One of the on-going difficulties for finance practitioners is to out rightly prove or disapprove the concept of market efficiency because the constituents of the concept do not always reflect real financial markets. Market efficiency is an idle state that varies with time and may have dire consequences for active market participants. The aim of this study was to empirically investigate market efficiency before, during and after a period of financial distress. A BDSL non-linear dependency test was used to observe the logic distance between the observed pairs of returns and the expected pair vectors in stock prices for the JSE, Nasdaq, CAC 40, DAX, Nikkei 225 and BIST100. The findings revealed that market efficiency is a dynamic concept. Most financial markets under consideration show strong signs of efficiencies before and after financial distress. However, significant inefficiencies were observed during a bearish period probably due to fear and greed. Considering the dynamic nature of market efficiency, market participants may enhance the value of their portfolios by alternating their investment style accordingly. More specifically, investors should consider investing in index fund EFTs during periods of financial distress and adopt an active management strategy during bullish periods. Also, scarce liquidity seems to be the major cause of market inefficiency during periods of financial distress therefore, quantitative easing is strongly recommended during these episodes.
This paper examines the dynamic nexus of monetary and fiscal policy in South Africa with evidence from key macroeconomic economic indicators from 2000 quarter 1 to 2022 quarter 3. The Markov-switching dynamic regression is used in the Taylor theoretical framework. The contemplation is what type of monetary and fiscal policy mix in a different state of policy rate or repo rate. There is less attention to the analysis of the impact of fiscal policy macroeconomic variables in a different state of policy rate with the consideration of the lower bound and upper bound rate of inflation. The South Africa Reserve Bank's reaction to fiscal policy macroeconomic variables is significant in different states. Moreover, there is evidence of constant reaction of the South Africa Reserve Bank when inflation is at the lower and upper bound. The increase in the gross domestic product gap and inflation gap results in an increase in the rope rate. The result suggests that the monetary policy provided a supportive policy to fiscal policy macroeconomic variables. However, there is a state that reflects trade-offs in the current monetary and fiscal policy mix reaction. The fiscal policy needs to be adjusted to attain the desired target.
This study examines the extent to which crypto assets have moved to the mainstream by estimating the potential for spillovers crypto on bond and equity markets using daily data on price volatility and returns. The analysis reveals that the coefficients of the constant variance term, the ARCH and the GARCH parameters are positive and statistically significant at the 1% level across all models. In respect of the mean equation, the results suggest that the spill-over effects of bitcoin on equities and long-term bonds are ambiguous. Spillovers from price volatility of the oldest and most popular crypto asset, Bitcoin, to the S&P 500 and MSCI emerging markets indices have increased by about 12-16 percentage points since the onset of the COVID-19 pandemic, while those from its returns have increased by about 8-10 percentage points. This clearly indicates that the persistence of volatility shocks, as represented by the sum of the ARCH and GARCH parameter is large. Moreover, this suggests that the effect of today’s shock remains in the forecasts of variance for many periods in the future.
We empirically investigate the effects of financialization on economic growth in South Africa. The country experienced increases in the share of the financial sector since the democratic dispensation. This country is also one of the few developing countries with a large financial market. The sample period includes a long-run horizon from 1994 to 2021. The study applies quantile regression methodology which we use to explain the effects of financialization at different levels of economic growth. We estimate the effects of financialization at the 25th, 50th, 75th percentile of economic growth. The key measure of financialization is the finance gross value added and the measure of economic growth is the gross domestic product. We find that financialization has a significantly high and positive effect only at all the levels of economic growth. From the different percentiles, financialization contributes more to higher levels of economic growth.
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