What has the S&P 500 returned per year over the last 10 years?

S&P 500 Buy and Hold: Returns, Risk and Drawdowns (10-Year Data)

The benchmark every strategy on Exent is measured against: annual returns, volatility, Sharpe ratio and drawdowns of the S&P 500 from Jul 2016 to Sep 2026.

David, Senior AnalystUpdated Oct 12, 20264 min readHow we research

Key takeaways

S&P 500 (buy and hold): +15.2% a year vs +15.2% for the S&P 500 (Jul 2016–Sep 2026, backtest).
Sharpe ratio 0.88 vs 0.88; max drawdown −23.9% vs −23.9%.
Its worst calendar year in the window was 2022 at −18.2%.
This is the benchmark itself.

In this article

S&P 500 (buy and hold) vs the S&P 500: the results
Year by year
Growth of $10,000
How the backtest is built

S&P 500 (buy and hold) vs the S&P 500: the results

From Jul 2016 to Sep 2026, s&p 500 (buy and hold) returned +15.2% a year against +15.2% for the S&P 500, with volatility of 15.2% against 15.2%. This is the benchmark itself.

Metric	S&P 500 (buy and hold)	S&P 500
Annual return (CAGR)	+15.2%	+15.2%
Volatility	15.2%	15.2%
Sharpe ratio	0.88	0.88
Sortino ratio	1.39	1.39
Max drawdown (month-end)	−23.9%	−23.9%
COVID crash (Feb–Mar 2020)	−19.4%	−19.4%
2022	−18.2%	−18.2%
Calendar years beating the S&P 500	0 of 9	—
Correlation with the S&P 500	1.00	1.00

Year by year

Year	S&P 500 (buy and hold)	S&P 500	Difference
2026 (YTD)	+12.1%	+12.1%	0.0%
2025	+17.7%	+17.7%	0.0%
2024	+24.9%	+24.9%	0.0%
2023	+26.2%	+26.2%	0.0%
2022	−18.2%	−18.2%	0.0%
2021	+28.7%	+28.7%	0.0%
2020	+18.3%	+18.3%	0.0%
2019	+31.2%	+31.2%	0.0%
2018	−4.6%	−4.6%	0.0%
2017	+21.7%	+21.7%	0.0%

Growth of $10,000

End of	S&P 500 (buy and hold)
2016	$10,788
2017	$13,128
2018	$12,529
2019	$16,441
2020	$19,454
2021	$25,043
2022	$20,491
2023	$25,855
2024	$32,290
2025	$38,011
Sep 2026	$42,626

How the backtest is built

Holdings: SPY. A market-cap-weighted index fund: the benchmark most investors are measured against.

Ten years is one market cycle dominated by US large‑cap growth, so results for value, small caps and international‑style tilts can look very different over other periods. Compare every strategy side by side on the strategies page, or read why beating the S&P 500 is so hard.

Backtested (hypothetical) results calculated by Exent from historical ETF prices with dividends reinvested, monthly rebalancing unless stated, and no trading costs, taxes or fees beyond the funds’ own expense ratios. Backtests are not actual trading and have hindsight bias. Past performance does not guarantee future results. Not investment advice.

Measure your own portfolio the same way

Upload a screenshot of your holdings; no brokerage login.
Exent computes your return, volatility, Sharpe, Sortino and drawdowns and compares them with a risk‑matched benchmark, not just the S&P 500.
The efficient frontier shows whether a different mix of what you already own took less risk for the same return.

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

Frequently asked questions

From Jul 2016 to Sep 2026 the S&P 500 (SPY, dividends reinvested) returned +15.2% a year with 15.2% volatility and a worst month-end drawdown of −23.9%.

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How does your own portfolio compare?

Exent measures your portfolio against a risk-matched benchmark, shows its Sharpe ratio, drawdowns and crash exposure, and where it sits on the efficient frontier.

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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.