Analysis of South Africa’s financial market relationship with business cycle indicators for financial stability
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Various developments spearheaded by social, political and economic behaviour have shaped both the soundness and the vulnerability of the market economy through direct and indirect mechanisms. Retrospective observation of past and present economic and financial patterns indicate that the economy undergoes alternating phases, characterised by periods of recessions and expansions caused by different factors. Knowledge and understanding of such patterns, their basic and scientific nature as well as their causes and potential indicators, has proved to be socially, politically and economically profitable for policy setting, including the uplifting of the social and economic agendas. To prevent or, at least, curb or mitigate the potential effects of likely financial crises, which may resultantly affect both the financial and real economy, it is important that a large contingent of economic agents, specifically investors, scholars and practitioners, predict behavioural dynamics of market fluctuations and their potential ramifications. For an emerging economy such as South Africa’s, ensuring the stability of the financial sector is critical for avoiding further economic stagnation amid pre-existing heightened unemployment, poverty and inequality as well as relatively low growth trajectories. This study examined the co-movement or the explanatory capacity of South Africa’s subcomponent variables of the composite business cycle indicators (BCIs) in explaining the behaviour and patterns of the financial market. Specifically, the financial market’s capital markets included the stock, bond and commodity and exchange rate markets. The aim of the research was to identify whether the component series of the composite BCIs can serve as leading, lagging or coinciding indicators of each of the capital market segments. A diverse set of econometric models and methods were employed. These included the cross-correlations test, the Granger causality model, variance decomposition, the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) process, and an autoregressive distributed lag (ARDL) model. Results revealed that South Africa’s official component series of the composite BCIs have explanatory power over the capital market segments. Based on the observation of turning points showcased by the chart analysis, varying time-series of the BCIs were identified to exhibit leading, lagging and coinciding properties with the stock, bond, commodity and exchange rate market. Accordingly, these indicators provided causal signals of the various capital markets with cyclical attributes of pro-cyclicality and counter-cyclicality with the capital markets. Nevertheless, a small sample of BCIs were acyclical to the market segments. Findings of concordance between identified leading series of each capital market were at least reiterated by the analysed short and long-run cointegration analysis based on the ARDL model. The study conclusively established that South Africa’s official subcomponents of the composite BCIs are not only valuable resource indicators on a macroeconomic context, they are also key signals for the interpretation of financial market or capital market analysis. These indicators can thus be useful in formulating macroprudential or monetary policy for maintaining financial market stability and are not limited to mere macroeconomic policy. The combined use of both financial and real economic time-series for financial market analysis can amplify the understanding of turning points of the stock, bond, commodity and exchange rate. Likewise, component series of the composite BCIs can also be used by investors in gauging the market sentiments for sound and value judgement to increase profitability. Thus, business cycle aggregates cannot only serve as a reflection of the real economy, but also, as a metric and gauge for financial sector dynamics and attitudes.
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