Thomas Idzorek is the Global CIO of the Institute of Morningstar. His presentation is *The Impact of Skewness and Fat Tails on the Asset Allocation Decision* (see here for the paper that formed the basis for the presentation).

My session notes follow. As always, these are *at-the-time* notes. I make no guaranty as to their accuracy or completeness.

- The standard return model (bell curve) underestimates fat tails (following Taleb).
- The “flaw of averages” — average returns over time mean less due to potential extreme outcomes and any category can underperform, even by a lot, over long periods.
- Average returns focus can ignore risks.
- Markowitz mean-variance optimization has issues (e.g., the model ignore liabilities — the reasons
*why* one is saving/investing).
- Paul Kaplan: Deja Vu All Over Again.
- “Bad crap happens about ten times more often than normal distributions suggest.”
- James Xiong: Nailing Downside Risk (more here).
- Standard deviation only helpful as a stand-in for risk when distributions are normal.
- U.S. REITs and global high yield are dangerous when analyzed with better metrics (fund-of-fund optimization) due to non-normal attributes.
- Optimizing Manager Structure and Budgeting Manager Risk (nearly as important as Markowitz).
- “There’s no substitute for common sense.”
- Re models — garbage in, garbage out.

Conclusions:

- Asset returns are not normally distributed.
- Investor preferences often go beyond mean and variance.
- M-CVaR favors assets with higher positive skewness, lower kurtosis, and lower variance.
- Certain products (e.g., hedge funds) can depart from normal distribution a lot.
- We need a good fund-of-funds optimizer (recognizes that asset returns are not normally distributed).
- Idzorek and colleagues are working on it.

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