The trend in recent years of securitizing more of the world’s market betas offers investors, in theory, better odds for enhancing risk-adjusted returns. Providing access to a broader set of assets with low/negative correlations moves us closer to the ideal of building optimal portfolios. In practice, however, juicing results is messy. One challenge is the grey area of developing reasonable expectations for relatively “new” betas that come down the pike. Tapping into a previously obscure market via an ETF, for instance, can be a good thing, but sometimes it’s unclear what to expect due to limited historical data. For some folks, that’s a reason to steer clear. But playing it safe comes with its own set of risks. The question, then, is how does one develop a comfort level with new products that don’t have a long track record as investable portfolios? The short answer: carefully, methodically, and with several techniques, including a bit of statistical modeling.
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