Seminar | March 14 | 11 a.m.-12:30 p.m. | 639 Evans Hall
Marielle de Jong
Consortium for Data Analytics in Risk
Mean-variance efficient portfolios are optimal as Modern Portfolio Theory alleges, only if risk were foreseeable, which is under the hypothesis that price (co)variance is known with certainty. Admitting uncertainty changes the perception. If portfolios are presumed vulnerable to unforeseen price shocks as well, risk optimality is no longer obtained by minimizing variance but also pertains to the diversification in the portfolio, for that provides protection against unforeseen events. Generalizing MPT in this respect leads to the double risk objective to minimize variance and maximize diversification. We demonstrate that a series of portfolio construction techniques developed as an alternative to MPT, in fact, address this double objective, under which Bayesian optimization, entropy-based optimization, risk parity and covariance shrinkage. We give an analytical demonstration and provide by that new theoretical backing for these techniques.
Wouter Leenders, leenders@berkeley.edu, 510-