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This master thesis tries to investigate the dependence of the distribution of extreme positive
returns of US equity mutual funds. The aim is to identify the determinants of extreme positive
returns. We investigated a sample of 11,373 US equity mutual funds and covered a time interval
from January 2001 to December 2019. Our set of explanatory variables includes financial, macroeconomic
and fund – specific variables. We modeled the extreme positive returns by using the EVT
and the POT approach. We assume that the distribution of extreme positive returns follows a Generalized
Pareto distribution where the scale and shape parameters depend on the covariates. The
selection of the optimal and relevant set of explanatory variables is performed by a regularization
procedure based on a penalized – likelihood estimation. This regularization procedure is proposed
by Hambuckers, Groll, and Kneib (2018). Lastly, we assessed the robustness of our model by
comparing our results to models using a time - varying threshold to define the extreme positive
returns or a different time interval.

Mutual Fund, Extreme Performance, Extreme Value Theory, Peak – Over – Threshold approach, Generalized Pareto Distribution --- Sciences économiques & de gestion > Finance