Why Traditional Risk Models Overstate Factor Risk
- Why traditional risk models overstate factor risk, due to inefficient regression weights and confusion between idiosyncratic and factor risk
- How the MAC3 model addresses these issues with proper regression weights and refined factor variance estimation
- The benefits of MAC3 in boosting portfolio optimization efficiency and reducing spurious correlations between factor and idiosyncratic returns
Speakers
Jose Menchero
Head of Portfolio Analytics Research
Bloomberg
Jose Menchero serves as Head of Portfolio Analytics Research at Bloomberg. Jose and his team are responsible for developing the analytics and algorithms used for factor risk models, portfolio risk and return attribution, scenario analysis, tail risk, 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.