Finding Your Balance: Tradeoffs and Decisions in Portfolio Rebalancing


Investing in the real world incurs costs, and costs matter for the returns investors get.

Dimensional uses a flexible trading approach that seeks to reduce costs. This flexibility starts with our investment philosophy. We seek to add value by systematically emphasizing groups of stocks with higher expected returns rather than by identifying mispriced securities. As a result, we can consider many securities with similar characteristics as close substitutes for one another. Our flexible trading approach is also empowered by our thoughtful portfolio implementation. We structure our portfolios to focus on long-term drivers of returns—such as company size, relative price, and profitability—which do not require high turnover. We incorporate information from shorter-term drivers of returns, such as momentum and securities lending fees, by delaying buys and/or sells of securities rather than by chasing fast-dissipating signals. And we seek to rebalance our portfolios incrementally each day using up-to-date information. All of this enables us to participate daily in the available market liquidity and avoid demanding immediacy.

In a new study, we examine the trading price advantages of our flexible approach after tracking trade data over the 2017–2020 period across 46 stock markets. As shown in Exhibit 1, Dimensional’s average price advantages—measured by our trading prices relative to those obtained by market participants who demand immediacy—were pervasive across markets and persistent over time. Our price advantage was 10.5 basis points (bps)1 on average over the period, ranging from 4.3 bps for US large cap stocks to 24.8 bps for emerging markets small cap stocks. Furthermore, our longstanding flexibility can be more valuable when volatility is high. Indeed, we see that the price advantages increased as much as 100% in times of extreme return volatility, like March 2020.


Weighing Your Options

Reducing rebalancing costs and minimizing deviations from a target allocation represent conflicting goals. More frequent rebalancing may keep a portfolio tightly aligned with its target but at the cost of greater turnover. Less frequent rebalancing may lower costs but lead to larger tracking deviations.

Exhibit 1 illustrates this tradeoff. For a US 60/40 portfolio from 1979 to 2019, rebalancing quarterly produced about twice the turnover—our proxy for rebalancing costs—of rebalancing annually. But with that higher cost came a much lower tracking deviation from the target 60/40 allocation—less than half that experienced with annual rebalancing. Exhibit 1 also shows that calendar-based approaches, while convenient, tend to lead to less efficient rebalancing tradeoffs—higher turnover for a given level of tracking error and vice versa—compared to rebalancing with tolerance bands. As detailed in our paper, further improvements can be gained with tiered approaches that apply different tolerance bands across and within asset classes.


exhibit 1

Take Your Pick

Different ways of rebalancing a US 60/40 portfolio, January 1979–December 2019


In evaluating how rebalancing choices may impact a portfolio’s short-term performance, we find that less frequent rebalancing does not necessarily lead to higher maximum drawdowns. However, rebalancing less frequently can lead to meaningful short-term return differences relative to the target asset allocation. Our results show that the range of tracking error across rebalancing approaches is wider for portfolios with larger equity allocations, suggesting that investors sensitive to tracking error should be particularly mindful when choosing rebalancing approaches if their portfolios have high allocations to equities.

When choosing between investing in an integrated portfolio solution and investing in a portfolio with many components, investors should take into account rebalancing costs; a multicomponent portfolio can incur meaningfully higher costs due to rebalancing, but with little expected difference in returns compared to an integrated portfolio with otherwise similar characteristics.

Furthermore, we do not find evidence that rebalancing choices can reliably increase expected returns. Realized return differences across rebalancing approaches are typically due to style drift. For example, more frequent rebalancing tends to reduce returns because rebalancing tends to reduce the allocation to asset classes with higher expected returns. However, if a greater allocation to higher-expected-return asset classes was appropriate, it should be reflected in the target allocation. Noise in returns can also impact the realized return outcomes of different rebalancing approaches, suggesting that investors should avoid choosing a rebalancing method based solely on historical returns.

There are no one-size-fits-all, universally optimal rebalancing approaches. Our recent paper provides a framework that can help investors strike the right balance between minimizing rebalancing costs and keeping a better focus on their investment objectives, which may better position them to capture what the market has to offer.


Watch highlights from our recent webcast on rebalancing.




glossary

Tolerance bands: A percentage range around a portfolio’s target allocation that determines when to rebalance a portfolio. Rebalancing occurs if the weight of any portfolio component deviates from its target weight by more than the specified tolerance. For example, with a 5% tolerance band, a portfolio targeting 60% in equities and 40% in fixed income is rebalanced if the portfolio weight of equities either exceeds 65% or falls below 55%.

Tracking error: A measure used to quantify how closely a portfolio follows an index or benchmark, often defined as the standard deviation of the difference between the portfolio and index returns.

Footnotes

  1. 1Rebalancing costs can take various forms and include explicit and implicit costs. Even in a market environment where many exchange-traded funds (ETFs) are traded with zero transaction fees, rebalancing can be costly for investors due to ETF spreads, taxes, and monitoring costs.

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