Abstract: Solving the “curse of dimensionality” problem in multi-asset class risk models.
Estimating a robust risk model risk for a portfolio that spans multiple asset classes is a challenging task due to the “curse of dimensionality” (i.e., the problem of estimating too many relationships from too few observations). While the sample covariance matrix is easily computed, it is susceptible to capturing spurious relationships that make it unsuitable for portfolio construction purposes. In this talk, we present a new approach for constructing risk models that span multiple asset classes. We also discuss the implications for portfolio risk management and portfolio construction.
Speaker Bio: Jose Menchero serves as Head of Portfolio Analytics Research at Bloomberg. Jose and his team are responsible for developing the full suite of factor risk models spanning multiple asset classes, as well as portfolio risk and return attribution, portfolio construction, and portfolio optimization.
Prior to joining Bloomberg, Jose was the founder and CEO of Menchero Portfolio Analytics Consulting. Before founding his consulting firm, Jose worked for eight years at MSCI, where he was Managing Director responsible for developing the Barra equity risk models, and for portfolio construction research. Jose also served for seven years as Director of Research at Thomson Financial, where he developed several risk and return attribution methodologies, as well as equity factor risk models.
Jose has over 30 finance publications in leading practitioner journals. Before entering finance, Jose was Professor of Physics at the University of Rio de Janeiro in Brazil. Jose holds a PhD in theoretical physics from the University of California at Berkeley, and a BS degree in aerospace engineering from the University of Colorado at Boulder. Jose is a CFA Charterholder.
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Ralph Goldsticker, Senior Investment Strategist at Goldsticker Investment Strategy
Robert Maxim, Duff & Phelps
Jason Ribando, RS Investments
Irene Rusman, Oracle
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Walt French, Nuveen Investments
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