Vol.17 No.1, 2019 Practitioner’s Digest View PDF… Read more
1st Quarter (2019)
Surveys & Crossovers – Predicting Investor Success Using Graph Theory and Machine Learning
Vol. 17. No.1, 2019 Predicting Investor Success Using Graph Theory and Machine Learning: Jeffrey Glupker, Vinit Nair, Benjamin Richman, Kyle Riener and Amrita Sharma View PDF… Read more
Portfolio Optimization With Noisy Covariance Matrices
Vol. 17 No.1, 2019 Jose Menchero and Lei Ji In this paper, we explore the effect of sampling error in the asset covariance matrix when constructing portfolios using mean–variance optimization.We show that as the covariance matrix becomes increasingly ill-conditioned (i.e., “noisy”), optimized portfolios exhibit certain undesirable characteristics such as under-prediction of risk, increased out-of sample… Read more
Lessons Learned From Student Managed Portfolios
Vol. 17 No.1, 2019 Stephan Kranner , Neal Stoughton, and Josef Zechner We study asset management decisions of three competing student managed funds in Vienna, Austria for a ten-year period. This real-world experience allows us to precisely test the tournament effect of fund management, the disposition effect, and managerial team size. We find support for… Read more
Book Review – Rational Investing: The Subtleties of Asset Management by Hugues Langlois and Jacques Lussier
Vol. 17. No.1, 2019 Rational Investing: The Subtleties of Asset Management by Hugues Langlois and Jacques Lussier reviewed by Savannah Smith View PDF… Read more
Explaining Buyout Industry Returns: New Evidence
Vol. 17 No.1, 2019 David Turkington Traditional equity factors such as the leveraged equity risk premium, the small-cap premium, and the value premium have had high historical returns on average, as has the buyout fund industry in aggregate. Previous research has argued that these factors explain the excess performance of private equity over public equity… Read more
Does Extreme Correlation Matter in Global Equity Asset Allocation?
Vol. 17 No.1, 2019 Bruno Solnik and Thaisiri Watewai Global asset allocation provides risk diversification. But international market correlation increases sharply during global crises and diversification benefit disappears when it is most needed. We model these correlation breaks and derive the asset allocation implications. The model can quickly detect crises and suggests adapting allocation for… Read more