TQQQ vs QQQ

#What this plan actually returned

These are real results, not estimates. We ran $10,000 up front plus $500 a month from September 9, 2016 to September 9, 2026 (10.0 years), with dividends reinvested, against actual daily closing prices for each fund.

#Reading the result

TQQQ finished at roughly $721,000 against QQQ’s $241,000 on the same $70,000 of contributions. That is about three times the ending value, which looks like the leverage worked exactly as advertised.

Now read the last column. TQQQ’s worst decline was about 82 percent, against 35 percent for QQQ. That is not three times worse. On a 35 percent underlying decline, a naive 3x expectation would be somewhere near a total loss, and the reason it landed at 82 percent rather than 105 percent is the same daily reset mechanism that makes these products behave unlike a simple multiplier in both directions.

#What the daily reset actually does

TQQQ targets three times the daily return of the Nasdaq-100. The word daily carries the entire burden. Each trading day the fund rebalances its exposure to restore 3x leverage against its new asset base, which means the multiplier applies to one day at a time and never to a multi-day period.

The consequence is that returns compound off a base that moves every day, and volatility drags on the result. A simple illustration: an index that falls 10 percent and then rises 11.1 percent is back where it started. A 3x daily fund on that same path falls 30 percent, leaving 70 percent of its value, then rises 33.3 percent, reaching about 93 percent. The index is flat and the leveraged fund is down 7 percent, with no fees or costs involved. The loss came entirely from the path.

The more the index oscillates, the worse this gets. In a smooth, sustained uptrend the same mechanism works in your favor, because each day’s gain is levered off a larger base. The last decade contained an unusual amount of the second condition, which is why the headline number in the table looks as good as it does.

#The window is doing a great deal of work here

TQQQ launched in February 2010, roughly at the start of one of the longest bull markets in US history. It has never operated through a multi-year bear market. Every backtest of this fund, including the one above, is measured over a period selected by the fund’s own inception date, and that period happens to be close to the best possible environment for a daily-reset leveraged product.

The 2022 decline is the closest thing to a real test in the record, and it is visible in the dates: TQQQ’s worst window ran from November 19, 2021 to December 28, 2022, slightly longer than QQQ’s, ending more than a month later. Even that was a single drawdown inside an otherwise favorable decade.

For what a genuinely hostile environment would imply, the QQQ 2000 to 2010 comparison shows the underlying index falling 83 percent peak to trough. A 3x daily product through that sequence is examined in what leveraged ETFs would have done in a real bear market.

#Costs that compound alongside the leverage

Leveraged ETFs carry meaningfully higher expense ratios than plain index funds, and the fund also pays financing costs on the borrowed exposure it maintains. Those financing costs rise with interest rates, which means the product became more expensive to hold during exactly the period when its underlying index was falling.

Both of these are reflected in the fund’s actual price history, so they are already inside the numbers above. They are worth naming because they are structural ongoing drags rather than one-time events, and they work against you in flat and choppy markets where the leverage provides no benefit.

#What to test

• →Run a window from November 2021 to December 2022 by itself. Watching the drawdown in isolation is more instructive than seeing it absorbed into a favorable decade.
• →Run the plan ending at the end of 2022 rather than today, so the period finishes in the drawdown rather than after the recovery.
• →Add QQQ and VOO alongside it so the comparison includes an unleveraged baseline.
• →Compare how much of each final value came from contributions versus gains. Leveraged results are far more sensitive to when contributions landed.