Worked research note
Rebalancing frequency, turnover, and drift
In one pretax 60/40 case, tighter calendar control demanded far more turnover while the unrebalanced reference carried more risk.
Published Oct 11, 2026
At a glance
Daily rebalancing generated 45.73% annual turnover, compared with 2.79% for annual rebalancing, in this 60% SPY and 40% BND study.
Never rebalancing returned 9.57% annually, with 12.39% volatility and a 23.96% maximum drawdown. Its higher return came with a different risk exposure. Taxes and trading costs are not modeled.
Scope: One historical path cannot identify a universally optimal rebalance frequency.
Frequency changed turnover by more than sixteenfold
The study compares seven calendar frequencies for 60% SPY and 40% BND, using $250,000 principal, total returns, and January 2015 through December 2024. We highlight daily, annual, and no rebalancing.
Daily rebalancing produced 45.73% annual turnover, more than sixteen times the annual policy’s 2.79%. No rebalancing produced zero policy-driven turnover.
Exhibit 01
The turnover price of tighter calendar control
The three cited rows from the recorded sweep. Turnover is an implementation quantity, not a modeled dollar cost in this case.
Turnover measures trading activity. This recorded case does not convert activity into transaction costs or tax drag.
| Category | Annual turnover |
|---|---|
| Daily | 45.732% |
| Annual | 2.789% |
| Never | 0% |
Source and construction: Archived ArthaPilot Rebalancing Sensitivity calculation; 60% SPY and 40% BND; 2015-01-02 through 2024-12-31; response hash a601b4b1a0f2… .
How this figure was calculated
Inputs
- A $250,000 portfolio fixed at 60% SPY and 40% BND.
- The archived seven-frequency result over 2015-01-02 through 2024-12-31.
- The request's disabled offset setting, so no tax offset enters any row.
- No inflation adjustment, so every displayed figure is nominal.
Calculation
- Hold assets, target weights, principal, dates, and total-return basis constant.
- Read one-way annual turnover from the daily, annual, and never rows.
- Convert the response's decimal turnover values to percentages.
Exact values behind the figure
| Series | Calendar policy | Annual turnover (%) |
|---|---|---|
| Annual turnover | Daily | 45.732% |
| Annual turnover | Annual | 2.789% |
| Annual turnover | Never | 0% |
The recorded sweep makes the implementation gradient visible: a more frequent rule traded much more of the portfolio. It does not establish that daily or annual rebalancing was economically costly after spreads, commissions, or taxes because those frictions were disabled.
Turnover should therefore be read as the amount of activity a later cost model would need to price. It is not tax drag or an all-in expense estimate.
The highest return belonged to the drifting reference
Daily, annual, and never-rebalance CAGR were 8.59%, 8.50%, and 9.57%, respectively. A return-only ranking would put the never-rebalance row first.
But the same row also had the highest recorded volatility, 12.39%, and maximum drawdown, 23.96%. This study does not support the claim that avoiding rebalancing improved the strategy while holding risk constant. Risk was allowed to move with the weights.
Exhibit 02
Return did not move independently of risk
CAGR for the three cited policies, with the recorded risk statistics attached to the no-rebalance reference.
The chart describes one realized path. It does not hold the drifting portfolio's risk exposure constant or identify a winning policy.
| Category | CAGR | Volatility | Maximum drawdown |
|---|---|---|---|
| Daily | 8.59% | 11.02% | 21.8% |
| Annual | 8.5% | 10.84% | 21.02% |
| Never | 9.57% | 12.39% | 23.96% |
Source and construction: Same recorded ArthaPilot response; total returns, no inflation adjustment, no transaction-cost model, and no investor-tax model.
How this figure was calculated
Inputs
- Pretax CAGR, volatility, and maximum drawdown from the daily, annual, and never rows.
- Identical dates, principal, holdings, and total-return basis across rows.
Calculation
- Read the three response metrics for each selected frequency.
- Place return, volatility, and drawdown on the same policy categories without forming a composite score.
Exact values behind the figure
| Series | Calendar policy | Annualized or peak-to-trough value (%) |
|---|---|---|
| CAGR | Daily | 8.59% |
| CAGR | Annual | 8.5% |
| CAGR | Never | 9.57% |
| Volatility | Daily | 11.02% |
| Volatility | Annual | 10.84% |
| Volatility | Never | 12.39% |
| Maximum drawdown | Daily | 21.8% |
| Maximum drawdown | Annual | 21.02% |
| Maximum drawdown | Never | 23.96% |
The no-rebalance row is a drifting-risk reference, not a winning policy. Its higher realized return may reflect the exposures it was permitted to accumulate along this particular path.
A policy comparison becomes decision-useful only after the desired allocation control is stated. Without that target, the exercise silently rewards whichever drift happened to be favorable.
What this worked case leaves unanswered
This study covers calendar frequencies for one portfolio. It does not test tolerance bands, execution-date offsets, trading costs, investor taxes, or a second portfolio.
Each can change the result: bands alter when a trade occurs, offsets change the prices encountered, and taxes convert sell-side turnover into a household-specific ledger.
Exhibit 03
Measured here and outside this note
A scope boundary that separates the verified calendar-frequency case from excluded comparisons.
The curve describes calendar-frequency turnover before costs and taxes. It contains no band, offset, after-tax, or implementation-cost result.
| Category | Recorded turnover |
|---|---|
| Daily | 45.732% |
| Weekly | 18.863% |
| Biweekly | 13.605% |
| Monthly | 8.967% |
| Quarterly | 5.526% |
| Annually | 2.789% |
| Never | 0% |
Note: The adjacent scope ledger identifies comparisons absent from this pretax calendar-frequency fixture.
Source and construction: Scope of the archived ArthaPilot Rebalancing Sensitivity calculation.
How this figure was calculated
Inputs
- The seven requested calendar frequencies and their response turnover_per_year values.
- The response's null after-tax fields and no-cost effective assumptions, retained as scope boundaries.
Calculation
- Convert each annual-turnover decimal to percentage points by multiplying by 100.
- Order the points from daily through never to preserve the requested frequency sequence.
Exact values behind the figure
| Series | Calendar frequency | Annual turnover |
|---|---|---|
| Recorded turnover | Daily | 45.732% |
| Recorded turnover | Weekly | 18.863% |
| Recorded turnover | Biweekly | 13.605% |
| Recorded turnover | Monthly | 8.967% |
| Recorded turnover | Quarterly | 5.526% |
| Recorded turnover | Annually | 2.789% |
| Recorded turnover | Never | 0% |
This case shows an implementation trade-off: tighter calendar control coincided with much higher turnover, while no rebalancing changed the return-and-risk profile.
This note does not estimate tax drag or identify an optimal rebalance rule. Those questions are outside its recorded evidence.
Method and constraints
Method
The displayed pretax calendar-frequency results reconcile to one archived request and result.
The note makes no claim about tolerance bands, execution-date offsets, transaction costs, taxes, a second portfolio, or an optimal rule.
Assumptions held fixed
- The recorded portfolio is fixed at 60% SPY and 40% BND with a $250,000 starting principal.
- The common market window is 2015-01-02 through 2024-12-31 on a total-return basis without inflation adjustment.
- Seven calendar frequencies were tested. Daily, annual, and no rebalancing are highlighted in the first two exhibits.
- Transaction costs and investor taxes are disabled, so turnover is not converted into dollars or tax drag.
Limitations
- One historical path cannot identify a universally optimal rebalance frequency.
- This study does not quantify how much allocation drift each policy removed.
- It does not model transaction costs, taxes, tolerance bands, execution-date offsets, or cash-flow-assisted rebalancing.
- Results for one SPY-and-BND portfolio need not carry to other assets, weights, or correlation regimes.
Sources and prior research
- Vanguard Investment Strategy Group, Rational rebalancing: an analytical approach to multiasset portfolio rebalancing decisions and insights (2022)
Primary firm research on calendar, threshold, and combination policies and the trade-off between allocation control and transaction costs.
- Vanguard, Rebalancing your portfolio (2026)
Authoritative explanation that rebalancing is an allocation-control process rather than a market-timing rule, with tax-aware implementation considerations.
- ArthaPilot, Rebalancing Sensitivity guide (2026)
Calculation contract for the recorded calendar-frequency sweep and its excluded policy comparisons.
Evidence and reproducibility
cost-of-rebalancing-recorded-demo-fixture
A descriptive worked note comparing recorded pretax calendar-frequency rows for one 60% SPY and 40% BND portfolio.
Evidence date: 2026-08-17. Basis and units are stated in each recorded fact.
note=434808c8914438bd7e232fe34abb676e97d5c7c5bd1e058b4869c5cb3d3a9509; request=ce0b0ef1e34876faface54e7cb3fdad7e7ff2da4ffaaa4e1d481db67e643f85d; response=a601b4b1a0f2c3ec3d692eb87850ff308b3924c9f65e201c4111a7a58144e6ef
Source: web/src/data/research/portfolio/fixtures/rebalancing.record.json. Versions: fixture1=69daa3e2f3fd5efe2faa78e6b08748eee1bc250c@1.0.0.
- An after-tax or transaction-cost ranking
- A result for tolerance bands, execution-date offsets, or a second portfolio
- A universal optimal rebalance rule
Inspect the same question with your own inputs
- Compare rebalance frequencies Opens the study's 60/40 holdings, dates, $250,000 principal, and total-return basis. Review taxes, inflation, and sweep settings before running; current market data and methods can differ from the archived result.