posted Jun 23, 2011, 10:00 PM by Jonathan Li
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updated Oct 3, 2012, 2:22 PM
]
I am excited to be awarded and to share my work at Saint John's Newfoundland; what a wonderful place! Another must-go place.
| | First Prize - Open Category |
"Portfolio Selection under Model Uncertainty: A Penalized Moment-Based Optimization Approach" Jonathan Y. Li, University of Toronto |
Uncertainty on the choice of a
financial model leads to additional "model risk" in portfolio selection.
This level of risk becomes ever pronounced in recent financial markets
and results in substantial deterioration of portfolio performance. In
practice, portfolio managers face difficulty in seeking a balance
between relying on their knowledge of a reference financial model and
taking into account possible ambiguity of the model. We present a new
approach for portfolio selection when the underlying distribution of
asset returns is uncertain or ambiguous to investors. In particular, we
consider the case that an investor can formulate some reference
financial models based on his/her prior beliefs or information but is
concerned about misspecification of the reference models and the
associated loss. Based on the concept of Distributionally Robust
Optimization (DRO), we introduce a new penalty framework that provides
investors flexibility to define prior reference models using moment
information and accounts for model ambiguity in terms of moment
uncertainty. We further provide efficient solution methods for the
penalized moment based problem. Computational experiments show that our
penalized moment-based approach outperforms classical DRO approaches
using real-market data. Furthermore, the approach can be extended to
incorporate alternative uncertainty structures and factor models.  Fredrik Odegaard (r) presenting the First Prize, Student Paper Competition, Open Category to Jonathan Li.
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