Time‐varying volatility modelling of Baltic stock markets

References

• Adekola , A. , Korsakiene , R. and Tvaronavičiene , M. 2008 . Approach to innovative activities by Lithuanian companies in the current conditions of development . Technological and Economic Development of Economy , 14 (4) : 595 – 611 . doi:10.3846/1392–8619.2008.14.595–611
   Web of Science ®Google Scholar
• Akgiray , V. 1989 . Conditional Heteroscedasticity in Time Series of Stock Return: Evidence and Forecast . Journal of Business , 62 (1) : 55 – 80 . doi:10.1086/296451
   Google Scholar
• Alexander , C. 2000 . Risk Management and Analysis, Measuring and Modelling Financial Risk , 304 New York : John Wiley & Sons . ISBN‐10: 0471979570
   Google Scholar
• Alexander , C. 2001 . Market Models: A Guide to Financial Data Analysis , 514 New York : John Wiley & Sons . ISBN13: 9780471899754
   Google Scholar
• Aslanidis , N. , Osborn , D. R. and Sensier , M. 2009 . Co‐Movements between US and UK Stock Prices: The Role of Time‐Varying Conditional Correlations . International Journal of Finance and Economics , [online], [accessed 6 May 2010]. Available from Internet: < http://www3.interscience.wiley.com/journal/122528310/abstract>
   Google Scholar
• Black , F. 1976 . “ Studies of stock price volatility changes ” . In Proceedings of the 1976 Meeting of the Business and Economics Statistics Section , 177 – 181 . Washington, DC : American Statistical Association .
   Google Scholar
• Blattberg , C. R. and Gonedes , J. N. 1974 . A Comparison of the Stable and Student Distribution of Statistical Models for Stock Prices . Journal of Business , 47 (2) : 244 – 280 . doi:10.1086/295634
   Google Scholar
• Bollerslev , T. 1986 . Generalized Autoregressive Conditional Heteroscedasticity . Journal of Econometrics , 31 (3) : 307 – 327 . doi:10.1016/0304–4076(86)90063–1
   Google Scholar
• Christiansen , C. 2010 . Decomposing European Bond and Equity Volatility . International Journal of Finance and Economics , 15 (2) : 105 – 122 . doi:10.1002/ijfe.385
   Google Scholar
• Christie , A. A. 1982 . The Stochastic Behavior of Common Stock Variance: Value, Leverage and Interest Rate Effects . Journal of Financial Economics , 10 (4) : 407 – 432 . doi:10.1016/0304–405X(82)90018–6
   Google Scholar
• Clark , K. P. 1973 . A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices . Econometrica , 41 : 135 – 156 . doi:10.2307/1913889
   Web of Science ®Google Scholar
• Teresiene , D. 2009 . Lithuanian Stock Market Analysis Using a Set of Garch Models . Journal of Business Economics and Management , 10 (4) : 349 – 360 . doi:10.3846/1611–1699.2009.10.349–360
   Google Scholar
• Ding , Z. , Granger , C. W. J. and Engle , F. R. 1993 . A Long Memory Property of Stock Markets Returns and A New Model . Journal of Empirical Finance , 1 (1) : 83 – 106 . doi:10.1016/0927–5398(93)90006‐D
   Google Scholar
• Enders , W. 2004 . Applied Econometric Time Series , 2nd edition , 480 New York : John Wiley & Sons . ISBN: 978–0–471–23065–6
   Google Scholar
• Engle , F. R. 1982 . Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation . Econometrica , 50 (4) : 987 – 1008 . doi:10.2307/1912773
   Web of Science ®Google Scholar
• Engle , F. R. , Lilien , M. D. and Robins , P. R. 1987 . Estimating Time‐Varying Risk Premia in the Term Structure: The ARCH‐M Model . Econometrica , 55 (2) : 391 – 407 . doi:10.2307/1913242
   Google Scholar
• Engle , F. R. and Lee , G. J. G. 1993a . Long Run Volatility Forecasting for Individual Stocks in a One Factor Model , 93 San Diego : University of California . Manuscript
   Google Scholar
• Engle , F. R. and Lee , G. J. G. 1993b . A Permanent and Transitory Component Model of Stock Return Volatility , Discussion paper 92–44R 130 San Diego : University of California .
   Google Scholar
• Engle , F. R. and Ng , K. V. 1993 . Measuring and Testing the Impact of News on Volatility . Journal of Finance , 48 (5) : 1749 – 1778 . doi:10.2307/2329066
   Google Scholar
• Engle , F. R. and Mezrich , J. 1995 . Grappling with GARCH . Risk , 8 (9) : 112 – 117 .
   Google Scholar
• Fama , F. E. 1965 . The Behavior of Stock Market Prices . Journal of Business , 38 : 34 – 105 . doi:10.1086/294743
   Web of Science ®Google Scholar
• Glosten , R. L. , Jagannathan , R. and Runkle , E. D. 1993 . On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. Federal Reserve Bank of Minneapolis . Research Department Staff Report , 157 : 1 – 36 .
   Google Scholar
• Gurgul , H. , Majdosz , P. and Mestel , R. 2006 . Implications of Dividend Announcements for Stock Prices and Trading Volume of DAX Companies . Czech Journal of Economics and Finance , 56 (1–2) : 58 – 68 .
   Google Scholar
• Hagerud , E. G. 1997 . Specification Test for Asymmetric GARCH . Working Paper Series in Economics and Finance , 163 : 1 – 32 .
   Google Scholar
• Kearney , C. and Daly , K. 1998 . The Causes of Stock Market Volatility in Australia . Applied Financial Economics , 8 (6) : 597 – 605 . doi:10.1080/096031098332637
   Google Scholar
• Kim , D. and Kon , S. I. 1994 . Alternative Models for Conditional Heteroscedasticity of Stock Returns . Journal of Business , 67 (4) : 563 – 598 . doi:10.1086/296647
   Google Scholar
• Lucchetti , R. and Rossi , E. 2005 . Artificial Regression Testing in the GARCH‐in‐Mean Model . Econometrics Journal , 8 (3) : 306 – 322 . doi:10.1111/j.1368–423X.2005.00166.x
   Google Scholar
• Mandelbrot , B. 1963 . The Variation of Certain Speculative Prices . Journal of Business , 36 : 394 – 419 . doi:10.1086/294632
   Web of Science ®Google Scholar
• Mcmillan , D. G. and Speight , A. E. H. 2006 . Volatility Dynamics and Heterogeneous Markets . International Journal of Finance and Economics , 11 (2) : 115 – 121 . doi:10.1002/ijfe.281
   Google Scholar
• McDonald , B. J. 1996 . “ Probability Distributions for Financial Models ” . In Handbook of Statistics , Edited by: Maddala , G.S. and Rao , C.R. 427 – 461 . Elsevier Science 14 .
   Google Scholar
• Melnikas , B. 2008 . Integral Spaces in the European Union: Possible Trends of the Social, Economic and Technological Integration in the Baltic Region . Journal of Business Economics and Management , 9 (1) : 65 – 77 . doi:10.3846/1611–1699.2008.9.65–77
   Web of Science ®Google Scholar
• Nelson , B. D. 1991 . Conditional Heteroskedasticity in Asset Returns: A New Approach . Econometrica , 59 (2) : 347 – 370 . doi:10.2307/2938260
   Google Scholar
• Pagan , R. A. and Schwert , G. W. 1990 . Alternative Models for Conditional Stock Volatility . Journal of Econometrics , 45 (1–2) : 267 – 290 . doi:10.1016/0304–4076(90)90101‐X
   Google Scholar
• Pilinkus , D. 2010 . Macroeconomic Indicators and Their Impact on Stock Market Performance in the Short and Long Run: The Case of the Baltic States . Technological and Economic Development of Economy , 16 (2) : 291 – 304 . doi:10.3846/tede.2010.19
   Google Scholar
• Pota , V. 2008 . Estimating the Dynamics of Weak Efficiency on the Prague Stock Exchange Using the Kalman Filter . Czech Journal of Economics and Finance , 58 (5–6) : 248 – 260 .
   Google Scholar
• Schwert , G. W. 1989 . Why Does Stock Market Volatility Change Over Time? . Journal of Finance , 44 (5) : 1115 – 1153 . doi:10.2307/2328636
   Google Scholar
• Sentana , E. and Wadhwani , S. 1992 . Feedback Traders and Stock Return Autocorrelations: Evidence From a Century of Daily Data . Economic Journal , 102 : 415 – 425 . doi:10.2307/2234525
   Web of Science ®Google Scholar
• Tay , N. S. P. and Zhu , Z. 2000 . Correlations in Returns and Volatilities in Pacific‐Rim Stock Markets . Open Economies Review , 11 (1) : 27 – 47 . doi:10.1023/A:1008349012883
   Google Scholar
• Tvaronavičiene , M. , Grybaite , V. and Tvaronavičiene , A. 2009 . If Institutional Performance Matters: Development Comparisons of Lithuania, Latvia and Estonia . Journal of Business Economics and Management , 10 (3) : 271 – 278 . doi:10.3846/1611–1699.2009.10.271–278
   Google Scholar
• Taylor , S. J. 1994 . Modelling Stochastic Volatility: A Review and Comparative Study . Mathematical Finance , 4 (2) : 183 – 204 . doi:10.1111/j.1467–9965.1994.tb00057.x
   Google Scholar