Performance of American and Russian joint stock companies on financial market. A microstructure perspective
DOI:
https://doi.org/10.12775/EQUIL.2016.037Keywords:
market microstructure, Manganelli model, Moscow Stock Exchange (MOEX), New York Stock Exchange (NYSE), National Association of Securities Dealers Automated Quotations System (NASDAQ)Abstract
This paper compares the periods before and after the Ukrainian crisis of 2014 from the perspective of market microstructure. The hypothesis is that the crisis influenced the fragile Russian financial market equilibrium. As financial markets adapt to the new equilibrium, the paper studies the effects of the crisis and the imposition of economic sanctions on Russia in terms of volatility, duration, prices and volume for selected joint stock companies listed on the U.S. and the Russian stock markets. Results reveal that the Moscow Stock exchange lacks an appropriate transmission mechanism from informed investors to the rest of the market.
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References
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A?t-Sahalia, Y., & Yu, J. (2009). High Frequency Market Microstructure Noise Estimates and Liquidity Measures. Annals of Applied Statistics, 1. DOI: http://dx.doi. org/10.1214/08-AOAS200.
Allen, D., Ng, K. H., & Peiris, S. (2013). The Efficient Modelling of High Frequency Transaction Data: A New Application of Estimating Functions in Financial Economics. Economics Letters, 120. DOI: http://dx.doi.org/10.1016/j.econlet.2013. 03.049.
Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-section and Time-series Effects. Journal of Financial Markets. 5(1). DOI: http://dx.doi.org/10.1016/S1386-4181(01)00024-6.
Amihud, Y., & Mendelson, H. (1988). Liquidity and Asset Prices: Financial Management Implications. Financial Management, 17(1). DOI: http://dx.doi.org/10. 2307/3665910.
Bagehot, W. (1971). The Only Game in Town. Financial Analyst Journal, 22(27). DOI: http://dx.doi.org/10.2469/faj.v27.n2.12.
Bauwens, L., & Giot., P. (2000). The Logarithmic ACD Model: an Application to the Bid-ask Quote Process of Three NYSE Stocks. Annuls of Economy and Statistic, 60. DOI: http://dx.doi.org/10.2307/20076257.
Bauwens, L., & Veredas, D. (2004). The Stochastic Conditional Duration Model: a Latent Variable Model for the Analysis of Financial Durations. Journal of Econometrics, 119. DOI: http://dx.doi.org/10.1016/S0304-4076(03)00201-X.
Berger, D., Chaboud, A., Chernenko, S., Howorka, E., & Wright, J. (2008). Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data. Journal of International Economics, 75. DOI: http://dx.doi.org/10.1016/j.jinteco.2007 .10.004.
Bessembinder, H. (1994). Bid-Ask Spreads in the Interbank Foreign Exchange Market. Journal of Financial Economics, 35. DOI: http://dx.doi.org/10.1016/0304-405X(94)90036-1.
Bień, K. (2006a). Zaawansowane specyfikacje modeli ACD ? prezentacja oraz przykład zastosowania. Przegląd Statystyczny, 53(1).
Bień, K. (2006b). Model ACD ? podstawowa specyfikacja i przykład zastosowania. Przegląd Statystyczny, 53 (3).
Bień, K., Nolte, I., & Pohlmeier, W. (2007). A Multivariate Integer Count Hurdle Model: Theory and Application to Exchange Rate Dynamics. In L. Bauwens, W. Pohlmeier & D. Veredas (Eds.). Recent Developments in High Frequency Financial Econometrics. Berlin: Springer.
Bień, K., (2010). Przepływ zleceń a kurs walutowy ? badanie mikrostruktury międzybankowego. Bank i Kredyt., 41(5).
Box, G., & Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day.
Bu, F., Zhang, W., & He, W. (2005). Research on Stock Liquidity Based on Ultrahigh Frequency Data. Statistics & Decision, 2.
Caporale, G. M., & Plastun, A. (2016). Calendar Anomalies in the Ukrainian Stock Market. Deutsches Institut für Wirtschaftsforschung. Discussion Paper.
Doman, M., (2011). Mikrostruktura giełd papierów wartościowych. Poznań: Wydawnictwo UE.
Doman, M., & Doman, R. (2010). Dependencies Between Price Duration, Volatility, Volume and Return on the Warsaw Stock Exchange. Journal of Modern Accounting and Auditing, 6(10).
Dufour, A., & Engle, R. F. (2000). Time and the Impact of a Trade. Journal of Finance, 55.
Easley, D., & O?Hara, M. (2002). Time and the Process of Security Price Adjustment. Journal of Finance, 47. DOI: http://dx.doi.org/10.1111/j.1540-6261.1992.tb0 4402.x.
Easley, D., Kiefer, N., & O?Hara, M. (1997a). The Information Content of the Trading Process. Journal of Empirical Finance, 4. DOI: http://dx.doi.org/10.1016/ S0927-5398(97)00005-4.
Easley, D., Kiefer, N., & O?Hara, M. (1997b). One Day in the Life of a Very Common Stock. Review of Financial Studies, 10, DOI: http://dx.doi.org/10.1093 /rfs/10.3.805.
Easley, D., Kiefer, N., O?Hara, M., & Paperman, J. (1996). Liquidity. Information and Infrequently Traded Stocks. Journal of Finance, 51. DOI: http://dx.doi.org/10. 1111/j.1540-6261.1996.tb04074.x.
Easley, D., & O?Hara, M. (1987). Price. Trade Size. and Information in Securities Markets. Journal of Financial Economics, 19. DOI: http://dx.doi.org/10.1016 /0304-405X(87)90029-8.
Easley, D., & O'Hara, M. (1992). Time and the Process of Security Price Adjustment. Journal of Finance, 47(2). DOI: http://dx.doi.org/10.1111/j.1540-6261.1992 .tb04402.x.
Engle, R. F. (2000). The Econometrics of Ultra-high-frequency Data. Econometrica, 68. DOI: http://dx.doi.org/10.1111/1468-0262.00091.
Engle, R. F., & Lange, J. (1997). Measuring. Forecasting and Explaining Time Varying Liquidity in the Stock Market. Tech. Rep. National Bureau of Economic Research.
Engle, R. F., & Russell, J. R. (1998). Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data. Econometrica, 66.
Engle, R. F., & Russell, J. R. (2004). Analysis of High Frequency Data. In Y. Ait-Sahalia & L. P. Hansen (Eds.). Handbook of Financial Econometrics. North-Holland: Elsevier Science. DOI: http://dx.doi.org/10.2307/2999632.
Fernandes, M., & Grammig, J. (2006). A Family of Autoregressive Conditional Duration Models. Journal of Econometrics, 130. DOI: http://dx.doi.org/10.1016/j. jeconom.2004.08.016.
Frank, N. (2009). Linkages Between Asset Classes During the Financial Crisis. Accounting for Market Microstructure Noise and Non-synchronous Trading. Oxford-Man Institute of Quantitative Finance and Department of Economics. University of Oxford. U.K.
Garman, M. B. (1976). Market Microstructure. Journal of Financial Economics, 3(3). DOI: http://dx.doi.org/10.1016/0304-405X(76)90006-4.
Grossman, S. J., & Stiglitz, J. J. (1980). On the Impossibility of Informationally Efficient Markets. American Economic Review, 70.
Giot, P. (2001). Time Transformations. Intraday Data. and Volatility Models. Journal of Computational Finance, 4. DOI: http://dx.doi.org/10.21314/JCF.2001.071.
Glosten, L. R. & Milgrom, P. R. (1985). Bid. Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders. Journal of Financial Economics, 14. DOI: http://dx.doi.org/10.1016/0304-405X(85)90044-3.
Ghysels, E., & Jasiak, J. (1998). GARCH for Irregurally Spaced Financial Data: the ACD-GARCH Model. Studies in Nonlinear Dynamics & Econometrics, 2(4).
Gourieroux, C., & Jasiak, J. (2001). Financial Econometrics: Problems. Models and Methods. Princeton University Press.
Gourieroux, C., Jasiak, J., & LeFol, G. (1999). Intra-Day Market Activity. Journal of Financial Markets, 2. DOI: http://dx.doi.org/10.1016/S1386-4181(99)00004-X.
Green, W.H. (2003). Econometric Analysis. New Jersey: Pearson Education.
http://www.aeroflot.ru/cms/en.
http://www.ctcmedia.ru.
http://www.mcdonalds.com.
http://moex.com/en.
https://www.microsoft.com/pl.
http://www.nasdaq.com.
https://www.nyse.com.
http://www.rosneft.com.
http://www.rostelecom.ru/en.
http://corporate.exxonmobil.com.
https://www.yahoo.com.
https://www.yandex.com.
http://faculty.chicagobooth.edu
Hasbrouck, J. (2002). Stalking the ?Efficient Price? in Market Microstructure Specifications: an Overview. Journal of Financial Markets, 5.
Noh, J., Engle, R. F., & Kane, A. (1994). Forecasting Volatility and Option Prices of the S&P 500 Index. Journal of Derivatives, 2(1). DOI: http://dx.doi.org/10.3905/ jod.1994.407901.
Kyle, A. S. (1985). Continuous Auctions and Insider Trading. Econometrica, 22. DOI: http://dx.doi.org/10.2307/1913210.
Kyle, A. S., & Obizhaeva, A. A. (2016). Market Microstructure Invariance: Empirical Hypotheses. Econometrica, 84(4). DOI: http://dx.doi.org/10.3982/ECTA10486.
Liesenfeld, R., Nolte, I., & Pohlmeier, W. (2006). Modelling Financial Transaction Price Movements: A Dynamic Integer Count Data Model. Empirical Economics, 30(4). DOI: http://dx.doi.org/10.1007/s00181-005-0001-1.
Manganelli, S. (2005). Duration, Volume and Volatility Impact of Trades. Journal of Financial Markets, 8. DOI: http://dx.doi.org/10.1016/j.finmar.2005.06.002.
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59. DOI: http://dx.doi.org/10.2307/2938260.
Obizhaeva, A. A. (2016). The Russian Ruble Crisis of December 2014. Voprosy Ekonomiki, 5.
O?Hara, M. (1995). Market Microstructure. Cambridge. UK: Blackwell Publishers.
Osińska, M. (2010). Quality of the Forecasts of Currencies Exchange Rates Volatilities. International Research Journal of Finance and Economics, 60.
Payne, R. (2003). Informed Trade in Spot Foreign Exchange Markets: An Empirical Investigation. Journal of International Economics. 61. DOI: http://dx.doi.org/10. 1016/S0022-1996(03)00003-5.
Perraudin, W., & Vitale, P. (1996). Interdealer Trade and Information Flows in a Decentralized Foreign Exchange Market. In The Microstructure of Foreign Exchange Markets. National Bureau of Economic Research, Inc..
Russel, J. R., & Engle, R. F. (2010). Analysis of High Frequency Data. In Y. Ait-Sahalia & L. P. Hansen (Eds.). Handbook of Financial Econometrics. (vol. 1). Elsevier.
Scalas, E., Gorenflo, R., Luckock, H., Mainardi, F., Mantelli, M., & Raberto, M. (2004). Anomalous Waiting Times in High-frequency Financial Sata. Quantitative Finance, 4(6). DOI: http://dx.doi.org/10.1080/14697680500040413.
Sewell, M. V., & Yan, W. (2008). Ultra High Frequency Financial Data. In Proceedings of the 10th Annual Conference Companion on Genetic and Evolutionary Computation.
Tsay, R. (2005). Analysis f Financial Time Series. New York: Wiley.
Yuan, J., Pan, Y., & Zhang, X. (2015). Ultrahigh Frequency Data Liquidity Duration Estimation: A Case Study of Chinese A Shares. Mathematical Problems in Engineering, 2015. DOI: http://dx.doi.org/10.1155/2015/371272.
Zhang, M. Y., Russell, J. R., & Tsay, R. S. (2001). A Nonlinear Autoregressive Conditional Duration Model with Applications to Financial Transaction Data. Journal of Econometrics, 104. DOI: http://dx.doi.org/10.1016/S0304-4076(01)00063-X.
A?t-Sahalia, Y., & Yu, J. (2009). High Frequency Market Microstructure Noise Estimates and Liquidity Measures. Annals of Applied Statistics, 1. DOI: http://dx.doi. org/10.1214/08-AOAS200.
Allen, D., Ng, K. H., & Peiris, S. (2013). The Efficient Modelling of High Frequency Transaction Data: A New Application of Estimating Functions in Financial Economics. Economics Letters, 120. DOI: http://dx.doi.org/10.1016/j.econlet.2013. 03.049.
Amihud, Y. (2002). Illiquidity and Stock Returns: Cross-section and Time-series Effects. Journal of Financial Markets. 5(1). DOI: http://dx.doi.org/10.1016/S1386-4181(01)00024-6.
Amihud, Y., & Mendelson, H. (1988). Liquidity and Asset Prices: Financial Management Implications. Financial Management, 17(1). DOI: http://dx.doi.org/10. 2307/3665910.
Bagehot, W. (1971). The Only Game in Town. Financial Analyst Journal, 22(27). DOI: http://dx.doi.org/10.2469/faj.v27.n2.12.
Bauwens, L., & Giot., P. (2000). The Logarithmic ACD Model: an Application to the Bid-ask Quote Process of Three NYSE Stocks. Annuls of Economy and Statistic, 60. DOI: http://dx.doi.org/10.2307/20076257.
Bauwens, L., & Veredas, D. (2004). The Stochastic Conditional Duration Model: a Latent Variable Model for the Analysis of Financial Durations. Journal of Econometrics, 119. DOI: http://dx.doi.org/10.1016/S0304-4076(03)00201-X.
Berger, D., Chaboud, A., Chernenko, S., Howorka, E., & Wright, J. (2008). Order Flow and Exchange Rate Dynamics in Electronic Brokerage System Data. Journal of International Economics, 75. DOI: http://dx.doi.org/10.1016/j.jinteco.2007 .10.004.
Bessembinder, H. (1994). Bid-Ask Spreads in the Interbank Foreign Exchange Market. Journal of Financial Economics, 35. DOI: http://dx.doi.org/10.1016/0304-405X(94)90036-1.
Bień, K. (2006a). Zaawansowane specyfikacje modeli ACD ? prezentacja oraz przykład zastosowania. Przegląd Statystyczny, 53(1).
Bień, K. (2006b). Model ACD ? podstawowa specyfikacja i przykład zastosowania. Przegląd Statystyczny, 53 (3).
Bień, K., Nolte, I., & Pohlmeier, W. (2007). A Multivariate Integer Count Hurdle Model: Theory and Application to Exchange Rate Dynamics. In L. Bauwens, W. Pohlmeier & D. Veredas (Eds.). Recent Developments in High Frequency Financial Econometrics. Berlin: Springer.
Bień, K., (2010). Przepływ zleceń a kurs walutowy ? badanie mikrostruktury międzybankowego. Bank i Kredyt., 41(5).
Box, G., & Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day.
Bu, F., Zhang, W., & He, W. (2005). Research on Stock Liquidity Based on Ultrahigh Frequency Data. Statistics & Decision, 2.
Caporale, G. M., & Plastun, A. (2016). Calendar Anomalies in the Ukrainian Stock Market. Deutsches Institut für Wirtschaftsforschung. Discussion Paper.
Doman, M., (2011). Mikrostruktura giełd papierów wartościowych. Poznań: Wydawnictwo UE.
Doman, M., & Doman, R. (2010). Dependencies Between Price Duration, Volatility, Volume and Return on the Warsaw Stock Exchange. Journal of Modern Accounting and Auditing, 6(10).
Dufour, A., & Engle, R. F. (2000). Time and the Impact of a Trade. Journal of Finance, 55.
Easley, D., & O?Hara, M. (2002). Time and the Process of Security Price Adjustment. Journal of Finance, 47. DOI: http://dx.doi.org/10.1111/j.1540-6261.1992.tb0 4402.x.
Easley, D., Kiefer, N., & O?Hara, M. (1997a). The Information Content of the Trading Process. Journal of Empirical Finance, 4. DOI: http://dx.doi.org/10.1016/ S0927-5398(97)00005-4.
Easley, D., Kiefer, N., & O?Hara, M. (1997b). One Day in the Life of a Very Common Stock. Review of Financial Studies, 10, DOI: http://dx.doi.org/10.1093 /rfs/10.3.805.
Easley, D., Kiefer, N., O?Hara, M., & Paperman, J. (1996). Liquidity. Information and Infrequently Traded Stocks. Journal of Finance, 51. DOI: http://dx.doi.org/10. 1111/j.1540-6261.1996.tb04074.x.
Easley, D., & O?Hara, M. (1987). Price. Trade Size. and Information in Securities Markets. Journal of Financial Economics, 19. DOI: http://dx.doi.org/10.1016 /0304-405X(87)90029-8.
Easley, D., & O'Hara, M. (1992). Time and the Process of Security Price Adjustment. Journal of Finance, 47(2). DOI: http://dx.doi.org/10.1111/j.1540-6261.1992 .tb04402.x.
Engle, R. F. (2000). The Econometrics of Ultra-high-frequency Data. Econometrica, 68. DOI: http://dx.doi.org/10.1111/1468-0262.00091.
Engle, R. F., & Lange, J. (1997). Measuring. Forecasting and Explaining Time Varying Liquidity in the Stock Market. Tech. Rep. National Bureau of Economic Research.
Engle, R. F., & Russell, J. R. (1998). Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data. Econometrica, 66.
Engle, R. F., & Russell, J. R. (2004). Analysis of High Frequency Data. In Y. Ait-Sahalia & L. P. Hansen (Eds.). Handbook of Financial Econometrics. North-Holland: Elsevier Science. DOI: http://dx.doi.org/10.2307/2999632.
Fernandes, M., & Grammig, J. (2006). A Family of Autoregressive Conditional Duration Models. Journal of Econometrics, 130. DOI: http://dx.doi.org/10.1016/j. jeconom.2004.08.016.
Frank, N. (2009). Linkages Between Asset Classes During the Financial Crisis. Accounting for Market Microstructure Noise and Non-synchronous Trading. Oxford-Man Institute of Quantitative Finance and Department of Economics. University of Oxford. U.K.
Garman, M. B. (1976). Market Microstructure. Journal of Financial Economics, 3(3). DOI: http://dx.doi.org/10.1016/0304-405X(76)90006-4.
Grossman, S. J., & Stiglitz, J. J. (1980). On the Impossibility of Informationally Efficient Markets. American Economic Review, 70.
Giot, P. (2001). Time Transformations. Intraday Data. and Volatility Models. Journal of Computational Finance, 4. DOI: http://dx.doi.org/10.21314/JCF.2001.071.
Glosten, L. R. & Milgrom, P. R. (1985). Bid. Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders. Journal of Financial Economics, 14. DOI: http://dx.doi.org/10.1016/0304-405X(85)90044-3.
Ghysels, E., & Jasiak, J. (1998). GARCH for Irregurally Spaced Financial Data: the ACD-GARCH Model. Studies in Nonlinear Dynamics & Econometrics, 2(4).
Gourieroux, C., & Jasiak, J. (2001). Financial Econometrics: Problems. Models and Methods. Princeton University Press.
Gourieroux, C., Jasiak, J., & LeFol, G. (1999). Intra-Day Market Activity. Journal of Financial Markets, 2. DOI: http://dx.doi.org/10.1016/S1386-4181(99)00004-X.
Green, W.H. (2003). Econometric Analysis. New Jersey: Pearson Education.
http://www.aeroflot.ru/cms/en.
http://www.ctcmedia.ru.
http://www.mcdonalds.com.
http://moex.com/en.
https://www.microsoft.com/pl.
http://www.nasdaq.com.
https://www.nyse.com.
http://www.rosneft.com.
http://www.rostelecom.ru/en.
http://corporate.exxonmobil.com.
https://www.yahoo.com.
https://www.yandex.com.
http://faculty.chicagobooth.edu
Hasbrouck, J. (2002). Stalking the ?Efficient Price? in Market Microstructure Specifications: an Overview. Journal of Financial Markets, 5.
Noh, J., Engle, R. F., & Kane, A. (1994). Forecasting Volatility and Option Prices of the S&P 500 Index. Journal of Derivatives, 2(1). DOI: http://dx.doi.org/10.3905/ jod.1994.407901.
Kyle, A. S. (1985). Continuous Auctions and Insider Trading. Econometrica, 22. DOI: http://dx.doi.org/10.2307/1913210.
Kyle, A. S., & Obizhaeva, A. A. (2016). Market Microstructure Invariance: Empirical Hypotheses. Econometrica, 84(4). DOI: http://dx.doi.org/10.3982/ECTA10486.
Liesenfeld, R., Nolte, I., & Pohlmeier, W. (2006). Modelling Financial Transaction Price Movements: A Dynamic Integer Count Data Model. Empirical Economics, 30(4). DOI: http://dx.doi.org/10.1007/s00181-005-0001-1.
Manganelli, S. (2005). Duration, Volume and Volatility Impact of Trades. Journal of Financial Markets, 8. DOI: http://dx.doi.org/10.1016/j.finmar.2005.06.002.
Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59. DOI: http://dx.doi.org/10.2307/2938260.
Obizhaeva, A. A. (2016). The Russian Ruble Crisis of December 2014. Voprosy Ekonomiki, 5.
O?Hara, M. (1995). Market Microstructure. Cambridge. UK: Blackwell Publishers.
Osińska, M. (2010). Quality of the Forecasts of Currencies Exchange Rates Volatilities. International Research Journal of Finance and Economics, 60.
Payne, R. (2003). Informed Trade in Spot Foreign Exchange Markets: An Empirical Investigation. Journal of International Economics. 61. DOI: http://dx.doi.org/10. 1016/S0022-1996(03)00003-5.
Perraudin, W., & Vitale, P. (1996). Interdealer Trade and Information Flows in a Decentralized Foreign Exchange Market. In The Microstructure of Foreign Exchange Markets. National Bureau of Economic Research, Inc..
Russel, J. R., & Engle, R. F. (2010). Analysis of High Frequency Data. In Y. Ait-Sahalia & L. P. Hansen (Eds.). Handbook of Financial Econometrics. (vol. 1). Elsevier.
Scalas, E., Gorenflo, R., Luckock, H., Mainardi, F., Mantelli, M., & Raberto, M. (2004). Anomalous Waiting Times in High-frequency Financial Sata. Quantitative Finance, 4(6). DOI: http://dx.doi.org/10.1080/14697680500040413.
Sewell, M. V., & Yan, W. (2008). Ultra High Frequency Financial Data. In Proceedings of the 10th Annual Conference Companion on Genetic and Evolutionary Computation.
Tsay, R. (2005). Analysis f Financial Time Series. New York: Wiley.
Yuan, J., Pan, Y., & Zhang, X. (2015). Ultrahigh Frequency Data Liquidity Duration Estimation: A Case Study of Chinese A Shares. Mathematical Problems in Engineering, 2015. DOI: http://dx.doi.org/10.1155/2015/371272.
Zhang, M. Y., Russell, J. R., & Tsay, R. S. (2001). A Nonlinear Autoregressive Conditional Duration Model with Applications to Financial Transaction Data. Journal of Econometrics, 104. DOI: http://dx.doi.org/10.1016/S0304-4076(01)00063-X.
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Published
2016-12-31
How to Cite
Osińska, M., Dobrzyński, A., & Shachmurove, Y. (2016). Performance of American and Russian joint stock companies on financial market. A microstructure perspective. Equilibrium. Quarterly Journal of Economics and Economic Policy, 11(4), 819–851. https://doi.org/10.12775/EQUIL.2016.037
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