QQQ MACD backtests: is a 20% annual return reliable?

A high return is not automatically a model advantage

In the period beginning in 2013, the cached QQQ holding benchmark compounds at 20.45% on the research convention used here. In the overlapping period beginning in 2020, it compounds at 21.25%. A strategy reporting more than 20% in such a market must still be compared with simply holding the same asset over the same dates.

A model can earn a positive return primarily because the asset rose. It may improve risk, reduce market participation, add leverage or do none of those things. Those are different outcomes. The appropriate question is what the model changes after accounting for exposure, costs and the benchmark, not whether a headline number sounds attractive.

What the two historical model summaries show

We recalculated two existing MACD holding-or-cash variants, labelled A and B without disclosing their settings or decision rules. Both earn less than holding QQQ in the displayed periods beginning in 2013 and 2020. Their daily-close maximum drawdowns are also smaller in those periods. That is a risk–return trade-off, not a demonstration that a momentum indicator adds a reliable return premium.

The earlier segment also matters: Model A has a negative compound return from 1999 through 2012, while the holding benchmark is positive. A conclusion drawn only from a recent rising market would omit a materially different environment. The two recent segments overlap and must not be treated as independent replications.

Data and performance conventions

The source is the project’s saved adjusted-daily-price history for the QQQ ETF, ending on 9 October 2026. Adjustment is the data provider’s treatment of corporate actions and distributions, not a reconstruction of an individual investor’s taxes. Prices were checked for positive finite values and unique dates. This is the ETF series, not a crypto exchange’s QQQ-labelled perpetual or a leveraged ETF.

CAGR uses compounded daily returns with a year defined as 252 trading observations; drawdown uses daily marked equity against its running high. The models include a preset turnover charge, while the holding benchmark omits a one-time purchase and sale charge. Neither result includes personal taxes or a complete live-slippage model. Segment results are slices of an existing historical return series, not separate newly funded accounts.

A lagged daily backtest is not a fill record

The historical implementation applies the prior observation’s model position to the following close-to-close return. This avoids directly using the following day’s signal, but still uses an idealised daily-price convention. It does not establish that an order placed after computing a closing signal could transact at that same close, or reproduce next-open gaps, actual spreads and rejected orders.

The table should therefore be read as modelled historical evidence rather than an executable live track record. Cash earns no interest in this particular comparison. Changing cash treatment, execution timing or financing can change the result, so results from other implementations cannot be combined without reconciling those conventions.

What would support a stronger claim

A claim of repeatable outperformance needs pre-specified evaluation, information available at the time, realistic execution and costs, and testing on genuinely unused observations. Searching many settings and showing only the best introduces selection bias. A smoother equity curve can also result from holding less market risk, rather than a forecasting advantage.

To preserve confidential model details, this article does not publish settings, signal combinations, exposure rules or an execution recipe. That also limits independent strategy replication: source fingerprints identify the price snapshot, not proof of every private model calculation. The evidence supports examining trade-offs, not promising more than 20% a year.

Can a QQQ MACD model guarantee 20% annual returns?

No. The archived comparisons include periods when QQQ buy-and-hold already exceeded 20% annualized, while the tested model summaries earned less in the same periods. A historical annualized figure is not a promised future yield.

What should a QQQ momentum backtest be compared with?

Compare the same dates and price treatment with a clear QQQ holding benchmark, then examine drawdowns, costs and validation limits. A lower drawdown and a higher return are different findings, and neither proves out-of-sample reliability on its own.

Limitations

Historical, selected model variants and overlapping periods; full model reproduction is intentionally unavailable because settings are not published. Execution is idealised, costs are assumed and data are provider-adjusted. No live performance or future annual-return target is established.

Sources and data access

• Invesco: QQQ holdings, index and performance definitions
• Yahoo Finance: QQQ historical data provider

Cited sources document external facts or data formats; they do not endorse our findings. The public snapshot contains the table and methods. Source-file fingerprints are included for recalculated datasets. Full archived raw files are not distributed here; fingerprints identify the files used, rather than independently proving the results.

Aggregate data snapshot (JSON) · Markdown · Methods and limitations

Live prior 30-day hourly baseline — separate from the historical study

Only the current watch list is shown, up to 12 assets. Missing or stale estimates remain unavailable. Venue and quote currency are kept separate; beta needs matching BTC data. Hourly statistics are not minute-move probabilities.

Observation cutoff (UTC): 20/10/2026, 15:01