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2016 | 17 | nr 1 | 77--92
Tytuł artykułu

The Logarithmic ACD Model: the Microstructure of the German and Polish Stock Markets

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The main goal of this paper is to compare the microstructure of selected stocks listed on the Frankfurt and Warsaw Stock Exchanges. We focus on the properties of duration on both markets and on fitting the appropriate ACD models. Because of the quite different levels of capitalization of stocks on these markets, we observe essential discrepancies between these stocks. While for most German companies on the DAX30, the Burr distribution fits better than generalized gamma distribution, the latter distribution is superior in the case of the largest Polish companies. Analyzing series by hazard function, we note the similarity of hazard functions for companies on both markets, which tend to have a U-shaped pattern. (original abstract)
Rocznik
Tom
17
Numer
Strony
77--92
Opis fizyczny
Twórcy
  • AGH University of Science and Technology, Poland
autor
  • Jagiellonian University, Poland
Bibliografia
  • Angel, J., Harris, L. and Spatt, C. (2011) 'Trading the 21st century', Quarterly Journal of Finance, vol. 1 (1), pp. 1-53.
  • Bauwens, L. and Giot, P. (2000) 'The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks', Annales d'Economie et de Statistique, vol. 60, pp. 117-149.
  • Bauwens, L. and Giot, P. (2001) Econometric Modelling of Stock Market Intraday Activity, Dordrecht: Springer Science, Business Media.
  • Bauwens, L. and Veredas, D. (2004) 'The stochastic conditional duration model: a latent variable model for the analysis of financial durations', Journal of Econometrics, vol. 119, pp. 381-412.
  • Biais, B. and Wooley, P. (2011) 'High Frequency Trading', Working Paper, Toulouse University, IDEI.
  • Biais, B., Foucault, T. and Moinas, S. (2015) 'Equilibrium high-frequency trading', Journal of Financial Economics, vol. 116(2), pp. 292-313.
  • Boehmer E., Fong K.Y.L. and Wu J. (2015) 'International evidence on algorithmic trading,' AFA 2013 San Diego Meetings Paper.
  • Brogaard, J., Hendershott, T. and Riordan, R. (2011), 'High Frequency Trading and Price Discovery', Working Paper, [Online], Available: http://ssrn.com/abstract=1928510.
  • Brogaard, J., Garriott, C. and Pomranets, A. (2012) 'Is more high-frequency trading better? ' Working Paper.
  • Brogaard, J., Hendershott, T.J. and Riordan, R. (2014) 'High-frequency trading and price discovery', Review of Financial Studies, vol. 27(8), pp. 2267-2306.
  • Carrion, A., (2013) 'Very fast money: high-frequency trading on NASDAQ', Journal of Financial Markets, vol. 16(4), pp. 680-711.
  • Cespa, G. and Vives, X. (2013) 'The Welfare Impact of High Frequency', Working Paper.
  • Diebold, F.X., Gunther, T.A. and Tay, A.S. (1998) 'Evaluating density forecasts with applications to financial risk management', International Economic Review, vol. 39, pp. 863-883.
  • Easley, D., Lopez de Prado, M. and O'Hara, M. (2011) 'The Microstructure of the «Flash Crash»': Flow Toxicity, Liquidity Crashes, and the Probability of Informed Trading', Journal of Portfolio Management, vol. 37, pp. 118-128.
  • Easley, D., Lopez de Prado, M. and O'Hara, M. (2012a) 'Flow Toxicity and Liquidity in a High Frequency World', Review of Financial Studies, vol. 25, pp. 1457-1493.
  • Easley, D., Lopez de Prado, M. and O'Hara, M. (2012b) 'Bulk Classification of Trading Activity', SSRN Electronic Journal, vol. 03, DOI: 10.2139/ssrn.1989555.
  • Easley, D., Lopez de Prado, M. and O'Hara, M. (2013) 'Optimal Execution Horizon', Mathematical Finance, vol. 25(3), pp. 640-672.
  • Eddelbutel, D., McCurdy, T.H. (1998) 'The Impact of News on Foreign Exchange Rates: Evidence from very High Frequency Data', Manuscript, Rotman School of Management and Institute for Policy Analysis, University of Toronto.
  • Engle, R. (2000) 'The Econometrics of Ultra-High Frequency Data', Econometrica, vol. 68, pp. 1-22.
  • Engle, R. and Russell, J. (1997) 'Forecasting the Frequency of Changes in Quoted Foreign Exchange Prices with the Autoregressive Conditional Duration Model', Journal of Empirical Finance, vol. 4, pp. 187-212.
  • Engle, R. and Russell, J. (1998) 'Autoregressive Conditional Duration. A New Model for Irregularly Spaced Transaction Data', Econometrica, vol. 66, pp. 1127-1162.
  • Ghysels, E. and Jasiak, J. (1998) 'GARCH for Irregularly Spaced Financial Data: The ACD-GARCH model', Studies in Nonlinear Dynamics and Econometrics,vol. 2, pp. 133-149.
  • Goldstein, M., Kumar, P. and Graves, F.C. (2014) 'Computerized and High Frequency Trading', The Financial Review, vol. 49 (2), pp. 173-433.
  • Gramming, J. and Maurer, K.O. (2000) 'Non-Monotonic Hazard Functions and the Autoregressive Conditional Duration Model', The Econometrics Journal, vol. 3, pp. 16-38.
  • Guillaume, D.M., Dacorogna, M.M., Dave, R.R., Muller, U.A., Olsen, R.B. and Pictet, O.V. (1997) 'From the Bird's Eye to the Microscope: A Survey of New Stylized Facts of the Intra-Daily Foreign Exchange Markets', Finance and Stochastics, vol. 1, pp. 95-129.
  • Hafner, C. (1996) 'Estimating High Frequency Foreign Exchange Rate Volatility with Nonparametric ARCH Models', Journal of Statistical Planning and Inference, vol. 68, pp. 247-269.
  • Haldane, A. (2011) 'The Race to Zero', Bank of England Speeches, Speech given to the International Economic Association Sixteenth World Congress, July 2011.
  • Hasbrouck, J. (2013) 'High Frequency Quoting: Short-term Volatility in Bids and Offers', Working paper, [Online], Available: http://ssrn.com/abstract=2237499.
  • Hasbrouck, J. and Saar, G. (2009) 'Technology and Liquidity Provision: The Blurring of Traditional Definitions', Journal of Financial Markets, vol. 12, pp. 143-172.
  • Hasbrouck, J. and Saar, G. (2013) 'Low-Latency Trading', Journal of Financial Markets, vol. 16 (4), pp. 646-679.
  • Hautsch, N. (2004) Modelling Irregular Spaced Financial Data - Theory and Practice of Dynamic Duration and Intensity Models, Berlin Heidelberg: Springer-Verlag.
  • Hendershott, T., Jones, C. and Menkveld, A. J. (2011) 'Does Algorithmic Trading Increase Liquidity?', Journal of Finance, vol. 66, pp. 1-33.
  • Jasiak, J. (1998) 'Persistence in Intertrade Durations', Finance, vol. 19, pp. 166-195.
  • Jones, C. (2012) 'What do we know about high frequency trading?', Columbia University Working Paper.
  • Kirilenko, A.A., Kyle, A.S., Samadi, M. and Tuzun, T. (2011) 'The flash crash: the impact of high-frequency trading on an electronic market', Working Paper, CFTC and University of Maryland.
  • Laughlin, G., Aquirre, A. and Grundfest, J. (2014) 'Information Transmission between Financial Markets in Chicago and New York', Financial Review, vol. 49, pp. 283-312.
  • Lunde, A. (2000) 'A Generalized Gamma Autoregressive Conditional Duration Model', Discussion Paper, Aarlborg University.
  • Madhavan, A. (2013) 'Exchange-traded funds, market structure, and the flash crash', Financial Analysts Journal, vol. 68, pp. 20-35.
  • Malinova, K. and Park, A. (2013) 'Do retail traders benefit from improvements in liquidity?', Working Paper.
  • O'Hara, M. (2015) 'High Frequency Market Microstructure', Journal of Financial Economics, vol. 116, pp. 257-270.
  • O'Hara, M. (2011) 'What is a quote?', Journal of Trading, vol. 5(2), pp. 10-16.
  • O'Hara, M., Saar G., and Zhang, Z. (2014) 'Relative Tick Size and the Trading Environment', SSRN Electronic Journal, vol. 1, DOI: 10.2139/ssrn.2463360
  • Pagnotta, E. and Philippon, T. (2011) 'Competing on Speed', NBER Working Papers 17652, National Bureau of Economic Research.
  • Ye, M., Yao, C. and Jiading, G. (2013) 'The Externalities of High-Frequency Trading', Working Paper 2013.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171628100

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