- To order reprints of this article, please contact David Rowe at d.rowe{at}pageantmedia.com or 646-891-2157.
To open this issue, Lausberg, Slager, and Stork present an intuitive framework for measuring and steering fundamental factors in a portfolio. Meissner develops a correlation-based portfolio performance measure which informs an investor how skilled the manager is in achieving a high return with respect to correlation risk, as well as how skilled a manager is in applying diversification benefits. Sherrill examines differences between target date funds with the same target date from different fund providers, finding considerable differences in asset allocations, risk, performance, and other fund characteristics.
Next, Ashraf tests the predictability power of returns across economically related industries using a machine learning model LASSO and indicates cross-predictability of industry return by showing significant relation between an industry’s returns and its LASSO-selected trade partners’ lagged returns.
Mikkelsen, Kjærland, and Henriksen evaluate the out-of-sample diversification benefits of including hedge fund indices in global stock-bond portfolios. Hubble and Grable test how risk profile factors are used to make investment portfolio allocation recommendations and find that financial advisors inconsistently amalgamated the presented risk profile factors into portfolio recommendations.
As we continue, Besson, Lasnier, and Falck present the benefits of European Periodic Auctions beyond MiFID II caps on dark trading. Bush, Chen, and Legunn evaluate currency exposure to show why currency acts as implicit leverage in a portfolio. Under an additional assumption, the portfolio risk equation reduces to the Pythagorean equation. The risk equation can be rearranged to give the “correlation break-even” that an investor requires to be indifferent to hedging or not hedging. Howell proposes a new decomposition of the interest rate term structure that includes an additional fourth factor and finds that a yield curve hump positioned at longer maturities appears to be consistent with lengthier time horizons of investors and with more risk-seeking behavior.
To conclude the issue, Gottesman and Morey try to predict a mutual fund’s activeness by examining mutual fund manager educational characteristics.
As always, we welcome your submissions. We value your comments and suggestions, so please email us at journals{at}investmentresearch.org.
TOPICS: Retirement, analysis of individual factors/risk premia, statistical methods
Brian Bruce
Editor-in-Chief
- © 2019 Pageant Media Ltd