The accurate estimation of Value-at-Risk (VaR) has become central to the measurement and management of financial risk – in particular, the financial risk inherent in investing in stock markets. While the Gaussian distribution is known to provide an unsuitable read more

The accurate estimation of Value-at-Risk (VaR) has become central to the measurement and management of financial risk – in particular, the financial risk inherent in investing in stock markets. While the Gaussian distribution is known to provide an unsuitable depiction of daily asset returns, it is a well-established fact that returns taken weekly, monthly or quarterly exhibits (progressively) more Gaussian behaviour. This paper examines such aggregational effect in using two popular families of distributions, namely extreme value models and generalized hyperbolic models, for VaR estimation and contrasts their behaviours against the corresponding Gaussian estimates. The data sets used are returns of indices extracted from the NYSE, FTSE, KRX and TWSE

Infrastructure is widely considered an important determinant of firm performance but evidence on its importance on technical efficiency of hairdressers is very limited. Against this background, this study sought to compute and compare the technical efficiency read more

Infrastructure is widely considered an important determinant of firm performance but evidence on its importance on technical efficiency of hairdressers is very limited. Against this background, this study sought to compute and compare the technical efficiency levels of female hairdressers operating by the road side with those operating within formalised and designated salons. Primary cross-sectional data were collected using questionnaires and analysed within a quantitative research design. Technical efficiency was measured using a stochastic frontier technique which, in computing efficiency scores, separates the effect of random factors that are exogenous to the hairdressers. Based on a Cobb Douglas functional form chosen by relevant statistical tests, results from the stochastic frontier model estimated by the maximum likelihood confirm that hairdressers operating in designated saloons are more efficient when compared with hairdressers operating by the road side. A policy implication arising from this finding is that the provision of proper infrastructure is necessary to improve technical efficiency of hairdressers currently operating by the road side.

The growth of the African economy is increasing rapidly since the last decades, but those economic activities affect environmental quality. Researches have shown that an increase in economic activities would lead to environmental degradation which may read more

The growth of the African economy is increasing rapidly since the last decades, but those economic activities affect environmental quality. Researches have shown that an increase in economic activities would lead to environmental degradation which may eventually cause environmental collapse. In this study we intend to examine the relationship between CO2 emission as a proxy of the environmental quality and gross domestic product (GDP) as a proxy of economic growth in Africa, then to detect and compare the Environmental Kuznets Curve (EKC) between African economic groups. An annual data of forty-eight (48) African countries classified into four economic levels according to World-Bank classification: lower income, lower middle income, lower upper income, and higher income countries for the period between 1960 to 2014, using panel data regression technique. The main findings show that there is a significant positive relationship between CO2 emission and GDP in Africa, as one unit of GDP increase, CO2 emission will increase by 0.37 metric ton in the African continent. Moreover, the analysis shows the existence of the EKC hypothesis of an inverted U-shape curve for all African economic levels with a higher turning point in higher income countries.

The literature on the dynamics of inflation appears to have shifted from the question of the root cause of shocks to inflation, to whether the monetary union has a bearing in the measure of the degree or the persistence of the effect of the shocks. To capture read more

The literature on the dynamics of inflation appears to have shifted from the question of the root cause of shocks to inflation, to whether the monetary union has a bearing in the measure of the degree or the persistence of the effect of the shocks. To capture the specific effect of monetary policy shocks on the persistence of inflation in WAMZ, a multivariate Vector Autoregressive Moving Average GARCH (VARMAGARCH) framework is implemented. The study employs both conventional and conditional time-varying unit root tests to understand the extent to which monetary union influences the degree of inflation persistence. We find the degree of inflation persistence to have been relatively lower since the advent of monetary union in the WAMZ. The significance of this finding is particularly evident when the time-varying property of the persistence is captured. It is also observed that a monetary policy shock has the potential to neutralise the persistence of shocks to inflation at least in the long run, particularly when the timevarying property of the inflation series is captured.

Using a panel of South African banks covering the period from 2005 to 2015, we further develop, validate and test the liability mismatch index (LMI) developed by Bai, Krishnamurthy and Weymuller (2018). Deviating from their approach, we develop measures of read more

Using a panel of South African banks covering the period from 2005 to 2015, we further develop, validate and test the liability mismatch index (LMI) developed by Bai, Krishnamurthy and Weymuller (2018). Deviating from their approach, we develop measures of liquidity that integrate both market liquidity and funding liquidity. Two liquidity measures developed are the bank liquidity mismatch index (BLMI) and the aggregate liquidity mismatch index (ALMI) whose performances are compared and contrasted with the Basel III liquidity measures and traditional liquidity measures. Overall, the two constructed liquidity indices perform better than other liquidity measures. Unlike the LMI, the BLMI and ALMI can be used to evaluate the liquidity of a given bank under liquidity stress events. Our empirical results, though not significant, also show that banks increase their liquidity buffers during times of turmoil as both BLMI and ALMI improved during the period 2007–2009.

There has been increased interest in promoting export diversification as a means of ensuring sustainable growth in most developing countries. Yet, the arguments on the relationships between export diversity and economic growth is not settled in literature, read more

There has been increased interest in promoting export diversification as a means of ensuring sustainable growth in most developing countries. Yet, the arguments on the relationships between export diversity and economic growth is not settled in literature, with mixed findings concerning the sign and size of the correlation. This study assesses the relationship between export diversification and economic growth in selected Sub-Saharan African countries. Employing fixed effect and generalised least square regression models, with data from the World Bank, the findings show that a U-shaped relationship between export concentration and economic growth: the study finds a positive non-significant relationship for low-income countries, a positive and significant relationship for lower-middle-income countries and negative though not significant relationship for upper-middle-income countries.

This paper seeks to analyse how FDI from China, US, EU, and the rest of Asia transmit to growth in sub-Sahara Africa through export upgrading for the period (2003-2012). Terms-of-trade is utilized as a proxy for export upgrading. We develop a theoretical read more

This paper seeks to analyse how FDI from China, US, EU, and the rest of Asia transmit to growth in sub-Sahara Africa through export upgrading for the period (2003-2012). Terms-of-trade is utilized as a proxy for export upgrading. We develop a theoretical argument to show that countries with worsening (less than 1%) terms-of-trade are associated with poor industrialization as a result they can hardly improve quality and quantity of their products for export market, vis-àvis. In this respect, this study contributes to existing literature in two ways. First, we investigate if technology embodied in FDI from the above-mentioned sources can enhance quantity and quality improvements of export commodities in sub-Sahara Africa. Second, we account for industrial policy heterogeneity of sub-Sahara African countries in order to determine the threshold level at which FDI-induced export upgrading can contribute positively to growth. Using both 2SLS and PTR models, our results reveal that FDI from China and the rest of Asia does not bear significant impact on growth in sub-Sahara Africa through export upgrading. However, PTR analysis demonstrates that FDI from US and EU seem to have a significant negative impact only below a threshold of 1.08%. As the terms-of-trade improves beyond 1.08%, the estimated coefficients of both FDI from US and EU turn positive, albeit insignificant. We conclude that sub-Sahara African countries are far yet to reach a threshold at which FDI-induced export upgrading can contribute positively to growth.

This paper highlights the shortfalls of Modern Portfolio Theory (MPT). Amongst other flaws, MPT assumes that returns are normally distributed, that correlations are linear and risks are symmetrical. We propose a dynamic and flexible scenario-based approach to read more

This paper highlights the shortfalls of Modern Portfolio Theory (MPT). Amongst other flaws, MPT assumes that returns are normally distributed, that correlations are linear and risks are symmetrical. We propose a dynamic and flexible scenario-based approach to portfolio selection that incorporates an investor’s economic forecast. Extreme Value Theory (EVT) is used to capture the skewness and kurtosis inherent in asset class returns and account for the volatility clustering and extreme co-movements across asset classes. The estimation consists of using an asymmetric GJR-GARCH model to extract filtered residuals for each asset class return. Subsequently, a marginal cumulative distribution function (CDF) of each asset class is constructed by using a Gaussian-kernel estimation for the interior, together with a generalised Pareto distribution (GPD) for the upper and lower tails. The distribution of exceedance method is applied to find residuals in the tails. A Student’s t copula is then fitted to the data to induce correlation between the simulated residuals of each asset class. A Monte Carlo technique is applied to simulate standardised residuals, which represent a univariate stochastic process when viewed in isolation but maintain the correlation induced by the copula. The results are mean-CVaR optimised portfolios, which are derived based on an investor’s forward-looking expectation.

Accurate estimates of volatility are important for the valuation and risk management of financial assets. The benchmark interest rate for many assets in South Africa, the 3-month Jibar, is found to exhibit a high volatility persistence when modelled with a read more

Accurate estimates of volatility are important for the valuation and risk management of financial assets. The benchmark interest rate for many assets in South Africa, the 3-month Jibar, is found to exhibit a high volatility persistence when modelled with a standard generalised autoregressive conditional heteroskedasticity (GARCH) process. The literature suggests that unobserved regime-switching in interest rate data may lead to an overestimation of volatility persistence. In this study 120 GARCH-type volatility models are tested to determine which model, conditional distribution and number of regimes best fit the data in order to extract the most accurate in-sample estimation of historical volatility for asset pricing. The data analysed consists of 877 weekly observations of 3-month Jibar in total, spanning from September 2001 to July 2018. The switching between regimes is governed by a Markov chain process which produces state-dependent transition probabilities for the unobserved regimes. The study finds that a standard single regime GARCH model may not capture the underlying volatility dynamics of the interest rate. The best performing model in this study is the 4 State Threshold-GARCH indicating that in addition to evidence of regime-switching in the data, there is an asymmetric reaction to negative information.

This study estimates the effect of one charter school (a public-private partnership) on mathematics and reading comprehension among second grade students in Peru between 2007 and 2012. The study uses an identification strategy to estimate the causal effect of read more

This study estimates the effect of one charter school (a public-private partnership) on mathematics and reading comprehension among second grade students in Peru between 2007 and 2012. The study uses an identification strategy to estimate the causal effect of a charter school. The strategy is based on a natural experiment of an admission lottery to determine which students would be accepted into second grade at the charter school. The results show that the charter school achieved substantial gains in the scores of the lottery winners that are equivalent to 0.4 standard deviations. We also find that this effect has increased over time.