“Our research represents a sensible starting point for potential direct indexing investors who want to include this strategy in their portfolios,” said Vanguard senior investment strategist Kevin Khang, Ph.D., one of the paper’s authors.

Direct or personalized indexing (PI) is a flexible portfolio management strategy that tracks a personalized index for an investor. It is an investor-specific policy reflecting environmental, social, and governance (ESG) preferences and/or factor tilts while harvesting capital losses for tax-saving purposes. In terms of asset allocation, direct indexing represents a modified beta exposure to U.S. equity with an active return stream arising from personalization and tax-loss harvesting (TLH).

To help develop a portfolio construction plan for direct indexing investors, the authors examined various modes of tax-loss harvesting implementation within portfolios.¹ Their research considers two investors seeking tax alpha with recurring capital gains and generally higher tax rates.²

Investor A represents mass affluent and high-net-worth investors (also referred to in the paper as low-alpha investors, because the tax alpha they can expect is generally modest). These investors’ interest in direct indexing has grown recently as it has become more accessible.

Investor B represents ultra-high-net-worth investors with the highest short- and long-term capital gains tax rates. The authors refer to them as high-alpha investors because these investors often have extensive capital gains arising from other parts of their balance sheet, and they may expect a higher tax alpha.

Using these two types of investors, the authors perform a two-part analysis. The first part examines how various modes of tax-loss harvesting affect tax alpha.

“We found that a higher frequency of tax-loss harvesting leads to materially higher alpha for both investors,” Khang said. For ultra-high-net-worth investors represented by Investor B, TLH alpha is 146 basis points (bps) higher for direct indexing investors who tax-loss harvest daily than for those who do so annually.³ The difference is significant, too, for high-net-worth investors represented by Investor A.

Khang and his coauthors also found that personalization may come at a cost, ranging from negligible for investors with 1.50% of alpha (a high-alpha investor, or Investor B) to about 60 bps of return reduction for the entire portfolio for investors with only 0.25% of alpha (a low-alpha investor with maximum tracking error, or Investor A).

The second part of the analysis explores how to integrate direct indexing into an existing portfolio through the lens of the Vanguard Asset Allocation Model (VAAM). From an asset allocation perspective, the implication for direct indexing and personalization for high-alpha investors, such as Investor B, is straightforward. The pursuit of personalization may result in greater tracking error against the benchmark, but the optimal allocation and expected risk–return profile of the entire portfolio will remain largely unaffected.

“For high-alpha investors, the optimal allocation to equity effectively equals the allocation to direct indexing at all reasonable levels of tracking error,” Khang said. “So, our asset allocation recommendation is easy: Replace the equity allocation to passive taxable U.S. equity with direct indexing and personalize freely.”

But for low-alpha investors, such as Investor A, greater personalization has important performance and implementation implications, Khang said. Greater tracking error in direct indexing, he said, calls for a lower allocation to equity and therefore a lower expected return from the entire portfolio. As tracking error rises above 75 bps and optimal equity allocation declines, the optimal mix between direct indexing and passive equity may also change.

“Low-alpha investors may want to lower their overall equity allocation to accommodate meaningful personalization in their portfolios,” he said.

Khang said the paper marks an important development in direct indexing. Until now, the marketplace for direct indexing lacked general guidance on implementing it in a portfolio.

Although investors still need to customize their portfolio plans to determine the optimal allocation to it, Khang said, “our research presents an evidence-based starting point that investors can use for adding direct indexing to their portfolios.”