Tax Matters

“The Tax Benefits of Separating Alpha from Beta” Wins the 2020 Graham and Dodd Top Paper Award

May 5, 2021

Topics - Tax Aware

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“The Tax Benefits of Separating Alpha from Beta” Wins the 2020 Graham and Dodd Top Paper Award

We were gratified and humbled by the decision of the Graham and Dodd selection committee of the CFA Institute to award the 2020 Top Graham and Dodd Award to our paper “The Tax Benefits of Separating Alpha from Beta.”  1 1 Close Liberman, Joseph, Clemens Sialm, Nathan Sosner, and Lixin Wang. 2020. “The Tax Benefits of Separating Alpha from Beta.” Financial Analysts Journal 76 (1): 38-61.

In our research, we often focus on tax-aware strategies. However, in this paper, we tackle a different practical question: In a world dominated by tax-agnostic managers, how can investors design their tax-agnostic strategy allocations to improve the tax efficiency of their overall investment portfolios? We show that investors who invest separately in a long-short (tax-agnostic) strategy and an index fund have the ability to achieve higher after-tax returns than those investors who invest in a long-only (tax-agnostic) strategy that utilizes the exact same alpha signals as the market neutral strategy. 



The reason for this is simple: Trading stocks in pursuit of investment alpha, a long-only active manager realizes taxes on both the market appreciation and the alpha it adds on top of the market return. On the other hand, a long-short manager realizes taxes only on the alpha it achieves. Therefore, investors who separated alpha investments from beta exposure are able to enjoy the market appreciation (almost) tax free by investing in an index fund. We call the latter approach of combining an index fund with a separate long-short strategy a “composite long-short strategy.”

Figure 1 below 2 2 Close Figure 1 presents the same data as Figure 2 in the paper.   depicts the relationship between components of pre-tax return and tax costs of the hypothetical long-only and hypothetical composite long-short strategies. The first things we notice in the chart is a striking difference between the levels of tax costs of the hypothetical long-only strategy and the hypothetical composite strategy for any level of pre-tax return. In fact, we measure the expected tax cost of the hypothetical tax-agnostic long-only strategy to be 1.4% compared to just 0.2% for the hypothetical tax-agnostic composite strategy. 

Further, Panel A shows that tax costs of the hypothetical long-only strategy are closely related to the market return, as is evidenced by the highly positive slope of the regression line and a small dispersion around it. Panel B shows that, surprisingly, tax costs of the hypothetical long-only strategy have virtually no relationship to its pre-tax alpha. These results are quite remarkable. They show that the hypothetical tax-agnostic long-only strategy generates tax costs due to its market exposure, an exposure that could be obtained free of tax by investing in an index fund.



On the contrary, for the hypothetical composite long-short strategy, the relationship of its tax costs with the market return is negative (Panel A) and with the pre-tax alpha demonstrably positive (Panel B), meaning that the hypothetical strategy realizes tax costs on its alpha, as it should.

In sum, in a world dominated by tax-agnostic managers, the approach of separating alpha from beta provides a practical solution of reducing an unnecessary tax burden coming from market exposure.

Finally, as a robustness test, we show that tax awareness does not change the relative tax efficiency of the hypothetical long-only and the composite strategies—a hypothetical tax-aware composite long-short strategy achieves a significantly higher after-tax return than a hypothetical tax-aware long-only strategy. 

 

Figure 1. Relationship between Components of Pre-Tax Return and Tax Costs of a Hypothetical Tax-Agnostic Long-Only and a Hypothetical Composite Long-Short Strategies

Source: AQR.   Figure shows results of 100 Monte-Carlo simulated histories. Each data point corresponds to a time-series average of one simulation. The lines depict ordinary least-squares regressions of hypothetical average tax costs on hypothetical average market returns (Panel A) and pre-tax alphas (Panel B). Each simulation history is constructed as follows. Stock returns are drawn from a multifactor distribution for 500 stocks. The simulated portfolios are updated monthly for a period of 25 years. We assume that all the returns are price returns and do not model dividend income. The multifactor stock return distribution is based on market, value, and momentum factors. The value factor is proxied by a long-term reversal and depends negatively on the performance over the prior 60 months and the momentum factor depends positively on the performance over the prior 12 months excluding the most recent month. The market factor has an annualized mean return of 8% and a volatility of 15%. The value and momentum style factors each have an annual average return of 2% and a volatility of 4%. The market factor is assumed to be uncorrelated with the value and the momentum factors, whereas the correlation between the value and the momentum factors is −0.7.  All stocks are assumed to have a constant beta of one to the market factor. Stocks’ exposures to the value and momentum factors vary dynamically based on stocks’ simulated price histories. The annualized stock-specific volatility is set equal to 25% for each stock. We construct hypothetical strategy portfolios as flows. We rank stocks based on their value and momentum exposures, sum up the value and momentum ranks, and rank again to obtain a combined value-momentum rank. The ranks are then demeaned such that half of the stocks have a positive factor score and half of the stocks have a negative factor score. For the hypothetical long-only strategy, the negative ranks are dismissed, and the positive ranks are rescaled to sum to 100%. For the long-short component of the hypothetical composite strategy, positive and negative scores are each rescaled to sum to 50%, resulting in a total gross notional exposure of 100%. The investor uses each $1 of capital invested in the hypothetical passive index fund to margin $1 of gross notional exposure of the hypothetical long-short strategy, $0.50 long and $0.50 short. We calibrate the two-sided turnover as a percent of portfolio net asset value (NAV) of the value-momentum strategies at 180% per year. A two-sided turnover takes into account both acquisitions and dispositions of stocks. For the hypothetical tax cost calculation, we assume that long-term gains are taxed at a 20% rate and short-term gains are taxed at a 35% rate.  We keep track of the individual tax lots of the portfolio holdings and use a highest-in first-out (HIFO) accounting method for managing tax lots. In each calendar year capital gains taxes are computed after an appropriate netting of capital gains and capital losses. Net capital losses are carried forward to future years.  Taxes on net capital gains are funded by liquidating portfolio positions: Once a year the initial NAV of the strategy is reduced by the amount of tax liabilities of the previous year effectively exchanging portfolio positions into cash which then can be used to cover the tax obligations. These withdrawals of capital from the strategy result in some additional taxes and portfolio turnover.

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The annual Graham and Dodd Awards of Excellence include the top G&D Award to recognize the best research article and up to two Scroll Awards to acknowledge the runners-up. Winners are chosen through a two-stage selection process. First, all members of the Financial Analysts Journal Advisory Council and Editorial Board are invited to vote, producing a shortlist of peer-reviewed research articles published in the Journal throughout the year. Second, the G&D Awards Committee (six members selected from the CFA Institute Board of Governors, the CFA Institute Leadership Team, CFA Society Leadership, and the Journal editorial team) collectively decides the award winners from the shortlist.

HYPOTHETICAL PERFORMANCE RESULTS HAVE MANY INHERENT LIMITATIONS, SOME OF WHICH, BUT NOT ALL, ARE DESCRIBED HEREIN. NO REPRESENTATION IS BEING MADE THAT ANY FUND OR ACCOUNT WILL OR IS LIKELY TO ACHIEVE PROFITS OR LOSSES SIMILAR TO THOSE SHOWN HEREIN. IN FACT, THERE ARE FREQUENTLY SHARP DIFFERENCES BETWEEN HYPOTHETICAL PERFORMANCE RESULTS AND THE ACTUAL RESULTS SUBSEQUENTLY REALIZED BY ANY PARTICULAR TRADING PROGRAM. ONE OF THE LIMITATIONS OF HYPOTHETICAL PERFORMANCE RESULTS IS THAT THEY ARE GENERALLY PREPARED WITH THE BENEFIT OF HINDSIGHT. IN ADDITION, HYPOTHETICAL TRADING DOES NOT INVOLVE FINANCIAL RISK, AND NO HYPOTHETICAL TRADING RECORD CAN COMPLETELY ACCOUNT FOR THE IMPACT OF FINANCIAL RISK IN ACTUAL TRADING. FOR EXAMPLE, THE ABILITY TO WITHSTAND LOSSES OR TO ADHERE TO A PARTICULAR TRADING PROGRAM IN SPITE OF TRADING LOSSES ARE MATERIAL POINTS THAT CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS. THERE ARE NUMEROUS OTHER FACTORS RELATED TO THE MARKETS IN GENERAL OR TO THE IMPLEMENTATION OF ANY SPECIFIC TRADING PROGRAM WHICH CANNOT BE FULLY ACCOUNTED FOR IN THE PREPARATION OF HYPOTHETICAL PERFORMANCE RESULTS, ALL OF WHICH CAN ADVERSELY AFFECT ACTUAL TRADING RESULTS. 
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