The S&P 500 is the index of 500 large US companies. An active fund is one whose manager picks shares to try to beat an index. Over the 20 years to June 2026, 93% of US active funds that buy large companies did worse than the S&P 500. The count comes from S&P Dow Jones Indices, which publishes it twice a year.
Systematic investing swaps the manager's choices for written rules. So can a rule do better? We tested one simple rule on the S&P 500 from April 2017 to September 2026. It holds the index only while the price is above its average of the past 200 trading days. We measured it on return and on risk.
Can systematic investing beat the S&P 500? Systematic investing means following written rules for what to buy, how much to hold and when to sell. In our test of one simple rule on the S&P 500 since 2017, the rule made less money than holding the index, but its worst fall was much smaller.
Over the 20 years to June 2026, 93% of US active funds that buy large companies trailed the S&P 500, according to S&P Dow Jones Indices.
A rule that held the S&P 500 only while its price was above its average of the past 200 trading days grew $100 to $278 after costs. Simply holding grew it to $378.
The rule's worst fall was 19.9%, against 33.7% for holding. Measured as return per unit of risk, the two finished about level.
What beating the S&P 500 means
The easiest way to own the S&P 500 is through an index fund, a fund that holds every share in the index. We explain how they work in What Is an Index Fund? Our test uses SPY (the S&P 500 exchange-traded fund, or ETF). It trades like a share.
Systematic investing is covered in full in What Is Systematic Investing? Here the question is narrower. A strategy can beat the index in two ways:
On return: it ends with more money.
On risk-adjusted return: it earns as much or more for each unit of risk taken.
Three measures carry the comparison:
Volatility: how much the daily returns swing, scaled to a year.
Drawdown: the fall from a previous high to a later low. The worst one is the maximum drawdown.
Sharpe ratio: the yearly return above the Treasury bill rate, divided by volatility. A Treasury bill is a loan to the US government that is repaid within a year. A higher Sharpe ratio is better.
How many active funds trail the S&P 500
SPIVA is S&P Dow Jones Indices' scorecard of active funds against their benchmark index. Its Mid-Year 2026 US edition, published on 17 September 2026, covers periods ending 30 June 2026. It uses returns after fund fees. Large-cap funds are the ones that buy large companies.
Source: S&P Dow Jones Indices, SPIVA U.S. Scorecard Mid-Year 2026; YX Insights
Over one year, 79% of large-cap active funds trailed the S&P 500. Over five years it was 89%. Over 20 years it was 93%. In the first six months of 2026 alone, the figure was 67%.
The scorecard also counts funds that closed or merged as failures. That matters over long periods. Of the 690 large-cap funds alive at the start of the 20 years, only 37% were still running at the end.
The 200-day rule we tested on SPY
A moving average is the mean of the last set of closing prices, updated each day. The 200-day average uses the last 200 trading days. When the price sits above it, the trend is up.
The rule has two lines:
Hold SPY on any day after it closed above its 200-day average.
Hold cash otherwise, earning the 3-month Treasury bill rate.
A backtest applies a rule like this to past prices, as if it had been traded. In ours, each trade happens one day after the signal. We charge 0.1% on every switch, to cover dealing costs. Dividends are counted. Our price data starts in June 2016, so the first 200-day average exists on 4 April 2017. The test runs from there to 24 September 2026, about nine and a half years.
We chose the 200-day because it came first of eleven lengths tested on SPY in our essay I Tried to Debunk the 200-Day Moving Average. That test used data running to August 2026.
SPY buy and hold vs the 200-day rule since 2017
Source: YX Insights price data; FRED (DTB3); YX Insights
Holding SPY turned $100 into $378, or 15.1% a year. The rule turned $100 into $278, or 11.4% a year after costs. So the rule gave up 3.7 percentage points a year. It held SPY on 83% of trading days and sat in cash for the rest.
Strategy | $100 became | Yearly return | Volatility | Sharpe ratio | Worst fall | Days in SPY | Trades |
|---|---|---|---|---|---|---|---|
Buy and hold SPY | $378 | 15.1% | 18.3% | 0.72 | 33.7% | 100% | 0 |
200-day rule, before costs | $292 | 12.0% | 12.2% | 0.78 | 18.1% | 83% | 50 |
200-day rule, after 0.1% a trade | $278 | 11.4% | 12.2% | 0.74 | 19.9% | 83% | 50 |
Source: YX Insights price data; FRED (DTB3); YX Insights
The rule was calmer. Its volatility was 12.2%, against 18.3% for holding. Before costs, its Sharpe ratio was 0.78, against 0.72 for holding. After the 0.1% cost on each of its 50 trades, the rule's Sharpe ratio fell to 0.74. A lead of 0.02 over holding is too small to call a win.
So the rule did not beat the S&P 500 on return. On return per unit of risk, it roughly matched it.
How the rule handled the falls of 2020, 2022 and 2025
Source: YX Insights price data; FRED (DTB3); YX Insights
The chart shows each strategy's fall from its previous high, with the rule after costs. Holding SPY fell 33.7% to 23 March 2020. The rule's worst fall was 19.9%, from January 2022 to March 2023. In 2025, SPY fell 18.8% to 8 April, while the rule fell 9.7%.
The rule also had weak spots that holding did not:
Whipsaws. A whipsaw is when the rule sells after a drop, then buys back higher soon after. From SPY's high on 19 February 2020 to the rule's final exit on 5 March, the rule lost 17.7%. Holding lost 10.6%.
Late return. After the rule sold on 5 March 2020, SPY fell another 25.8% to its low on 23 March. It then rose 34.1% by 26 May. The rule bought back that day, only 0.5% below where it sold. So the exit saved almost nothing.
Choppy markets. From 3 January to 11 April 2022, the price kept crossing its 200-day average. The rule traded nine times in that stretch. It lost 12.6%, while holding lost 7.1%.
What one test of one rule cannot prove
The result above is one test of one rule on one index. Four things limit what it proves:
Hindsight. We picked the 200-day after it came first in our earlier test. That test used data up to August 2026, which overlaps this one. Choosing a rule after seeing it work flatters the backtest. We explain this trap in What Is Backtesting?
A small sample. Nine and a half years is one stretch of history. A different decade could rank the two strategies differently.
Other markets. In our essay's test, the same rule on QQQ (the Nasdaq-100 ETF) did worse than holding it, even before costs.
Tax. Each sale can trigger tax on gains in a taxable account. The test ignores it.
How to judge a claim that a strategy beats the S&P 500
A few checks help when reading any backtest or fund record:
Ask which kind of beat. More money, or the same money with smaller falls?
Check costs and timing. Look for a stated cost per trade and a one-day delay before each trade.
Check the period. It should include at least one big fall, such as 2020 or 2022.
Count the closed funds. A record that drops funds that shut down looks better than it was.
Our walk-through of a full report is in How to Read a Backtest Report. For a portfolio built on more than one rule, see Right for Years: Edge or Luck?
So can a simple rule beat the S&P 500? On return, ours did not: it made 11.4% a year against 15.1% for holding. On return per unit of risk it roughly matched the index, with a much smaller worst fall.
Learn more with YX Insights
This explainer is part of the YX Insights Academy. Each one takes a single idea and checks it against real data.
The same approach runs through everything else we publish:
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DISCLAIMER: This article is strictly educational. Any information or analysis in this note is not an offer to sell or the solicitation of an offer to buy any securities. Nothing in this note is intended to be investment advice and nor should it be relied upon to make investment decisions. Any opinions, analyses, or probabilities expressed in this note are those of the author as of the note's date of publication and are subject to change without notice.