RT Journal Article SR Electronic T1 Practical Applications of The Low-Risk Anomaly: How Much Is a Good Risk Estimate Worth? JF Practical Applications FD Institutional Investor Journals SP pa.2022.pa474 DO 10.3905/pa.2022.pa474 A1 Tony Barchetto A1 Razvan Pascalau A1 Ryan Poirier YR 2022 UL https://pm-research.com/content/early/2022/01/05/pa.2022.pa474.abstract AB In The Low-Risk Anomaly: How Much Is a Good Risk Estimate Worth?, from the November 2020 issue of The Journal of Portfolio Management, Tony Barchetto of Salt Financial, Razvan Pascalau of SUNY Plattsburgh, and Ryan Poirier of Salt Financial introduce a new method to exploit the low-risk anomaly. They propose a hybrid model using several lookback periods to measure volatility, thus producing a better measure of volatility than used by the CAPM. This multi-interval technique is a variation on Corsi (2009), who used intraday variance to write the HAR-RV model. Because intraday data are hard to come by, the authors propose a multi-interval approach using more widely available data. The authors find that using a variety of lookback periods results in higher alpha. This is the advantage of their model over standard HAR-RV and CAPM.The authors experimented with real data from December 1967 to June 2018 to test the forecasting abilities of their model on the $75 billion low-risk market. For every 60-day, 252-day, and 60-month lookback period, their model predicted that the lowest-risk portfolios would incur the highest alpha proportions as compared with riskier portfolios. Their model proved accurate when compared with the realized volatility data, or observed beta values, from those same lookback periods. By the authors’ calculation, somewhere between $420 million and $1.9 billion could have been gained from this market if their risk assessment model had been employed.