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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Portfolio Reconstruction: An Investigation of Brazilian Investment Funds |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Date | 2021 |
| Abstract Text | Returns-based style analysis (RBSA) is a statistical method commonly used to investigate the exposure of investment funds. It involves identifying the combination of market factors that most closely reproduces a fund’s returns and attempts to characterize their investment styles. This thesis utilizes RBSA to explore the investment behaviours of the most relevant classes of Brazilian investments funds: foreign exchange (FX), fixed income, stocks, and multi-strategy funds. We demonstrate that RBSA is adequate for analysing funds that possess relatively stable asset allocations; however, its performance is not satisfactory for funds with time-varying exposures. To overcome this limitation, we adapt a state-space model and apply a Kalman filter to construct a dynamic style analysis model. Between January of 2010 and April of 2021, we studied 320 funds that were selected based on their asset values size. We found that FX and fixed income funds are generally passively managed, and, by applying a clustering algorithm to their style results, we demonstrated that these funds can be categorized into groups that track the same benchmarks. However, this study also suggests that several stock funds and most multi-strategy funds are actively managed. For these classes of funds, our empirical results indicate that the Kalman filter estimations improve style predictions and yield better and more interpretable outputs. Finally, we extend this proposed framework with the use of past disclosed fund information to identify actual portfolio constituents over time. Our analysis shows that this innovative approach achieves accurate results only when applied to funds with a small number of assets. |
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