ISSN: 2056-3736 (Online Version) | 2056-3728 (Print Version)

Dynamic Responses of Major Pacific Rim Emerging Equity Markets to the US Crude Oil Fear Index (OVX)

Bahram Adrangi and Arjun Chatrath

Correspondence: Bahram Adrangi,

University of Portland, USA

pdf (1623.52 Kb) | doi:


This study examines the reaction of four major emerging equity markets of the Pacific Rim to the US oil market fear index (i.e., the Chicago Board of Trade Volatility Index, OVX). The OVX is designed to perform as a leading indicator of the volatility in crude oil markets. Our study examines the daily data for the period of 2014 through 2019. We excluded data for the extraordinary and transitory COVID-19 time period. We found that, during this period, there were four significant breaks in the data. Impulse responses from the structural vector autoregressive (SVAR) estimation show that in the second and third subperiods, from December 2016 through December 2018, the volatility of the equity markets of Hong Kong, Shanghai, Seoul, and Taiwan responded to structural shocks to the OVX. Nonlinear Granger causality tests confirmed these findings. This period is characterized by geopolitical crises, like nuclear proliferation on the Korean Peninsula and lingering complications surrounding the Brexit referendum.


  volatility, Pacific Rim Equity Markets, OVX, structural vector autoregression, GARCH Models, causality


Adrangi, B., Baade, H., & Raffiee, K. (2019). Dynamic Responses of the Economy to Monetary Shocks in the United Kingdom. Review of Economics & Finance, 15, 31-45.Adrangi, B., Chatrath, A., Macri, J., & Raffiee, K. (2015). Crude oil price volatility spillovers into major equity markets. Journal of energy markets, 8(1), 77-95.Adrangi, B., Chatrath, A., Macri, J., & Raffiee, K. (2018).   U.S. Diesel Fuel Price Responses to the Global Crude Oil Supply and Demand, Annals of Financial Economics,  pp. 181-825.Adrangi, B., Chatrath, A., Macri, J., & Raffiee, K. (2019). Dynamic Responses of Major Equity Markets to the US Fear Index. Journal of Risk and Financial Management, 12(4), 156.Adrangi, B., Chatrath, A., Macri, J., & Raffiee, K. (2020). Dynamics of crude oil price shocks and major Latin American Equity Markets: A study in time and frequency domains. Bulletin of Economic Research.Adrangi, B., Chatrath, A., Raffiee, K., & Ripple, R. D. (2001). Alaska North Slope crude oil price and the behavior of diesel prices in California. Energy Economics, 23(1), 29-42.Ahmad, W., Sadorsky, P., & Sharma, A. (2018). Optimal hedge ratios for clean energy equities. Economic Modelling, 72, 278-295.Akaike, H. (1974). A new look at the statistical model identification. In Selected Papers of Hirotugu Akaike (pp. 215-222). Springer, New York, NY.Ang, A., Hodrick, R. J., Xing, Y., & Zhang, X. (2006). The cross‐section of volatility and expected returns. The Journal of Finance, 61(1), 259-299.Badshah, I. U., Frijns, B., & Tourani‐Rad, A. (2013). Contemporaneous spill‐over among equity, gold, and exchange rate Implied Volatility Indices. Journal of Futures Markets, 33(6), 555-572.Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of applied econometrics, 18(1), 1-22.Blanchard, O. J., & Quah, D. (1989). The dynamic Effects of aggregate Demand and Supply Disturbances. American Economic Review, 79(4) 655-673.Blanchard, O. J. (1989). A traditional interpretation of macroeconomic fluctuations. The American Economic Review, 1146-1164.Bloomberg., March 2021Boscaljan, B., and J. Clark. 2013. Do large shocks in VIX signal a flight-to-safety in the gold market? Journal of Applied Finance 2:120-31.Chen, Y., He, K., & Yu, L. (2015). The information content of OVX for crude oil returns analysis and risk measurement: Evidence from the Kalman filter model. Annals of Data Science, 2(4), 471-487.Cheuathonghua, M., Padungsaksawasdi, C., Boonchoo, P., & Tongurai, J. (2019). Extreme spillovers of VIX fear index to international equity markets. Financial Markets and Portfolio Management, 33(1), 1-38.Edwards III, G. C., Mitchell, W., & Welch, R. (1995). Explaining presidential approval: The significance of issue salience. American Journal of Political Science, 108-134.Forbes, What Is The Outlook For Construction Post Pandemic? Apr 20, 2021Frijns, B., Tallau, C., & Tourani‐Rad, A. (2010). The information content of implied volatility: evidence from Australia. Journal of Futures Markets: Futures, Options, and Other Derivative Products, 30(2), 134-155.Geng, J. B., Chen, F. R., Ji, Q., & Liu, B. Y. (2021). Network connectedness between natural gas markets, uncertainty and stock markets. Energy Economics, 95, 105001.Geweke, J. (1984), Inference and causality in economic time series models, in Z. Griliches and M. D. Intriligator (eds), Handbook of Econometrics, Vol. 2, North-Holland, Amsterdam, 1101±1144.Giot, P. (2005). Relationships between implied volatility indices and stock index returns. Journal of Portfolio Management, 31(3), 92-100.Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438.GÜRSOY, S. (2020). Investigation of The Relationship Between VIX Index and BRICS Countries Stock Markets: An Econometric Application. Mehmet Akif Ersoy Üniversitesi Uygulamalı Bilimler Dergisi, 4(2), 397-413.Ji, Q., Bouri, E., & Roubaud, D. (2018). Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities. International Review of Financial Analysis, 57, 1-12.Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration—with applications to the demand for money. Oxford Bulletin of Economics and statistics, 52(2), 169-210.Jubinski, D., and A. F. Lipton. 2013. VIX, gold, silver, and oil: How do commodities react to financial market volatility? Journal of Accounting and Finance 13:70-88.Kang, S., Hernandez, J. A., Sadorsky, P., & McIver, R. (2021). Frequency spillovers, connectedness, and the hedging effectiveness of oil and gold for US sector ETFs. Energy Economics, 99, 105278.Kilian, L., & Park, C. (2009). The impact of oil price shocks on the US stock market. International Economic Review, 50(4), 1267-1287.Lin, J. B., & Tsai, W. (2019). The Relations of Oil Price Change with Fear Gauges in Global Political and Economic Environment. Energies, 12(15), 2982.Lundberg, C., Skolrud, T., Adrangi, B., & Chatrath, A. (2021). Oil Price Pass through to Agricultural Commodities. American Journal of Agricultural Economics, 103(2), 721-742.Lütkepohl, Helmut, New Introduction to Multiple Time Series Analysis, Ed. Springer-Verlag, Berlin, 2005.MacKinnon, J. G., Haug, A. A., & Michelis, L. (1999). Numerical distribution functions of likelihood ratio tests for cointegration. Journal of applied Econometrics, 14(5), 563-577.Moody's. Coronavirus-related disruptions to airline industry affect broad swath of global economy New York, July 16, 2020.Qadan, M., & Idilbi-Bayaa, Y. (2020). Risk appetite and oil prices. Energy Economics, 85, 104595.Sari, R., Soytas, U., & Hacihasanoglu, E. (2011). Do global risk perceptions influence world oil prices?. Energy Economics, 33(3), 515-524.Sharma, G., Kayal, P., & Pandey, P. (2019). Information linkages among BRICS countries: empirical evidence from implied volatility indices. Journal of Emerging Market Finance, 18(3), 263-289.Sims, C. A. (1989). Models and their uses. American Journal of Agricultural Economics, 71(2), 489-494.Sims, C. A., Stock, J. H., & Watson, M. W. (1990). Inference in linear time series models with some unit roots. Econometrica: Journal of the Econometric Society, 113-144.Skalin, J. & Svirta, T. (1999). Another Look at Swedish Business Cycles. Journal of Applied Econometrics, 14(4), 359-378.Stock, J. H. (1987). Asymptotic properties of least squares estimators of cointegrating vectors. Econometrica: Journal of the Econometric Society, 1035-1056.Vogelsang, T. J. (1997). Wald-type tests for detecting breaks in the trend function of a dynamic time series. Econometric Theory, 13(6), 818-848.Wen, F., Xiao, Y., & Wu, H. (2019). The effects of foreign uncertainty shocks on China’s macro-economy: Empirical evidence from a nonlinear ARDL model. Physica A: Statistical Mechanics and its Applications, 532, 121879.West, K. D. (1988). Asymptotic normality, when regressors have a unit root. Econometrica: Journal of the Econometric Society, 1397-1417.