RT Journal Article SR Electronic T1 Practical Applications of Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons JF Practical Applications FD Institutional Investor Journals SP 1 OP 6 DO 10.3905/pa.6.3.312 VO 6 IS 3 A1 Sarah J. Campbell A1 James Chong A1 William P. Jennings A1 G. Michael Phillips YR 2019 UL https://pm-research.com/content/6/3/1.18.abstract AB In Portfolio Optimization Strategy for Concentrated Portfolios: Models and Time Horizons, from the Fall 2018 issue of The Journal of Wealth Management, authors Sarah Campbell, James Chong, William Jennings, and G. Michael Phillips (all of MacroRisk Analytics) examine the relative merits of portfolio-construction approaches for concentrated, or high-conviction, (i.e., 15 or fewer holdings) portfolios. The authors’ study in part stems from the debate over the efficacy of an optimization approach to portfolio construction compared with an equally weighted (or “naïve”) approach. The authors’ intention is to help guide wealth managers in choosing a portfolio-optimization method best suited to their investment priorities (e.g., maximizing returns, minimizing risk, balancing risk and returns).The authors apply a Monte Carlo simulation to generate 18,000 buylists of stocks. From each buylist, the simulation derives an optimized portfolio and two equally weighted portfolios: one of stocks selected through optimization (a “hybrid” portfolio) and the other of randomly selected stocks (a “benchmark” portfolio). The study calculates each portfolio’s forward average yearly returns, annual standard deviations, and forward risk–return ratios for several different time frames, and then compares relative performance. The authors emphasize the importance of choosing the suitable portfolio-construction approach: one aligned with the number of holdings in a portfolio and investment horizon or one that best performs under the distinct circumstances faced by the wealth manager.TOPICS: Portfolio construction, analysis of individual factors/risk premia, tail risks, performance measurement