Linkages among energy price, exchange rates and stock markets: Evidence from emerging African economies

ABSTRACT

This study examines the dynamic links among oil prices, foreign exchange rates and stock markets in emerging Africa using recent 10 years data and VAR-BEKK-GARCH forecasting framework. We find evidence of significant return and volatility interactions in oil return, exchange rates and stock markets. The non-existence of long-term cointegration equilibrium implies potential diversification benefit in the long run. Autoregressive characteristics for most African foreign currencies and stock markets indicate markets’ own predictability. We see that high oil return leads to an appreciation of Botswana pula, Nigerian dollar and Zambian kwacha, depreciation of Egyptian pound and boost the stock markets of Egypt, Kenya, Nigeria and Tunisia. From the conditional variance equation, we observe significant statistical evidence of local spillover effects from oil to financial markets. Strong bi-directional shock and volatility spillovers between oil and most African exchange rates are reported. Significant shock and volatility spillovers between oil and stock markets are found in some of the African countries. We conduct portfolio optimization analyses as part of the financial risk management and risk mitigation strategies. Policy wise, leaders should promote the development of financial derivative instruments since foreign exchange rates are used as a tool to absorb oil and other external shocks.

KEYWORDS:

• Oil price shocks
• foreign exchange rates
• stock market returns
• market volatility

JEL CLASSIFICATION:

• G14
• G15
• Q43

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Specifically, an enhancement in equity returns increases the wealth of domestic investors, motivating them to demand more domestic assets. This will lead to an increase in interest rates, resulting in an appreciation of the domestic currency.

² BRVM represents Bourse Régionale des Valeurs Mobilières, a regional stock exchange serving the following west African countries: Côte d’Ivoire, Benin, Burkina Faso, Guinea Bissau, Mali, Niger, Senegal and Togo.

³ We use the following exchange rates and stock indices for each country: Botswana: Botswana pula, Botswana Stock Exchange Domestic Company Index; BRVM: West African CFA franc, BRVM Composite Index; Egypt: Egyptian pound, EGX 30; Ghana: Ghanaian Cedi and GSE Composite Index; Kenya: Kenyan shilling, NSE20; Morocco: Moroccan dirham, Morocco All Share Index; Namibia: Namibian Dollar, NSX Local Index; Nigeria: Nigerian naira, Nigeria All Share Index; South Africa: South African rand FTSE/JSE Africa All Share Index (JALSH); Tunisia: Tunisian dinar, TUNINDEX and Zambia: Zambian kwacha, Lusaka All Share Index.

⁴ The data for Ghana is from 4 January 2011 to 30 December 2016.

⁵ We only exclude weekends, New Year’s Day and Christmas day.

⁶ The results of these two unit root tests are provided on request.

⁷ If the time series need to be differenced d times before it becomes stationary, we can say that these time series are integrated of order d and denoted as X_t ̴ I(d).

⁸ The off-diagonal elements of matrix A($a_{ij}$) capture the shock spillover effects from market i to market j. Similarly, the volatility spillovers are measured by the off-diagonal elements of matrix B($b_{ij}$).