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Does the 200‑Day Moving Average Strategy Work?

A tested answer: what holding the S&P 500 only above its 200‑day average did to returns, crash losses and taxes from 2017 to 2026, why it struggled after the lows, and how a price rule differs from a macro regime model.

Published Updated 7 min readHow we research

Key takeaways

  • Partly. In a hypothetical backtest (Jan 2017 – Sep 2026), holding the S&P 500 only while it closed above its 200‑day average cut the worst fall from −33.7% to −19.2%, but returned 10.3% a year vs 15.1% for buy and hold.
  • The rule switched 58 times in under ten years, about 29 exits, while the index had only five declines of 10% or more. Most exits were false alarms that often ended with buying back higher.
  • It cut the loss in every big selloff, most in the COVID crash (−17.4% vs −33.7%), then gave much of it back in the rebounds: 2020 returned 5.6% with the rule vs 18.3% holding.
  • All 10 of the best days and 8 of the 10 worst since mid‑2016 came while the S&P 500 was below its 200‑day average, so a rule like this sat out both the biggest rebounds and most of the worst days (Exent’s data).
  • A price rule reacts after a fall starts. Macro regime models try to read the conditions behind prices instead. Neither is right every time.

Does the 200‑day moving average strategy work?

It works as a loss limiter, not as a way to earn more. The rule is simple: hold the S&P 500 while it closed above its 200‑day moving average the day before, and hold T‑bills while it closed below. In a hypothetical backtest (Jan 2017 – Sep 2026), that rule cut the S&P 500’s worst fall by 14.5 percentage points. It also gave up about 5 points of return a year.

The table shows the rule on the two big index funds. “Time invested” is the share of days the rule held the fund. Results are before trading costs and taxes, with dividends reinvested. It is one tool among many in portfolio protection.

FundHold: a yearHold: worst fall200‑day rule: a yearRule: worst fallTime invested
S&P 500 (SPY)15.1%−33.7%10.3%−19.2%82%
Nasdaq‑100 (QQQ)21.4%−35.1%19.2%−21.9%83%
FundS&P 500 (SPY)Nasdaq‑100 (QQQ)
Hold: a year15.1%21.4%
Hold: worst fall−33.7%−35.1%
200‑day rule: a year10.3%19.2%
Rule: worst fall−19.2%−21.9%
Time invested82%83%

The pattern held on both. On the Nasdaq‑100 (QQQ) the rule cut the worst fall from −35.1% to −21.9% and gave up 2.2 points a year, with 34 switches. On the S&P 500 (SPY) the cost was larger, and the index crossed its average more often: 58 switches.

Market risk check, updated every trading day

Data through the close of Oct 20, 2026. The S&P 500 fell 1.2% over the last five trading days, and the Nasdaq‑100 fell 3.5%. The S&P 500 is 1.3% below its record close of Oct 6: a small dip from its record. It is 6.4% above its 200‑day average (+7.9% a week earlier). Its 20‑day volatility is 9.4% a year, calmer than 71% of trading days since 2016.

The S&P 500 vs its 200‑day average

Daily closes over the last year, through Oct 20, 2026. Green: the index above its average; red: below it.

−1.3%from its record closeRecord: Oct 6, 2026
+6.4%vs its 200‑day averageA week earlier: +7.9%
9.4%20‑day volatility (a year)Median since 2016: 12.2%
−1.2%last five trading daysNasdaq‑100: −3.5%

The three big US index funds

Through Oct 20, 2026. “vs 200‑day avg.” = how far the close sits above or below its 200‑day average.

Index fundLast 5 daysYear to dateFrom its highvs 200‑day avg.
S&P 500 (SPY)−1.2%+13.1%−1.3%+6.4%
Nasdaq‑100 (QQQ)−3.5%+17.0%−5.5%+6.8%
Russell 2000 (IWM)−0.3%+12.2%−9.6%−0.3%
Index fundS&P 500 (SPY)Nasdaq‑100 (QQQ)Russell 2000 (IWM)
Last 5 days−1.2%−3.5%−0.3%
Year to date+13.1%+17.0%+12.2%
From its high−1.3%−5.5%−9.6%
vs 200‑day avg.+6.4%+6.8%−0.3%

Exent macro regime score, today

Last updated Oct 20, 2026. Members only.

Exent regime pillarToday
Liquidity
Credit stress
Economic cycle
Sentiment
Regime: Risk ON · Neutral · Risk OFF

Price trend and volatility show what the market has already done. Exent’s macro regime score reads the backdrop behind it (liquidity, credit stress, the economic cycle and sentiment) and classifies it as Risk ON, Neutral or Risk OFF. Market intel members see today’s reading and get an alert when it changes.

Exent market data, daily closes; returns include dividends and interest. The S&P 500, Nasdaq‑100 and Russell 2000 are shown through the SPY, QQQ and IWM funds. Refreshed every trading day. It describes conditions; it is not a forecast or a recommendation. Past performance does not guarantee future results.

What happens when the S&P 500 falls below its 200‑day average?

Usually less than the headlines suggest, but every big selloff passes through it. A daily rule made about 29 exits from 2017 to 2026. In the same period the S&P 500 had five declines of 10% or more. So most breaks below the line were false alarms: the index dipped, recovered, and the rule often bought back higher.

Outside studies point the same way. Benzinga counted 16 SPY breakdowns below the line in ten years (by its own definition), and SPY was higher a year later in 80% of them. Traders watch the line anyway, because deep falls do cross it: an analyst quoted by Business Insider in March 2026 found the S&P 500 crossed its 200‑day average at the start of every bear market since at least 2000. In each of the four big selloffs since 2018, the rule stepped aside partway down and took a smaller loss:

SelloffHolding: largest fallWith the 200‑day rule
Q4 2018 selloff−19.3%−13.6%
COVID crash, 2020−33.7%−17.4%
2022 bear market−24.5%−15.0%
2025 tariff selloff−18.8%−9.4%

The fast COVID crash and the slow 2022 bear show the two sides. In 2020 the S&P 500 fell 34.1% in 23 trading days. The rule stepped aside partway down and roughly halved the loss. But it only came back once the index was above its average again, after much of the rally off the March low, so 2020 ended at +5.6% with the rule vs +18.3% for holding.

The 2022 bear lasted 195 trading days, with several sharp rallies. The rule cut the peak‑to‑trough fall from −24.5% to −15.0%. Then it kept switching on each rally and dip. Its own worst stretch ran from January 2022 to March 2023, at −19.2%: the worst fall of the whole test came from whipsaws in a slow bear, not from the crash.

Why did the rule return less? Whipsaws, rebounds and taxes

Because it was out for much of each rebound. The extreme days themselves roughly cancel out. In Exent’s data, all 10 of the S&P 500’s best days since mid‑2016 came while it was below its 200‑day average the day before, and so did 8 of the 10 worst. Missing both sets would have left the return about where it was: 15.5% a year vs 15.2%. The cost came from the weeks after each low, when the index climbed back toward its average while the rule still held T‑bills.

Whipsaws add to the cost. The index often dips just below its average and climbs back; as Yahoo Finance’s Jared Blikre noted in April 2026, the market sometimes briefly overshoots the average before its trend resumes. Each overshoot is a sale and a buyback at a higher price. Year by year, the rule beat holding in one calendar year (2022), matched it in two, and trailed in the rest:

YearHoldingWith the 200‑day rule
2018−4.6%−7.8%
2019+31.2%+16.0%
2020+18.3%+5.6%
2021+28.7%+28.7%
2022−18.2%−14.2%
2023+26.2%+12.0%
2024+24.9%+24.9%
2025+17.7%+12.5%
2026 (to Sep 2026)+12.1%+9.4%

Two costs are missing from the backtest. Trading costs are small for a fund like SPY, but they add up over 58 switches. Taxes can be large. In a taxable account, every switch out is a sale, and gains on positions held a year or less are taxed as ordinary income. Many investors who follow a trend rule run it inside an IRA or 401(k) for that reason. Re‑entry is the other hard part; see when to get back into the market.

Is a monthly 10‑month rule the same test?

No. A monthly rule and this daily rule are different tests, and their numbers should not be mixed. The guide does market timing work? reports a monthly rule: hold the S&P 500 when it closed the month above its 10‑month average, otherwise T‑bills. Over Jul 2016 – Sep 2026 it returned 9.4% a year vs 15.2% for buy and hold.

A monthly check tends to switch less often but reacts later; a daily check reacts sooner but tends to whipsaw more. Both versions cost return in the same decade, and the monthly one lost more than holding in 2022 (−20.1% vs −18.2%). The “death cross”, when the 50‑day average falls below the 200‑day, is a related signal built on the same average: see golden cross and death cross.

Price trend rules vs macro regime models

A price trend rule reacts after the fall starts; a macro regime model tries to read the conditions behind the fall. The 200‑day average only knows what prices did. A macro regime score combines families of economic and market data, such as liquidity, credit stress, the economic cycle and sentiment, into one reading.

Price trend rule (200‑day)Macro regime model
What it readsThe index’s own priceConditions behind prices: money, credit, growth, mood
When it reactsAfter prices have already fallenCan shift before or after prices break
Typical failureWhipsaws in choppy markets; can be late in very fast crashesSudden shocks that macro data does not show in advance
Re‑entryMechanical: back above the lineWhen the reading improves, which can lag the price low
Cost to followFree; any chart shows itUsually a research service or your own model

Exits matter more as risk rises. In the same test, the rule cut TQQQ’s worst fall from −81.6% to −54.8%, and its return was higher than holding, because avoiding deep losses on a 3× fund was worth more than the rebounds it missed. The details are in TQQQ and the 200‑day moving average.

Read the conditions behind the price with Exent

  1. Exent Predictive Market Intelligence publishes a daily macro regime score (Risk ON, Neutral or Risk OFF) that reads four pillars: liquidity, credit stress, the economic cycle and sentiment.
  2. Members get an alert when the regime changes, plus a daily macro briefing with cited sources and cross‑asset signals.
  3. Six model allocations show how exposure can follow the regime, from fully invested or in cash to a 2× model that uses leverage only in Risk ON.

Featured on Business Insider · Yahoo Finance · Benzinga

Exent is our product. Educational content, not investment advice.

Frequently asked questions

Not on return in Exent’s hypothetical test. From January 2017 to September 2026 the rule returned 10.3% a year on the S&P 500 vs 15.1% for buy and hold, but its worst fall was 19.2% instead of 33.7%.

Often not much. A daily rule exited about 29 times from 2017 to 2026, while the index had only five declines of 10% or more. But each of the four big selloffs since 2018 took the index below the line.

It reduced the loss in each of the four selloffs since 2018 in Exent’s test, by about half in the COVID crash. It reacts only after prices fall, and it missed much of the rebound after the lows.

A daily version on the S&P 500 switched 58 times between January 2017 and September 2026. In a taxable account every switch out is a sale that can realize gains.

No. The 10-month rule checks once a month, so it tends to switch less; the 200-day rule checks daily and reacts sooner but tends to whipsaw more. Both cost return in Exent’s tests over the same decade, and the monthly rule lost more than holding in 2022.

In the same hypothetical test it cut TQQQ’s worst fall from 81.6% to 54.8%, and the return was higher than holding (46.4% vs 42.5% a year), because deep losses compound on a leveraged fund.

Know when to hold the index, and when to step aside.

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Educational content, not investment advice. Examples are illustrative; past performance does not guarantee future results.

DISCLAIMER: Exent AI is an informational research platform and does not provide investment advice, financial advice, or act as an investment adviser, broker-dealer, or fiduciary. All content, analytics, and model outputs are provided for educational and informational purposes only and should not be relied upon as a recommendation to buy, sell, or hold any financial instrument. Investing involves risk, including the possible loss of principal. Exent AI does not execute trades, hold customer funds, or provide brokerage services. Past performance and hypothetical results are not indicative of future results. Third-party data and AI-generated outputs may be incomplete or inaccurate.