An enormous body of academic finance literature discusses the pre-tax performance of public equity factor tilts, but almost nothing measures the impact of taxes on taxable asset owners. Pete Hand, Aperio’s Director of Quantitative Strategies, has remarked over the years that pretty much every paper in academic finance needs to be rewritten from the standpoint of the taxable investor. And David Swensen, Yale University’s legendary CIO, calls the management of taxable mutual fund assets without considering the tax consequences of trading activity “a highly visible, yet little considered scandal.” We would extend Swensen’s comment to include the management of all taxable assets, including those in separately managed accounts (SMAs), not just those that happen to be in a mutual fund wrapper.

In developing a quantitative investment strategy, a money manager will often “back-test” different strategies in order to see how it might have performed during different historical time periods. This is a fairly straightforward process on a pre-tax basis as sophisticated back-testing tools are commercially available to help run the simulations. Unfortunately, to the best of our knowledge, we know of no such tools that are commercially available which can simulate and measure the historical impact of taxes. As a result, Aperio has spent the past three years developing a very flexible and broad-based back-testing platform that is now the foundation for our public equity analyses across the board. We believe it is one of the only tools available that allows for after-tax back-testing. Called the After-Tax Back-Testing Analysis Tool, or ATBAT for short, the platform....

• Allows for after-tax optimization and performance measurement.
• Allows for multiple starting points for strategy testing, which is critical for processes that are path dependent (every tax-managed portfolio is path dependent!). In The Tax-Loss Harvesting Life Cycle, we use ATBAT to understand the value of tax-loss harvesting strategies across the spectrum of potential investor experiences.
• Can analyze multiple separate but equivalent back-tests, including cross-sectional studies (comparing portfolios as of specific point in time—for example, tax alpha in 2008—regardless of back-test start date) and longitudinal simulations (comparing portfolios across time; for example, cumulative tax alpha in years one to 10).
• Works with a wide variety of risk models, benchmarks, and Aperio or client-defined investment strategies while maintaining precise accounting of tax outcomes at a tax-lot level.
• Has a custom-built process for organizing and visualizing results along either calendar or vintage time dimensions, each of which is very important for taxable investors.
• Perhaps most importantly, helps advisors manage client expectations better by creating a range of expectations (due to the use of multiple paths) pre- and after-tax, based on empirical back-tests rather than just a simple summary using average or median metrics.

ATBAT builds on our paper, published in 2015 in Financial Analyst Journal, entitled “What Would Yale Do If It Were Taxable,” in which we evaluated the university endowment’s asset allocation from the perspective of an ultra-high-net-worth (UHNW) taxable investor. With ATBAT, we have a new research platform that we can use to test investment decisions, such as gifting strategies (“The Double Bottom Line—Tax-Loss Harvesting for the Altruistic Investor”) and factor investing (research paper forthcoming), in a taxable environment, as well as the impact of tax law changes at the state and/or federal level. Most recently, we used ATBAT to quantify the potential impact on our client portfolios of the proposed Senate tax reform bill changes that would disallow specific lot identification and instead require the FIFO (first-in, first-out) method (“The Impact of FIFO on a Tax-Managed Indexing Strategy”).

As the recent congressional tax proposals remind us, the investment environment can change very quickly and nothing is for certain. The best we can hope for is to make informed decisions as quickly as possible, and ATBAT is a powerful new platform at your disposal.

Send questions or comments to blog@aperiogroup.com.

You should use caution when considering this information regarding ATBAT (Aperio After-Tax Back-Testing Analysis Tool). ATBAT, as a tool-based platform, is inherently limited in its ability to reflect the actual results regarding performance and other quantitative information that may have been, or will be, achieved by any given portfolio. Aperio, like all investment advisors, has an incentive to present returns that reflect positively on Aperio’s investment strategies. While Aperio seeks to apply the application of ATBAT objectively and consistently, Aperio may be unsuccessful in removing all instances and forms of bias from the construction and implementation of the tool. There is no guarantee that any client results actually achieved will align with the modeled results demonstrated or output by ATBAT.

ATBAT may have fundamental errors and may produce inaccurate outputs when viewed against its design objective and intended business uses. The mathematical calculation and quantification exercise, for example, underlying the models embedded in ATBAT generally involves the application of theory, choice of sample design and numerical routines, selection of inputs and estimation, and implementation in information systems. Errors may have and can occur at any point from design through implementation. In addition, shortcuts, simplifications, or approximations used to manage complicated problems could compromise the integrity and reliability of outputs from those calculations. Finally, the quality of the outputs from ATBAT depends on the quality of input data and assumptions, and errors in inputs or incorrect assumptions will lead to inaccurate outputs. Even assuming that ATBAT is a fundamentally sound tool, producing accurate outputs consistent with its design objective may still exhibit high risk if it is misapplied or misused. Such modeling tools, by their nature, are simplifications of reality, and real-world events may prove those simplifications inappropriate.

ATBAT’s results aim to reflect Aperio’s tax-loss harvesting strategy. This strategy seeks to enhance the returns of an equity index–tracking portfolio by selling a basket of stocks to realize tax losses and buying a replenishment of stocks with similar risk characteristics, so that the rebalanced portfolio continues to track its benchmark.