عملکرد صندوق در تونس: یک روش GARCH چند متغیره

This article investigates mutual fund performance in the Tunisian capital market using conditional multifactor models. In the mutual fund literature, the traditional approach to capture conditionality is the use of predetermined instruments. This study proposes a multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approach to compute conditional measures. Overall, we find evidence of persistence in mutual fund performance only when we implement the multivariate GARCH method. This result is due to the fact that the Jensen alphas are estimated more precisely in the multivariate GARCH model than in the other approaches. These results indicate that the Tunisian capital market presents strong investment opportunities for sophisticated investors such as mutual funds.

There are many conflicting results in the literature as to whether mutual fund managers have superior information relative to the average investor. By investigating mutual fund performance in the Tunisian capital market, which is characterized by high asymmetric information, low liquidity and slow diffusion of information, we expect to get more decisive results confirming the presence of informed investors. In order to do so, we extend the bivariate GARCH model of Coggins et al. (2009) to a multivariate GARCH model; so that we can take into account other benchmarks in addition to the market. The empirical tests reveal that mutual funds outperform passive benchmarks only when we implement the multivariate GARCH model. When we restrict our sample to contain only bond funds, we document more compelling evidence bearing out the presence of informed managers. These results validate the main intuition of this article that the Tunisian capital market presents strong opportunities for informed investors such as mutual funds.