This research investigates the interrelation impact between oil price volatility and bilateral exchange rate volatility of selected oil – dependent countries and the causality pattern between them in the pre – and post 2008 -2009 global financial recession. Exchange rate volatility is for economies that are dependent on oil either for major industrial activities or for fiscal revenue. Thus, currencies exchange rates volatility examined in the study are for the Ghana cedi, Nigeria naira, South Africa rand, India rupee, Russia ruble; the euro and crude oil price is for West Texas Intermediate (WTI). Oil price volatility and exchange rate volatility are estimated using nonlinear models and interrelation impact between estimated volatilities as well as the causality pattern were done through linear models.
Empirical findings revealed both unidirectional and bidirectional impact between oil price volatility and exchange rate volatility for major oil dependent countries (Russia ruble and Nigeria naira, Ghanaian cedi and Nigeria naira). This impact was particularly confirmed in the post crisis period, which was not too surprising because higher volatility in oil price and exchange rate was evident in that same period (see Appendix B, Panel B). However, Granger causality test confirmed this relationship particularly in the post crisis period.
Keywords: Oil price volatility, Exchange rates volatility, Vector Autoregressive (VAR), GARCH, Exponential GARCH, Granger Causality, Pre-Financial Crisis, Post Financial Crisis.
CHAPTER ONE INTRODUCTION
Background of the Study
Countries all around the world, both developed and developing, depend heavily on crude oil for industrial production of goods and services and also, for fiscal revenue. Crude oil price and its volatility which are usually caused by factors such as demand and supply forces, geographical disturbances among others are at core of most countries’ economic activities. Literature have empirically shown that oil price volatility is correlated with changes in macroeconomic variables such as Gross Domestic Product (GDP), exchange rates, unemployment, interest rates and inflations, (Shaari, Hussain & Rahim, 2012; Ling & Jones, 2011; Basher, Hang & Sadorsky, 2012; Blanchard & Gali, 2007). An increase in crude oil prices contributes significantly to the development of economies through the transfer of wealth among oil dependent economies in a form of trade balance which leads to trade disequilibrium (Amano &Van Norden, 1998). The disequilibrium in trade results in high exchange rates volatility, especially for oil importing economies. Over the years, the United States dollar remains the most widely used currency for trading crude oil in the international market. In view of this, one will expect that fluctuations in the value of the US dollar will have a significant impact on crude oil prices and consequently, have an impact on economies that depend heavily on crude oil, especially for revenue generation. In other words, oil exporting economies whose currencies’ value are pegged to the value of the US dollar in a floating exchange rate system are affected by the volatility of the United States dollar. For such economies, their fiscal revenue from crude oil exports may be affected which may in turn affect the efficacy of their local currencies relative to the US dollar in a floating
exchange rate system, even with a stable supply of oil. For economies that are major crude oil importers whose local currencies’ values are pegged to the value of the dollar in floating exchange rate system, their cost of production fluctuates with the US dollar exchange rates volatility. In essence, the economic development vis-𝑎̀-vis currencies performance of oil
dependent economies is exposed to the risks that are associated with the volatility of the United
States dollar in a floating exchange rate system.
Studies by Ding and Vo (2012), Reboredo (2012), Salisu and Mobolaji (2013) have documented that, oil price–exchange rates volatility link appears to be either weak or no relationship of such existed in the period preceding the start of the 2007 global financial crisis. However, they documented confirmation of such relationship during the 2007 global financial crisis period. Despite the attempts of these studies to probe the link between the volatilities of oil price and exchange rates, they utilized currency index which tends to neutralize the behavioural characteristics of each currency; such characteristics may include the extent of development of a particular economy or the degree of dependency on oil by these economies. The use of currency index is not able to depict the performance and the strength of each economy’s currency against the US dollar in a floating exchange rate system when external shock strikes. This study expands existing literature of the impact that exist between the volatilities of oil price and exchange rates by adopting the currency exchange rates of six oil dependent economies and analysing how the volatilities in these countries exchange rates respectively relates with oil price volatility before and after the 2007 global financial crisis period. The currencies exchange rates volatility to be examined against oil price volatility include the European union euro, Nigerian naira, Indian rupee, Russian ruble, Ghanaian cedi and South African rand. Dependency on oil by these
economies may be either because fiscal revenue generation is heavily dependent on oil exports or industrial activities are primarily dependent on crude oil imports.
In addition, the causality nexus between oil price and exchange rate has been researched in literature. However, the nature (i.e. linear or nonlinear) and the causality direction documented in literature between these two markets are unconfirmed. Some studies empirically adopted the traditional Granger causality test which is centred on Vector Autoregressive (VAR) model and introduced by Granger (1969) and Sim (1972) to examine the linear causal relationship between these two markets. These studies, despite their different conclusions on the causality pattern between these two markets, documented evidence of linear causality between oil price and exchange rates (Amano & Van Norden, 1998; Tentatape, Jui-Chin & Yaya, 2015; Lizardo & Mollick, 2010). However, the findings of other empirical studies have criticized the Granger causality test as a technique that observed the ignorance of a common information factor (the volatility effect) which ends up in spurious conclusions. Moreover, they proposed the application of nonlinear techniques when using the Granger causality test that is inferred parametrically through autoregressive models, to examine the causal relationship between time series data. In this way, while the former captures the volatility effects in the series, the later establishes the causal relationship in the context of linear regression models of stochastic processes (Bell, Kay, & Malley, 1996; Asimakopoulos, David & Wan, 2000; Peguin–Feissolle, Strikholm & Terasvirta, 2008). In view of this, the study employs the Granger Causality test and the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) proxies as linear and nonlinear techniques respectively in investigating the causality link between oil price volatility and exchange rates volatility. Although the Granger causality test has been criticized in literature, it is applied in this study because it is proven in literature to be pragmatic, robust and
standard tool to reveal causal relationships in the context of linear regression models of stochastic processes (Granger, 1980; Hu & Liang, 2014; Friston, Stephan, Montague & Dolan, 2014). In addition, the application of GARCH proxies to generate the volatility series of oil price and exchange rates, will cushion the Granger Causality test against its defect to account for the volatility effect in the series. In other words, the GARCH proxies used as nonlinear technique in the study will neutralize the Granger causality test’s defect and provide a firm ground for its application.
The complexity of oil price volatility in the international market and its continuing sensitive impact on macroeconomic variables such exchange rates in high oil dependent economies, makes its relevant for academic cross–examination. Hence, the study first employed the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) proxies to generated the volatility series of oil price and the various currencies exchange rates. Secondly, the concept of Vector Autoregressive (VAR) model is employed to obtain the interrelation impact between oil price volatility and exchange rates volatility of the selected oil dependent economies. Lastly, the Granger Causality test is used to ascertain the linear impact interrelationship results.
In the middle of 2007, the United States financial market begun to slip into a disastrous moment of financial crisis since the Great recession of the early 1930’s (Tharkor, 2015). The moment of crisis in United States led to the collapse of many financial institutions including the Lehman Brothers. Indeed, literature have established that, after the ceased of the global economic depression in 2010, West Texas Intermediate (WTI) crude oil price started declining steadily, dipping as low as 28 US dollars per barrel in February 2016, during that same time, the value of
the United States dollar surged significantly contrary to most floating currencies including the cedi, euro, naira, rupee, rand and the ruble. Earlier in July 2008, crude oil price was traded at more than 145 US dollars per barrel (Reboredo, 2012; Mensah, Obi & Bopkin, 2017). Since the US dollar remains the most widely used currency for pricing crude oil, the contemporaneous rise of the US dollar and fall of oil prices in the post crisis period makes it prying into the contribution of oil price to the surged of the US dollar in the post crisis period. Hence, this study sought to unravel the contribution of oil price volatility to the significant surge of the US dollar against most floating currencies after the 2007 global crisis, with focus on the currencies listed above.
In addition, majority of empirical literature that investigated exchange rate–oil price link mainly focused at price level, whether high or low, rather than volatility (Wirjanto & Yousefi, 2004; Zhang, Fan, Tsai & Wei, 2008; Groen & Pesenti, 2010). According to Clark (1973) and Ross (1989), asset volatility is associated with market interaction in terms of information flow. Thus, exchange rate–oil price link should appear not in price levels but in terms of volatility. This necessitated studies that probe into how oil price volatility and exchange rate volatility interact to provide better insight for traders and regulators in these two markets. In this way, the traders will not only consider to their expected returns from their business activities but also their business strategy’s vulnerability or exposure to risk in the period of severe volatility in the market. It is worth pointing out that some studies have investigated the link between oil price and exchange rates in terms of their volatilities in literature (Ding & Vo, 2012; Salisu & Mobolaji, 2013; Phan, Sharma, & Narayan, 2016). As mentioned earlier in this research, these studies focused on the approach of US dollar index which tends to neutralize the dominance of each oil dependent economy’s specific currency against the dollar in the foreign exchange market; such dominance
could be influenced by their respective domestic economic activities. Also, the currency index approach is not able to explain the response of each currency’s exchange rate volatility to oil price volatility shock in literature. This study sought to fill this gap which has been abandoned by these studies in literature by investigating the respective response of each currency’s exchange rate volatility against oil price volatility. This approach unravels answers to how volatility in each oil dependent economy’s exchange rate reacts to the volatility in oil price which might be of interest in terms of forecasting and investment for market participants in their respective oil dependent economies.