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http://dx.doi.org/10.13106/jafeb.2020.vol7.no8.041

Capturing the Short-run and Long-run Causal Behavior of Philippine Stock Market Volatility under Vector Error Correction Environment  

CAMBA, Abraham C. Jr. (Department of Economics, College of Social Sciences and Development, Polytechnic University of the Philippines)
Publication Information
The Journal of Asian Finance, Economics and Business / v.7, no.8, 2020 , pp. 41-49 More about this Journal
Abstract
This study investigates the short-run and long-run causal behavior of the Philippine stock market index volatility under vector error correction environment. The variables were tested first for stationarity and then long-run equilibrium relationship. Moreover, an impulse response function was estimated to examine the extent of innovations in the independent variables in explaining the Philippine stock market index volatility. The results reveal that the volatility of the Philippine stock market index exhibit long-run equilibrium relationship with Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil prices. The short-run dynamics-based VECM estimates indicate that in the short-run, increases (i.e., depreciation) in Peso-Dollar exchange rate cause PSEI volatility to increase. As for the London Interbank Offered Rate, it causes increases in PSEI volatility in the short-run. The adjustment coefficients used with the long-run dynamics validates the presence of unidirectional causal long-run relationship from Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil prices to PSEI volatility, and bidirectional causal long-run relationship between PSEI volatility and London Interbank Offered Rate. The impulse response functions developed within the VECM framework demonstrate the positive and negative reactions of PSEI volatility to unanticipated Peso-Dollar exchange rate, London Interbank Offered Rate, and crude oil price shocks.
Keywords
Crude Oil; LIBOR; Exchange Rate; Stock Market Volatility;
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Times Cited By KSCI : 11  (Citation Analysis)
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1 Abdalla, S. Z. S. (2013). Modelling the Impact of Oil Price Fluctuations on the Stock Returns in an Emerging Market: The Case of Saudi Arabia. Interdisciplinary Journal of Research in Business, 2(10), 10-20.
2 Al Hayky, A., & Naim, N. (2016). The Relationship Between Oil Price and Stock Market Index: An Empirical Study from Kuwait. Presented at Middle East Economic Association 15th International Conference.
3 Al-Homaidi, A., Tabash, I., Al-Ahdal, M., Farhan, H. S., & Khan, H. (2020). The Liquidity of Indian Firms: Empirical Evidence of 2154 Firms. Journal of Asian Finance, Economics and Business, 7(1), 19-27. https://doi:10.13106/jafeb.2020.vol7.no1.19   DOI
4 Camba, Jr. A. C., & Camba, A. L. (2020). The Dynamic Relationship of Domestic Credit and Stock Market Liquidity on the Economic Growth of the Philippines. Journal of Asian Finance, Economics and Business, 7(1), 37-46. https://doi:10.13106/jafeb.2020.vol7.no1.37   DOI
5 Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(1), 1057-1072.   DOI
6 Echchabi, A., & Azouzi, D. (2017). Oil Price Fluctuations and Stock Market Movements: An Application in Oman. Journal of Asian Finance, Economics and Business, 4(2), 19-86. https://doi:10.13106/jafeb.2017.vol4.no2.19   DOI
7 Engle, R. F., & Granger, C. W. J. (1987). Cointegration and Error Correction: Representation Estimation and Testing. Econometrica, 55, 251-276. https://doi:10.2307/1912517   DOI
8 Granger, C.W.J. (1988). Some Recent Developments in a Concept of Causality. Journal of Econometrics, 39, 199-211. https://doi.org/10.1016/0304-4076(88)90045-0   DOI
9 Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration - with application to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x   DOI
10 Kuo, C. Y. (2016). Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory. Economic Modelling, 52, 772-789. https://doi.org/10.1016/j.econmod.2015.10.016   DOI
11 Lee, J. W., & Brahmasrene, T. (2018). An Exploration of Dynamical Relationships between Macroeconomic Variables and Stock Prices in Korea. Journal of Asian Finance, Economics and Business, 5(3), 7-17. https://doi:10.13106/jafeb.2018.vol5.no3.7   DOI
12 Lee, J. W., & Zhao, T.F. (2014). Dynamic Relationship between Stock Prices and Exchange Rates: Evidence from Chinese Stock Markets. Journal of Asian Finance, Economics and Business. 1(1), 5-14. https://doi:10.13106/jafeb.2014.vol1.no1.5   DOI
13 Malik, F., & Hammoudeh, S. (2007). Shock and Volatility Transmission in the Oil, US and Gulf Equity Markets. International Review of Economics and Finance, 16(3), 357-368. https://doi.org/10.1016/j.iref.2005.05.005   DOI
14 Malik, F., & Hassan S. A. (2004). Modeling Volatility in Sector Index Returns with GARCH Models Using an Iterated Algorithm. Journal of Economics and Finance, 28(2), 211-225. https://doi:10.1007/BF02761612   DOI
15 Maysami, R. C. Howe, L. C., & Hamzah M. A. (2004). Relationship between Macroeconomic Variables and Stock Market Indices: Cointegration Evidence from Stock Exchange of Singapore's All-S Sector Indices. Journal Pengurusan, 24, 47-77. Retrieved December 18, 2019, from: http://ejournal.ukm.my/pengurusan/article/view/1454/1264
16 Nguyen, C. T., & Nguyen, M. H. (2019). Modeling Stock Price Volatility: Empirical Evidence from the Ho Chi Minh City Stock Exchange in Vietnam. Journal of Asian Finance, Economics and Business, 6(3), 19-26. https://doi:10.13106/jafeb.2019.vol6.no3.19   DOI
17 Ono, S. (2011). Oil price shocks and stock markets in BRICs. European Journal of Comparative Economics, 8, 29-45. Retrieved December 20, 2019, from: http://hdl.handle.net/2115/46781
18 Rahman, M. L., & Uddin, J. (2009). Dynamic relationship between stock prices and exchange rates: Evidence from three South Asian countries. International Business Research, 2(2), 167-174.
19 Parsva, P., & Lean, H. H. (2017). Multivariate Causal Relationship between Stock Prices and Exchange Rates in the Middle East Journal of Asian Finance, Economics and Business, 4(1), 25-38. https://doi:10.13106/jafeb.2017.vol4.no1.25   DOI
20 Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrica, 75(1), 335-346. Retrieved January 11, 2020, from: http://www.jstor.org/stable/2336182   DOI
21 Sahadudheen, I. (2015). An Exponential GARCH Approach to the Effect of Impulsiveness of Euro on Indian Stock Market. Journal of Asian Finance, Economics and Business, 2(3), 17-22. https://doi:10.13106/jafeb.2015.vol2.no3.17   DOI
22 Tu, T.T., & Liao, C.W. (2020). Block Trading Based Volatility Forecasting: An Application of VACD-FIGARCH Model. Journal of Asian Finance, Economics and Business, 7(4), 59-70. https://doi:10.13106/jafeb.2020.vol7.no4.59   DOI