ETF Rotation Strategy - Journal Guide

ETF sector rotation is a rules-based position strategy suited to intermediate traders who want systematic market exposure without the noise of intraday decisions. By ranking the 11 SPDR sector ETFs on relative strength and rotating monthly into the top performers, traders capture momentum at the sector level while defensive filters limit drawdown during bear markets. The strategy requires discipline and precise journaling — without a structured log, it is impossible to distinguish a failing strategy from sloppy execution.

How ETF Rotation Works

The strategy exploits the well-documented tendency of outperforming sectors to continue outperforming over 1-12 month horizons — a phenomenon confirmed across decades of academic and practitioner research. Rather than picking individual stocks, traders gain diversified exposure to the strongest areas of the economy and rotate away from weakening ones.

The mechanics rest on two filters drawn from Gary Antonacci’s Dual Momentum framework. First, relative momentum identifies which of the 11 SPDR sector ETFs (XLK, XLE, XLV, XLF, XLI, XLY, XLP, XLU, XLRE, XLB, XLC) is strongest — scored by equally weighting 1-month, 3-month, and 6-month total returns. Second, absolute momentum screens out weak market environments: if a sector’s 12-month return doesn’t beat SHY (short-term Treasuries), it fails the filter even if it ranks #1 in relative strength.

The risk-off overlay uses SPY’s 10-month simple moving average or 200-day MA as the regime switch. When SPY closes a calendar month below that line, all equity exposure is exited and capital moves to AGG or cash. This signal, documented by Mebane Faber in his 2006 paper “A Quantitative Approach to Tactical Asset Allocation,” historically sidestepped the majority of bear market losses.

The strategy works best when sector leadership is clear and persistent — conditions common in trending macro environments like 2021-2022. It underperforms in whipsaw, sector-indifferent markets where leadership rotates faster than monthly cycles can capture.

Entry Rules

1. Run the RS screen on the first trading day of each month — Rank all 11 SPDR sector ETFs by composite score (equal-weight 1-month, 3-month, and 6-month total return). Select the top 2-3 sectors. Record all 11 scores in your journal before placing any orders.

2. Apply the absolute momentum filter — For each top-ranked sector, confirm its 12-month total return exceeds SHY’s 12-month return. If a sector fails this filter, replace it with AGG or cash rather than moving to the next-ranked equity sector.

3. Confirm the risk-on regime — Check that SPY closed the prior month above its 10-month SMA or 200-day MA. If SPY is below this level, do not enter any equity sector positions regardless of relative rankings. Hold AGG, SHY, or cash for the full month.

4. Execute at the open on rotation day — Use market or limit orders within the first 30 minutes. Do not delay — mid-month execution introduces timing drift that compounds over years and makes journal comparisons meaningless.

Exit Rules

1. Exit at the next monthly review if rank drops — Any sector that falls outside the top 2-3 at the next rotation date is sold at the open on the first trading day of the next month. No intra-month exits based on price action.

2. Exit all equity positions if SPY fails the MA test — If SPY closes any calendar month below its 10-month SMA, exit the entire equity portfolio at the open on the first trading day of the next month. Rotate fully to AGG or SHY — no partial hedges.

3. Exit if absolute momentum fails — If a held sector’s 12-month return drops below SHY at any monthly review, exit regardless of its relative rank. This prevents holding declining sectors simply because they’re declining less than others.

Risk Management for ETF Rotation

Allocate capital equally across the 2-3 held sectors — 50% each for two positions, 33% each for three. This prevents any single sector from dominating portfolio outcomes. Never concentrate more than 50% in a single ETF. When the defensive signal fires, move the entire portfolio to bonds or cash — partial hedges (e.g., 50% equity, 50% bonds) undermine the logic of the defensive filter and produce ambiguous journal data. SPDR sector ETFs carry an average expense ratio of 0.10-0.13%, making them cost-efficient for monthly turnover that generates approximately 24-36 trades per year.

Key Metrics to Track

• Benchmark Alpha — Monthly and YTD portfolio return vs. SPY. This is the single most important metric: a month of underperformance is only actionable if the journal shows whether it was a strategy failure or execution drift.
• Win Rate — Percentage of monthly rotations where the held sectors outperformed SPY. Expect this to be below 60% in any given year — the edge comes from asymmetry, not frequency.
• Max Drawdown — Peak-to-trough portfolio decline. Dual Momentum backtests (1974-2013) show max drawdown of roughly 25% vs. SPY’s 55% in the 2009 trough — this compression is the strategy’s primary value proposition.
• Defensive Signal Frequency — How many months per year the portfolio was in defensive mode. High frequency (above 4 months/year) may indicate a bear market regime requiring patience, not strategy changes.

Journal Fields for ETF Rotation Trades

Field	What to Record	Example
Rotation Date	First trading day of month	”Nov 1, 2022”
RS Scores (All 11 Sectors)	Composite score or rank for all 11 ETFs	”XLE: #1 (+42%), XLV: #2 (+8%), XLU: #3 (+5%)“
Sectors Entered	ETFs bought this rotation	”XLE, XLV”
Sectors Exited	ETFs sold this rotation	”XLK, XLY”
Defensive Signal Active	SPY vs. 10-month SMA status	”No — SPY above 200-day MA”
Portfolio Return vs SPY	End-of-month comparison	”Strategy: -1.2%, SPY: +5.4%“

Practical Example

On November 1, 2022, a trader with a $50,000 portfolio runs the monthly RS screen. XLE scores #1 with a 6-month return of +42%, XLV scores #2 at +8%, and XLU scores #3 at +5%. SPY is above its 200-day MA, so the defensive filter is inactive and all three top sectors pass the absolute momentum filter.

The trader sells October’s holdings (XLK and XLY) and deploys: $25,000 into XLE at $93.50 per share (267 shares) and $25,000 into XLV at $136.20 per share (183 shares). XLU is excluded to keep the portfolio to two positions at 50% each.

In JournalPlus, the trader logs: rotation date Nov 1, RS ranks for all 11 sectors, SPY 200-MA status = bullish, prior month P&L vs SPY.

By December 1, XLE has declined to $89.10 (-4.7%, a loss of $1,175) and XLV has risen to $140.80 (+3.4%, a gain of $850). Net portfolio change: -$325 (-0.65%), while SPY gained +5.4% that month. The journal shows one month of underperformance — but the full 12-month log reveals the strategy is +18% YTD vs. SPY at -14%, confirming this is a single noisy month, not a broken system.

Common Mistakes

1. Rotating mid-month — Executing on random dates rather than the first trading day introduces timing noise that makes month-over-month comparisons useless. Consistent dates are non-negotiable for journal integrity.

2. Skipping the absolute momentum filter — Holding the “best” sector when the whole market is in a downtrend (all sectors below T-bills) turns relative strength into a losing position. The 2022 bear market showed that even XLE’s +58.5% annual gain had multi-month drawdown periods that the absolute filter would have partially sidestepped.

3. Overriding the defensive signal — When SPY closes below the 10-month SMA, many traders rationalize staying in “strong” sectors. The 2022 case study — where XLK fell 33.2% while XLE gained 58.5% — is the exception; in most bear markets, all sectors fall together. The defensive signal exists for the average case.

4. Not logging all 11 RS scores — Recording only the sectors you bought makes it impossible to audit whether the ranking was applied correctly. If you log all 11 scores each month, you can reconstruct any rotation decision years later.

5. Confusing strategy underperformance with execution drift — A month where the strategy lags SPY may mean the system is broken, or it may mean you rotated on the wrong day, used incorrect return calculations, or skipped the absolute momentum check. Without a complete journal, these two explanations are indistinguishable. This is the journaling infrastructure that separates disciplined rotators from discretionary guessers.

How JournalPlus Helps with ETF Rotation

JournalPlus supports the custom journal fields that ETF rotation requires — traders can add fields for RS scores, defensive signal status, and benchmark comparison directly to each rotation entry, keeping all decision data alongside the trade record. The monthly P&L analytics make it straightforward to compare portfolio return vs. SPY for each period, surfacing the benchmark alpha metric that drives rotation decisions. Custom tags let traders mark each entry as “equity rotation” or “defensive” and filter historical performance by regime type. The trade review workflow is particularly valuable here: because rotation decisions compound over years, a structured end-of-month review against the full RS log is the primary tool for catching execution drift before it distorts strategy assessment.