臺灣博碩士論文加值系統

This paper follows Ghysels, Gourieroux, and Jasiak (1998), examines the causal relation between price and volume in Taiwan Futures Market. I use high frequency intraday data of Taiwan Stock Exchange Capitalization Weighted Stock Index in Taiwan Futures Exchange; and analyze the causality between returns and volume series, which are transformed into Markov chain, with Granger’s causal tests. I analyze the data with two different time category, trading time and calendar time. In our research we find out that Taiwan futures market has a bi-directional causality between price and volume in trading time analysis, as to the calendar time analysis, only price to volume unidirectional causality exists. Unlike the unidirectional causal relation that Ghysels, Gourieroux, and Jasiak (1998) observed in French security market.

1. Introduction 4
2. Methodology 8
3. Data 12
4. Empirical Results 14
4.1 Analysis in Trading Time 14
4.1.1 Univariate analysis for fixed price and volume thresholds 14
4.1.2 Correlation analysis and state selection for return series 15
4.1.3 Causality analysis and state selection for volume series 16
4.2 Analysis in Calendar Time 18
4.2.1 Univariate analysis for fixed price and volume thresholds 18
4.2.2 Correlation analysis and state selection for return series 19
4.2.3 Causality analysis and state selection for volume series 20
5. Conclusion 22
Reference 23
Appendix 25

[1] Addmati, A. and Pfleiderer, P. (1988): “A Theory of Intraday Patterns: Volume and Price Variability”, Review of Financial Studies, 1, 3-40
[2] Bouissou, M., Laffont J.J. and Q. Vuong (1986): “Test of Non Causality under Markov Assumptions for Qualitative Panel Data”, Econometrica, 54, 395-414
[3] Campbell, J., Grossman, S. and J. Wang (1993): “Trading Volume and Serial Correlation in Stock Returns”, Quarterly Journal of Economics, 108, 905-939
[4] Engle, R. and Russel, J. (1998): “Autoregressive Conditional Multinomial: A New Model for Irregularly Spaced Discrete-Valued Time Series Data with Applications to High Frequency Financial Data”, Discussion Paper, UCSD
[5] Gallant, R., Rossi, P. and Tauchen, G. (1992): “Stock Prices and Volume”, Review of Financial Studies, 5, 199-242.
[6] Ghysels, E., Gourieroux, C. and Jasiak, J. (1998): Causality between Returns and Traded Volumes
[7] Gourieroux, C., Jasiak, J. and G. Lefol (1999): “Intra-day Market Activity”, Journal of Financial Markets, 2, 193-226
[8] Granger, C. (1969): “Investigating Causal Relations by Econometric Models and Cross-spectral Methods”, Econometrica, 37, 424-438
[9] Gunduz, L. and Hatemi-J, A. (2005): “Stock Price and Colume Relation in Emerging Markets”, Journal of Emerging Markets Finance and Trade, 41, 29-44
[10] Jones,C., Kaul, G. and Lipson, M. (1994): “Transactions, Volume and Volatility”, Review of Financial Studies, 7, 631-651
[11] Kamath, R. (2007): “Investigating Causal Relations between Price Changes and Trading Volume Changes, in the Turkish Market”, American Society of Business and Behavioral Sciences, 3,
[12] Kamath, R. and Wang, Y. (2006): “The Causality between Stock Index Returns and Volumes in the Asian Equity Markets”, Journal of International Business Research, 5, 63-74
[13] Karpoff, J. (1987): “The Relation between Price Change and Trading Volume: A Survey”, Journal of Financial and Quantitative Analysis, 22, 109-126.
[14] Lamoureux, C. and Lastrapes, W. (1991): “Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects”, Journal of Finance, 45, 221-229
[15] Tauchen, G. and Pitts, M. (1983): “The Price Variability – Volume Relationship on Speculative Markets”, Econometrica, 51, 485-505.