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After the financial crisis of 2008, it was clear that investors were craving more transparency, liquidity and protection. Hedge fund managers saw an opportunity in the UCITS directive to launch UCITS compliant hedge funds and hedged mutual funds under the Investment Company Act of 1940. Previous studies have shown that the performance of funds drives the capital flows but no research has yet discovered whether the flows of liquid hedge funds and pure hedge funds are driven by their respective past performance. Using two different asset pricing models and a panel regression, this research suggests that liquid hedge funds are more sensitive to hedge funds' performance while hedge fund investors do not appear to react to positive liquid hedge funds' performance.
hedge fund --- mutual fund --- performance --- flow --- manager skills --- alternative investments --- UCITS --- panel regression --- Sciences économiques & de gestion > Finance
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Persistence in mutual funds’ performance is a subject that has been highly debated among the literature. No consensus has been reached yet and most of the work related to the topic have been done on U.S. markets. However, due to the recent development in European market importance, it becomes easier and more relevant to study this market as well. Persistence in performance has important consequences from an economic and practical perspective, if persistence is proven to be existing, then it represents a serious challenge to market efficiency, and it could also represent an important screening mechanism for investors. This thesis will study the performance of active domestic equity funds in Europe, focusing on 5th countries that are France, Germany, Italy, Netherlands, and Spain. First, a review of the literature regarding market efficiency, active management, and performance persistence in the U.S. and in Europe is performed, then a quick summary about the dataset is described and then we explain the methodology that will be used. Finally, empirical results are analyzed. To perform the analysis, we use several multi-factor models to calculate performance, as well as the use of the False Discovery Rate (FDR) to identify funds with a truly significant alpha and to eliminate the chance factor. In addition, we also use a non-parametric approach by using the Winner-Loser test and performing statistical tests on its results. The first objective of this paper is to give an overview on the efficiency of European markets and the existence of "Skill" among mutual fund managers by also testing whether past performance can give information on future performance (if the existence of persistence is proven). And the second objective would be to study the performance of domestic funds knowing that there is a cognitive bias for investors called "home bias" which pushes investors to overweight domestic investments compared to international investments, and to know if this bias is motivated by an "informational advantage" or if it is simply motivated by the familiarity that investors have with these companies and would therefore be an irrational choice.
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Performance analysis of hedge funds has proven to be challenging in the past since these entities have the flexibility to choose between a wide variety of dynamic trading strategies without being compelled to report their holdings. That being said, using bootstrap procedures, some authors in the academic literature have succeeded in quantifying the proportion of funds which demonstrates persistent performance. Yet, these methodologies are based on an extensive range of multifactor models to estimate the performance of hedge funds. Four different models which seem particularly adapted to assess hedge fund returns will be replicated, with both buy-and-hold and optional factors incorporated. The research aims at demonstrating the potential bias and/or outperformance brought by some factor models used when defining hedge fund manager skills. Using robust bootstrap simulations, evidence was found that superior hedge fund performance cannot be explained by luck alone and that, regardless of the multifactor model used.
hedge funds --- performance --- risk/return --- bootstrap procedure --- false discoveries --- dynamic trading strategies --- multifactor model --- manager skills --- luck --- Sciences économiques & de gestion > Finance
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Personnel management --- Technological innovations. --- Information technology. --- Employee experience. --- HR tech. --- Employee skills. --- Hybrid working. --- People analytics. --- Metaverse. --- Generative AI. --- Employee well-being. --- Diversity, equity, and inclusion. --- Fairness at work. --- Ethics in AI. --- Ethics at work. --- HR ethics. --- Asynchronous work. --- Work culture. --- Personalized work. --- Personalized employee experience. --- Manager skills. --- Ethical skills. --- Digital skills. --- Collaboration analytics.
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