This paper assesses the competitive environments of SSA banks with the view of analysing whether banks with market power profit from monetary policy. It employs various specifications of Lerner index as a measure of market power for 264 banks across 24 SSA countries. Tightening of monetary policy, high credit risk, risk aversion, and the high labour cost contribute to the high spread of banks in SSA. The results also reveal that a spread among banks with market power is significantly more sensitive to the monetary policy changes. The overall results suggest that banks in Africa gain from monetary policy shocks.
We investigate, for the first time, equity return overreaction and associated January effect in the Nigerian Stock Exchange (NSE); with both of these market anomalies also examined in the South African equity market (JSE), mainly to assess their likely persistence in the JSE. We find evidence of overreaction and seasonality in the NSE, in contrast to past studies that found the NSE to be weak form efficient. The overreaction in the NSE is also accompanied by January and June month-of-the-year effects. For the JSE, there is now no evidence of overreaction; thus, suggesting that overreaction may have been arbitraged away over time. Although, a January effect is still recorded in the JSE, it is an "October effect" that is now found to be robust. Importantly, the NSE shows evidence of congruity of return and investor sentiment, which suggests that investor sentiment, can explain seasonality of overreaction in the Nigerian market. Overall,our results point to useful policy and trading strategy guides for these two major regional equity markets of Africa.
This paper assesses the usefulness of monitoring market turbulence, return magnitude surprise and correlation surprise as potential signals to assist investors in timing de-risking strategies in the South African and African market settings. The analysis follows Kinlaw and Turkington (2014) who recently proposed the measures of magnitude and correlation surprise by decomposing the market turbulence measure. We find that in periods when correlation surprise spikes that in both the South African and African market environments subsequent periods are characterised by higher risk and lower returns. Our findings thus corroborate the predictive capability of the components of market turbulence.
This study uses the Auto-regressive Distributed Lag (ARDL) approach to cointegration to examine the short- and long-term dynamics of investors' herd behaviour at the JSE. The results from the ARDL model suggest that herding exists at the JSE. The study also noted that herd behaviour takes place with lapses in time; however the unrestricted error correction results suggest that such behaviour has a high speed of adjustment, implying that herding is a short-lived phenomenon. Since the direction of the market affects investors' behaviour, the study also investigated the asymmetric effects of herding behaviour during rising versus falling markets. While herding behaviour was identified during a rising market, the results did not support the presence of herd behaviour in a falling market.