence from public registration of Rule 144A bonds," Journal of Financial Markets, Elsevier, vol. 59(PB).
- Xu, Yanyan & Huang, Dengshi & Ma, Feng & Qiao, Gaoxiu, 2019. "Liquidity and realized range-based volatility forecasting: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1102-1113.
- Bannouh, Karim & Martens, Martin & van Dijk, Dick, 2013.
"Forecasting volatility with the realized range in the presence of noise and non-trading,"
The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 535-551.
- Bannouh, K. & Martens, M.P.E. & van Dijk, D.J.C., 2012. "Forecasting Volatility with the Realized Range in the Presence of Noise and Non-Trading," ERIM Report Series Research in Management ERS-2012-018-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
- Kim Christensen & Mark Podolskij & Mathias Vetter, 2009.
"Bias-correcting the realized range-based variance in the presence of market microstructure noise,"
Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
- Christensen, Kim & Podolskij, Mark & Vetter, Mathias, 2006. "Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise," Technical Reports 2006,52, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Liao, Yin & Anderson, Heather M., 2019.
"Testing for cojumps in high-frequency financial data: An approach based on first-high-low-last prices,"
Journal of Banking & Finance, Elsevier, vol. 99(C), pages 252-274.
- Yin Liao & Heather M. Anderson, 2011. "Testing for co-jumps in high-frequency financial data: an approach based on first-high-low-last prices," Monash Econometrics and Business Statistics Working Papers 9/11, Monash University, Department of Econometrics and Business Statistics.
- Goldstein, Michael A. & Namin, Elmira Shekari, 2023. "Corporate bond liquidity and yield spreads: A review," Research in International Business and Finance, Elsevier, vol. 65(C).
- Torben G. Andersen & Luca Benzoni, 2008. "Realized volatility," Working Paper Series WP-08-14, Federal Reserve Bank of Chicago.
- Olga Cielinska & Andreas Joseph & Ujwal Shreyas & John Tanner & Michalis Vasios, 2017.
"Gauging market dynamics using trade repository data: The case of the Swiss franc de-pegging,"
IFC Bulletins chapters, in: Bank for International Settlements (ed.), Statistical implications of the new financial landscape, volume 43,
Bank for International Settlements.
- Cielinska, Olga & Joseph, Andreas & Shreyas, Ujwal & Tanner, John & Vasios, Michalis, 2017. "Gauging market dynamics using trade repository data: the case of the Swiss franc de-pegging," Bank of England Financial Stability Papers 41, Bank of England.
More about this item
Keywords
Effective spread; Simulated method of moments; Time-varying estimation; Transaction costs;All these keywords.
JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- G20 - Financial Economics - - Financial Institutions and Services - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-MST-2017-04-23 (Market Microstructure)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedgfe:2017-45. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ryan Wolfslayer ; Keisha Fournillier (email available below). General contact details of provider: https://edirc.repec.org/data/frbgvus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.