Country risk components and financial asset markets interdependence: evidence from South Africa.
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Date
2023
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Abstract
Over the last few decades, financial markets have become more interlinked. As a result, there has been an increased demand for information across markets and thus, a need for country-specific risk ratings. Risk ratings are vital for attracting investments and capital inflows in financial markets by providing signals regarding a country’s economic, financial and political fundamentals. However, there remains a lack of consensus on the nature of the relationship between country risk and key asset markets, namely, the stock market, bond market, housing market, and gold and oil markets.
This doctoral study evaluates the impact of country risk components on asset returns and their interlinkages for the period from February 2000 to December 2019 within the South African context. The first analytical paper (presented in Chapter 3) evaluates the dynamic relationship between South African asset markets using the Markov Switching Vector Autoregressive (MSVAR) model. The findings showed that the response of all asset returns to shocks in the economic system was regime-dependent. Moreover, shocks emanating from the exchange rate market and bond market explained most of the variation in the bull and bear regimes.
The second paper (presented in Chapter 4) investigates the impact of country risk on various asset markets ing a Non-Linear Autoregressive Lag model (NARDL). This study fills the gap in understanding the reaction of stock, bond, housing, currency, gold and oil markets to positive and negative innovations in country risk components. The findings show evidence of long-run cointegrating relationships between asset returns and country risk components and indicate that country risk components are effective determinants of domestic asset market returns.
The third paper (presented in Chapter 5) examines the effects of economic, financial and political risk on asset market linkages using a combination of the Dynamic Conditional Correlation Generalised Autoregressive Conditional Heteroscedasticity (DCC-GARCH) and NARDL models. The findings show that the correlation between asset markets was positive in stable market conditions and showed negative comovements during periods of market turmoil. Financial and political risk ratings were found to be the main drivers of asset market comovements in the short run. An
increase in South African (domestic) political risk had a larger effect in the long run and was found to be an important determinant of asset return comovements. This result provides evidence suggesting that asset markets are informationally inefficient and changes in financial and political risk ratings can be used to predict price movements.
Overall, this doctoral dissertation’s findings highlight the diversification benefits of domestic assets during periods of market uncertainty. Moreover, the results show that examining the different components of country risk provides better insight into the impact of country risk on asset markets. The results of this dissertation have significant implications for asset allocation decisions and risk management. From a policy perspective, it is crucial to formulate policies that address political instability as it plays a pivotal role in determining asset return behaviour, and consequently, the financial stability of the country. Furthermore, the results have implications for traditional asset pricing models that only capture the effects of market risk to predict future asset market behaviour. A more comprehensive understanding of the risks of specific markets is vital for more informed financial decision-making. Future research could extend the scope of the study to investigate the composite political risk factors that explain asset market behaviour.
Description
Doctoral Degree. University of KwaZulu-Natal, Durban.