Mutual funds behavior and risk-adjusted performance in Nigeria
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DOIhttp://dx.doi.org/10.21511/imfi.18(3).2021.24
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Article InfoVolume 18 2021, Issue #3, pp. 277-294
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The paper investigates the behavior of mutual funds and their risk-adjusted performance in the financial markets of Nigeria between April 2016 and May 31, 2019, using descriptive statistics, as well as CAPM, Jensen’s alpha, and other risk-adjusted portfolio performance measures such as Sharpe and Treynor ratios, as well as Fama decomposition of return. The descriptive tests revealed that 80.77% of the funds were superior to market returns, while 13.46% were riskier. The market and the fund returns behaved abnormally with asymptotic and leptokurtic characteristics as their skewness and kurtosis varied from the normal requirements. Diagnostically, the normality test by Jacque-Berra showed that the return was not normally distributed at a 1% significance level. The market was more aggressive relative to the funds. The average risk-free rate was 6.75% above the market’s return. The risk-adjusted portfolio returns measured by Sharpe and Treynor ratios showed that 67.31% of the funds underperformed the market compared to 40.38% that outperformed the market using Jensen’s alpha. Fama decomposition of return revealed that the fund managers are risk-averse with 48% superior selection ability and rationally invested over 85% of investors’ funds in schemes with fixed income securities at a given risk-free return that cushioned the negative effects of the systematic and idiosyncratic risks and consequently threw the total returns into positive territories. Overall, the fund managers possessed 52% of inferior selection abilities that only earned 33% of superior risk-adjusted returns and hence, failed to achieve the desired diversification in the relevant period.
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JEL Classification (Paper profile tab)G11, G12, G14, G41
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References43
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Tables9
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Figures1
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- Figure 1. Distribution of investment in mutual funds in Nigeria
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- Table 1. Fund managers, schemes, and net asset value as at May 31, 2019
- Table 1 (cont.). Fund managers, schemes, and net asset value as at May 31, 2019
- Table 2. Descriptive statistics of the mutual funds in Nigeria (April 2016 – May 2019)
- Table 3. Risk-adjusted performance of the schemes in Nigeria (January 2016 – May 2019)
- Table A1. Descriptive statistics of mutual funds in Nigeria (January 2016–May 2019)
- Table B1. Risk-adjusted returns of mutual funds in Nigeria (January 2016–May 2019)
- Table B1 (cont.). Risk-adjusted returns of mutual funds in Nigeria (January 2016–May 2019)
- Table C1. Fama decomposition of mutual funds returns (January 2016–May 2019)
- Table C1 (cont.). Fama decomposition of mutual funds returns (January 2016–May 2019)
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Estimating systematic risk for the best investment decisions on manufacturing company in Indonesia
Zarah Puspitaningtyas
doi: http://dx.doi.org/10.21511/imfi.14(1).2017.05
Investment Management and Financial Innovations Volume 14, 2017 Issue #1 pp. 46-54 Views: 1766 Downloads: 805 TO CITE АНОТАЦІЯEstimation of systematic risk is one of the important aspects of the best investment decisions. Through systematic risk prediction will be known risks to be faced by investors, because systematic risk is a measure of investment risk. In addition to returns, investors always consider the risk of investment, because investors are rational individuals, ie individuals who always consider the trade-off between return and risk. At a certain level of return, investors will tend to choose investments with the lowest risk level. Conversely, at a certain level of risk, investors tend to choose investments with the highest return rate. The purpose of this paper is to analyze the influence of the financial information on the systematic risk of stock manufacturing companies listed on the Indonesia Stock Exchange over a period of five years from January 2011 to December 2015. The financial information is measured in four accounting variables, i.e. financial leverage, liquidity, profitability, and firm size. The results of data analysis using multiple linear regression method to prove that at the 0.05 level only variable sized companies that significantly influence systematic risk. Meanwhile, the variable financial leverage, liquidity, and profitability does not affect the systematic risk. The results showed inconsistencies with the results of several previous studies. This inconsistency may be due to measurement problems variable accounting, the implementation period of the study, and the use of different research samples.
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On the causality analysis of the correlation between financial leverage and systematic risk: evidence from Indonesian Stock Exchange
Ibnu Qizam
doi: http://dx.doi.org/10.21511/imfi.14(4).2017.08
Investment Management and Financial Innovations Volume 14, 2017 Issue #4 pp. 73-89 Views: 1258 Downloads: 360 TO CITE АНОТАЦІЯThis research is aimed at analyzing the causality puzzle on the correlation between financial leverage and systematic risk (beta). Financial leverage and beta are usually considered as two proxies of risk derived from different domains: one ends at financial decision outcome, and the other points to market. Cross-sectionally, this result does not support the moderating-variable impact of size on the relation between financial leverage and systematic risk. On the other hand, however, the moderating-variable impact of industry and operating leverage (to some extent) on the relation between financial leverage and systematic risk were well documented. Inter-temporally, financial leverage is significantly and symmetrically related to beta, not moderated by size and operating leverage. This means that the two variables show bidirectional causality. This study contributes to the new insight that financial leverage and beta are the two variables with bidirectional causality, showing that in the long run, risks from fundamental (financial/micro-economy) and from market (macro-economy) are tightly linked to each other inter-temporally.
