The behaviour of U.S. stocks to financial and health risks

Salissu, Afees and Raheem, Ibrahim and Eigbiremolen, Godstime (2020): The behaviour of U.S. stocks to financial and health risks. Forthcoming in: International Journal of Finance and Economics

Abstract

This article examines the hedging effectiveness of U.S. stocks against uncertainties due to equity market (financial risk) and pandemics (health risk), including Covid-19 pandemic. Consequently, we consider two categories of U.S. stocks—defensive and non-defensive stocks drawn from 10 different sectors and distinctly analysed over two data samples—pre- and post-Covid periods. We construct a predictive panel data model that simultaneously accounts for both heterogeneity and common correlated effects and also complementarily determine the predictive power of accounting for uncertainties in the valuation of U.S. stocks. We find that hedging effectiveness is driven by the types of stocks and measures of uncertainty. Defensive stocks provide a good hedge for pandemic-induced uncertainty, and the hedging effectiveness is higher during calm market conditions as compared to turbulent conditions, while both categories lack hedging capability in the face of equity-induced uncertainty. Finally, we find that the inclusion of uncertainty in the predictive model of U.S. stock returns improves its forecasts and this conclusion is robust to alternative measures of uncertainty and multiple forecast horizons.

• Item Type: MPRA Paper
• Language: English
• Keywords: Covid-19, defensive stocks, forecast evaluation, non-defensive stocks, pandemics, panel data, uncertainty, U.S. stocks
• Subjects: F - International Economics > F1 - Trade > F15 - Economic Integration; G - Financial Economics > G1 - General Financial Markets > G10 - General

References

Abul Basher, S., & Sadorsky, P. (2016). Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH. Energy Economics, 54, 235–247.

Arnold, S., & Auer, B. R. (2015). What do scientists know about inflation hedging? The North American Journal of Economics and Finance, 34, 187–214.

Arouri, M., Estay, C., Rault, C., & Roubaud, D. (2016). Economic policy uncertainty and stock markets: Long-run evidence from the US. Finance Research Letters, 18, 136–141.

Asness, C. S., Frazzini, A., & Pedersen, L. H. (2014). Low-risk investing without industry bets. Financial Analysts Journal, 70 (4), 24–41.

Badshah, I., Demirer, R., & Suleman, M. T. (2019). The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging. Energy Economics, 84, 104553. https://doi.org/10.1016/j.eneco.2019.104553

Baker, S. R., Bloom, N., Davis, S. J., & Terry, S. J. (2020). Covidinduced economic uncertainty (No. w26983). National Bureau of Economic Research.

Baker, S., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. Quarterly Journal of Economics, 131(4), 1593–1636.

Baldwin, R., & di Mauro, B. W. (2020). Economics in the Time of COVID-19. A VoxEU. org Book. London: Centre for Economic Policy Research.

Bannigidadmath, D., & Narayan, P. (2015). Stock return predictability and determinants of predictability and profits. Emerging Markets Review, 26, 153–173.

Blitz, D. C., & van Vliet, P. (2007). The volatility effect. The Journal of Portfolio Management, 34(1), 102–113.

Bloom, N. (2014). Fluctuations in uncertainty. Journal of Economic Perspectives, 28(2), 153–176.

Chudik, A., Mohaddes, K., Pesaran, M. H., & Raissi, M. (2016). Long-run effects in large heterogeneous panel data models with cross sectionally correlated errors. Advances in Econometrics, 36, 85–135.

Chudik, A., & Pesaran, M. H. (2015). Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics, 188(2), 393–420.

Clark, T. E., & West, K. D. (2007). Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics, 138, 291–311.

Devpura, N., Narayan, P. K., & Sharma, S. S. (2018). Is stock return predictability timevarying? Journal of International Financial Markets, Institutions, and Money, 52, 152–172.

Ditzen, J. (2018). Estimating dynamic common correlated effects in Stata. The Stata Journal, 18(3), 585–617.

Ditzen, J. (2019). Estimating long run effects in models with crosssectional dependence using xtdcce2 (CEERP Working Paper Series: 7).

Drechsler, I. (2013). Uncertainty, time-varying fear, and asset prices. The Journal of Finance, 68, 1843–1889.

Fang, L., Qian, Y., Chen, Y., & Yu, H. (2018). How does stock market volatility react to NVIX? Evidence from developed countries. Physica A: Statistical Mechanics and its Applications, 505, 490–499.

Gordon, J. & Knowles, J. (2019). What's a defensive stock in 2020? Retrieved from https://www.capitalgroup.com/apac/capitalideas. Kuepper, J. & Scott, G. (2020). CBOE Volatility Index (VIX) Definition. Retrieved from https://www.investopedia.com/terms/v/vix.asp.

Ludvigson, S.C., Ma, S. and Ng, S. (2017). Uncertainty and business cycles: Exogenous impulse or endogenous response? (NBER Working Paper, No 2018), p. 21803.

Narayan, P. K., & Gupta, R. (2015). Has oil price predicted stock returns for over a century? Energy Economics, 48, 18–23.

Narayan, P. K., Phan, D. H. B., Sharma, S. S., & Westerlund, J. (2016). Are Islamic stock returns predictable? A global perspective. Pacific-Basin Finance Journal, 40(A), 210–223.

Novy-Marx, R., & Velikov, M. (2016). A taxonomy of anomalies and their trading costs. The Review of Financial Studies, 29(1), 104–147.

OECD. (2020). Coronavirus: The world economy at risk. OECD Interim Economic Assessment.

Qadan, M., Kliber, D., & Chen, N. (2019). Idiosyncratic volatility, the VIX and stock returns. North American Journal of Economics and Finance, 47, 431–444.

Reese, S., & Westerlund, J. (2016). PANICCA - PANIC on crosssection averages. Journal of Applied Econometrics, 31(6), 961–981.

Salisu, A. A., Akanni, L. A., & Raheem, I. D. (2020). The COVID-19 global fear index and the predictability of commodity price returns. Journal of Behavioral and Experimental Finance. https://doi.org/10.1016/j.jbef.2020.100383.

Salisu, A. A., & Isah, K. O. (2017). Revisiting the oil price and stock market nexus: A nonlinear panel ARDL approach. Economic Modelling, Elsevier, 66(C), 258–271.

Salisu, A. A., Isah, K. O., & Raheem, I. D. (2019c). Testing the predictability of commodity prices in stock returns of G7 countries: Evidence from a new approach. Resources Policy, 64, 1–20. https://doi.org/10.1016/j.resourpol.2019.101520.

Salisu, A. A., & Ndako, U. B. (2018). Modelling stock price–exchange rate nexus in OECD countries: A new perspective. Economic Modelling, Elsevier, 74(C), 105–123.

Salisu, A. A., Raheem, I. D., & Ndako, U. D. (2019). A sectoral analysis of asymmetric nexus between oil price and stock returns. International Review of Economics and Finance, 61, 241–259.

Salisu, A. A., & Sikiru, A. A. (2020). Pandemics and the Asia-Pacific Islamic stocks. Asian Economics Letters, 1(1). https://doi.org/10.46557/001c.17413.

Salisu, A. A., Swaray, R., & Oloko, T. F. (2019). Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables. Economic Modelling, 76, 153–171.

Salisu, A. A., & Vo, X. V. (2020). Predicting stock returns in the presence of COVID-19: The role of health news. International Review of Financial Analysis, 71(2020), 101546.

Segal, G., Shaliastovich, I., & Yaron, A. (2015). Good and bad uncertainty: Macroeconomic and financial market implications. Journal of Financial Economics, 117(2), 369–397.

Sharif, A., Aloui, C., & Yarovayac, L. (2020) COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the waveletbased approach. International Review of Financial Analysis. https://doi.org/10.1016/j.irfa.2020.101496.

Su, Z., Fang, T., & Yin, L. (2017). The role of news-based implied volatility among US financial markets. Economics Letters, 157, 24–27.

Su, Z., Fang, T., & Yin, L. (2019). Understanding stock market volatility: What is the role of U.S. uncertainty?. The North American Journal of Economics and Finance, 48, 582–590.

Westerlund, J., Karabiyik, H., & Narayan, P. (2016). Testing for predictability in panels with general predictors. Journal of Applied Econometrics, 32, 554–574. https://doi.org/10.1002/jae.2535.

Westerlund, J., & Narayan, P. (2016). Testing for predictability in panels of any time series dimension. International Journal of Forecasting, 32(4), 1162–1177.

Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 101, 528.