Published: Path Dependency in Financial Planning, Retirement Edition


The Miller Thompson / Reuters monthly Taxes and Wealth Management newsletter carried an article we authored on the importance of volatility and path dependency (a.k.a sequence of returns risk) for retirees.  We are pleased to have been selected for publication, and hope that readers find value in our contribution.

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Forget active vs. passive. It’s all about factors.


We just love a good debate, and there seems to be quite a heated debate at the moment about the relative utility of passive versus active investing. Perhaps this debate is as timeless as investment management itself, but a flurry of recent studies may have finally armed passive advocates with enough ammunition to settle the argument once and for all.

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Published: Fallacies of the Fed Model


The Journal of the Society of Actuaries held a contest for articles on investment myths, and we are honored to have had our article on ‘Fallacies of the Fed Model’ chosen for publication in this prestigious journal. We want to thank our co-authors, David Cantor and Kunal Rajani of PriceWaterhouseCoopers, for proposing this collaboration, and for their critical insights and analytical contributions.

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A Global Passive Benchmark with ETFs and Factor Tilts


“One way to test our thinking would be to ask the question in reverse: If your index manager reliably delivered the full market return with no more than market risk for a fee of just 5 bps, would you be willing to switch to active performance managers who charge exponentially more and produce unpredictably varying results, falling short of their chosen benchmarks nearly twice as often as they outperform—and when they fall short, losing 50% more than they gain when they outperform? The question answers itself.” – Charles Ellis, “The Rise and Fall of Performance Investing

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Setting Expectations for Monthly Trading Systems


Systematic researchers overwhelmingly use monthly holding periods to test strategies. This is probably driven by the availability of long-term monthly total return data for a wide variety of indexes, where daily data is more scarce. This is fine to a point, but investors may not be aware of just how sensitive results might be to day-of-the-month effects which may not persist out of sample.

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