Abstract
Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.
Highlights
Economic uncertainties, technological advancements, and globalization have made countries vulnerable to volatility (Eissa et al 2010)
We briefly review a number of articles on the relationship between exchange rates and stock prices from G7, Asian, and African countries that have employed different methodologies
To check for robustness, we investigated the comovement between the two variables using the quantile regression (QR) model
Summary
Technological advancements, and globalization have made countries vulnerable to volatility (Eissa et al 2010). Studies on interdependencies are important because they have direct implications on how information is transferred between financial markets and several practical implications to investors and policymakers (Tsagkanos and Siriopoulos 2013). Studies such as Caporale et al (2014) emphasised the interdependencies between foreign exchange and stock markets. This may partly be explained on one hand by the occurrence of several financial crisis, such as the US subprime crisis in 2007, characterised by a sharp drop in asset prices that severely affected the foreign-exchange market with large losses in international portfolios (Walid et al 2011; Caporale et al 2014) On the other hand, practical concerns of policymakers and questions left unanswered from theoretical models have motivated empirical studies on interdependencies between foreign exchange and stock markets (Eissa et al 2010)
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