Mutual fund performance : uncertainty, sustainability and data envelopment analysis
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This thesis contributes to three aspects of the rich literature on mutual fund performance evaluation and portfolio selection. In the first study, we examine the effects of uncertainty on the distribution of mutual fund returns. We find a widening return dispersion in response to high uncertainty while the average return is unaffected. Examining fund flow data, we show that investors do not react to changes in uncertainty. We also demonstrate that a strategy that invests in momentum during stable periods yet takes a contrasting position during volatile periods generates outstanding returns. In the second part of our study, we investigate how uncertainty affects the impact of environmental, social and governance (ESG) ratings on mutual fund performance and flow. We construct fund-level ESG scores based on their stock holdings and show a significant U-shaped effect of ESG score on risk-adjusted returns (value at risk), which changes during times of peak uncertainty. In addition, we identify a drastic shift in investors’ ESG preferences in response to uncertainty levels. In the final chapter, we empirically examine whether the data envelopment analysis (DEA) can be used as a tool to generate investment plans. We identify a significant positive impact of the current DEA score on subsequent fund returns. Constructing DEA-sorted fund portfolios, we demonstrate significant practical value of the DEA method in fund selection and propose the DEA-momentum strategy that can deliver superior performance compared with traditional strategies and can be used by both retail and institutional investors.