The effectiveness of hedge fund strategies and managers’ skills during market crises: a fuzzy, non-parametric and Bayesian analysis
- Authors: Mwamba, John Muteba
- Date: 2012-11-05
- Subjects: Bayesian statistical decision theory , Hedge funds , Executive ability
- Type: Thesis
- Identifier: uj:7334 , http://hdl.handle.net/10210/8083
- Description: Ph.D. , This thesis investigates the persistence of hedge fund managers’ skills, the optimality of strategies they use to outperform consistently the market during periods of boom and/or recession, and the market risk encountered thereby. We consider a data set of monthly investment strategy indices published by Hedge Fund Research group. The data set spans from January 1995 to June 2010. We divide this sample period into four overlapping sub- sample periods that contain different economic market trends. We define a skilled manager as a manager who can outperform the market consistently during two consecutive sub-sample periods. To investigate the presence of managerial skills among hedge fund managers we first distinguish between outperformance, selectivity and market timing skills. We thereafter employ three different econometric models: frequentist, Bayesian and fuzzy regression, in order to estimate outperformance, selectivity and market timing skills using both linear and quadratic CAPM. Persistence in performance is carried out in three different fashions: contingence table, chi-square test and cross-sectional auto-regression technique. The results obtained with the first two probabilistic methods (frequentist and Bayesian) show that fund managers have skills to outperform the market during the period of positive economic growth (i.e. between sub-sample period 1 and sub-sample period 3). This market outperformance is due to both selectivity skill (during sub-sample period 2 and sub-sample period 3), and market timing skill (during sub-sample period 1 and sub- sample period 2). These results contradict the EMH and suggest that the “market is not always efficient,” it is possible to make abnormal rate of returns.However, the results obtained with the uncertainty fuzzy credibility method show that dispite the presence of few fund managers who possess selectivity skills during bull market period (sub-sample period 2 and sub-sample period 3), and market timing skills during recovery period (sub-sample period 3 and sub-sample period 4); there is no evidence of overall market outperformance during the entire sample period. Therefore the fuzzy credibility results support the appeal of the EMH according to which no economic agent can make risk-adjusted abnormal rate of return. The difference in findings obtained with the probabilistic method (frequentist and Bayesian) and uncertainty method (fuzzy credibility theory) is primarily due to the way uncertainty is modelled in the hedge fund universe in particular and in financial markets in general. Probability differs fundamentally from uncertainty: probability assumes that the total number of states of economy is known, whereas uncertainty assumes that the total number of states of economy is unknown. Furthermore, probabilistic methods rely on the assumption that asset returns are normally distributed and that transaction costs are negligible.
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Test of herding behaviour in the Johannesburg stock exchange : application of quantile regression model
- Authors: Ababio, Kofi Agyarko , Mwamba, John Muteba
- Date: 2017
- Subjects: Asymmetry , Herding Behaviour , Quantile Regression Model
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/250909 , uj:26156 , Citation: Ababio, K.A. & Mwamba, J.M. 2017. Test of herding behaviour in the Johannesburg stock exchange : application of quantile regression model. Journal of Economic and Financial Sciences, 10(3):457-474.
- Description: Abstract: The current study searches for evidence of herding behaviour in South Africa’s financial industry using an alternative approach. As a departure from the conventional test methodologies, the current study adopts the quantile regression model in estimating the empirical data on daily stock returns from January 2010 to September 2015. Employing the median as an alternative measure of average market portfolio returns, the study finds evidence of herding behaviour in the banking and real estate sectors during the sample period. Herding behaviour shows asymmetry and investors in the banking sector exhibit the herding behaviour when the market is falling (bear phase), whereas in the real estate sector, investors exhibited the herding behaviour when the market is rising (bull phase). However, in the entire financial industry, the empirical results show evidence of herding behaviour only during the extreme market period (bull phase).
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