- Over 16 years, systematically selling SPX puts produced $148,758 with a single contract: profitable, with a 91.5% win rate and a Profit Factor of 2.81.
- But the average win ($2,160) is one quarter of the average loss (−$8,233): a payoff ratio of 0.26. You win small, often — and lose big, rarely.
- In March 2020 the mark-to-market drawdown hit −$63,283, pushing the account into negative territory (−$18,792) and wiping out ten years of gains — before recovering within a few weeks.
- The account sat below its previous high 65.6% of the time. The deciding variable isn't return: it's survival.
- Professionals sell premium with tail-risk protection, synthetic structures and hedges — and not just on puts: on calls too.
It's one of the most popular questions among people getting into options: does selling puts actually pay off? Forums have been debating it for twenty years, gurus post screenshots of the premium they've collected, and the skeptics reply "ask the people who were there in 2020." As always on this blog, we let the data answer: a 16-year backtest of systematic SPX put selling, rebuilt day by day, in dollars, with nothing swept under the rug.
The strategy tested: systematic "naked" put selling on SPX
A put option is insurance against a decline: the buyer pays a premium and gets the right to "sell" the index at a set price (the strike) before expiration. The seller plays the insurer: they collect the premium up front and, if the index is above the strike at expiration, they keep all of it. If the index instead crashes below the strike, they pay the difference — which can far exceed the premium collected.
"Naked" means sold with no protection at all: no long option as a hedge, no hedge on the underlying. "Out-of-the-money" (OTM) means the strike is below the current price: in our test, roughly 5% below.
The logic is the simplest — and most widespread — in the options world: you sell an out-of-the-money put on the S&P 500 index and collect the premium, betting that the market will be above the strike at expiration. Each month a new put is sold, selected by a systematic rule: 0.20 delta — in practice, an option the market prices with roughly a 20% probability of finishing in-the-money — which across the sample corresponds on average to a strike 5.0% below the current price. Expiration is about 45 days out, and the position is held to expiration: no stop-loss, no defensive rolling.
It's the purest form of the premium harvested by the volatility seller: as long as the index doesn't crash below the strike, the put expires worthless and the seller keeps the entire premium (on average $2,199 per contract). When the market does break through the strike, the seller pays the difference — potentially far more than the premium collected.
Parameters observed in the backtest
| Underlying | $SPX (index, cash-settled) |
| Direction | Short put |
| Size | 1 fixed contract (×100) |
| Selection rule | Systematic 0.20 delta |
| Resulting average distance | 5.0% OTM |
| Average premium collected | $2,199 (21.99 pts) |
| Days to expiration | ~45 (monthly) |
| Management | None — held to expiration |
| Notional controlled | $107,500 → $654,000 |
The short answer: yes, but not for the reasons you think
Over 16 years the strategy produced $148,758 with a single contract, winning 91.5% of the time with a Profit Factor of 2.81. Taken in isolation, those numbers look like every trader's dream. But the same track record hides a dark side: a single trade lost −$20,249, the mark-to-market drawdown hit −$63,283 — in March 2020 equity fell to −$18,792, erasing ten years of gains — and the account spent 65.6% of the time below its previous high. Selling puts means picking up pennies in front of a steamroller: the data show that, with a single contract and adequate capital, the steamroller was survivable and even profitable. But survival — not return — is the real variable at stake.
The equity curve: 16 years rebuilt day by day
The curve below is the account's mark-to-market value: not just the profits realized when each trade closes, but the daily value of the open position. It's the honest way to look at an options strategy, because it shows the pain of positions that are still open — the pain a list of "closed" trades hides.
Equity curve — daily mark-to-market (in $)
The drawdown: how deep is the hole?
Drawdown (underwater) curve — distance from the previous high, in $
⚠️ The March 2020 paradox
The mark-to-market drawdown reached −$63,283, taking equity down to −$18,792: an account worth more than $44,000 after ten years of trading found itself in negative territory within a few weeks. And yet — this is the most instructive finding of the entire study — the trade open during Covid doesn't appear among the worst realized losses: held to expiration, the position had largely recovered by May 8, 2020. Those who held on recovered; those who were undercapitalized or got a margin call turned a temporary loss into a permanent one. That's the difference between a mark-to-market loss and a realized loss — and it's the lesson that separates the traders who survive from the ones who blow up.
Every metric, in dollars
📈 Performance
| Total net profit | $148,758 |
| Gross profit | $231,090 |
| Gross loss | −$82,332 |
| Average annual profit | $9,304 |
| Best year (2021) | $27,453 |
| Worst year (2018) | −$13,609 |
| Positive years / total | 12 / 16 |
| Profit Factor | 2.81 |
🎯 Trade statistics
| Number of trades | 117 |
| Win rate | 91.5% |
| Trades won / lost | 107 / 10 |
| Expectancy per trade | $1,271 |
| Average win | $2,160 |
| Average loss | −$8,233 |
| Payoff ratio (win/loss) | 0.26 |
| Largest win | $5,664 |
| Largest loss | −$20,249 |
| Std. dev. per trade | $3,566 |
| Max consecutive wins | 23 |
| Max consecutive losses | 2 |
🛡️ Risk
| Max Drawdown (mark-to-market) | −$63,283 |
| Date of the low | 2020-03-23 |
| Equity at the low | −$18,792 |
| New high recovered | 2020-05-08 |
| Longest underwater period | 711 days |
| Time spent in drawdown | 65.6% |
| Annual P&L volatility | $19,857 |
| Sharpe ratio (on P&L, rf=0) | 0.32 |
| Sortino ratio | 0.46 |
| Net Profit / Max Drawdown | 2.35 |
| MAR (annual profit / MaxDD) | 0.15 |
The asymmetry: win small often, lose big rarely
This is the single most important concept in the whole study. The strategy wins 91.5% of the time, but the average win ($2,160) is barely one quarter of the average loss (−$8,233). The payoff ratio is 0.26.
This profile — many small wins and rare catastrophic losses — is the very definition of selling volatility. It works as long as the frequency of wins offsets the size of the losses, and in the backtest it did (Profit Factor 2.81). But it's a fragile balance: just a few more losses, or a single one bigger than expected, is enough to flip the entire result.
- The 10 losing trades (out of 117) burned through $82,332 of profits
- The single worst loss (−$20,249) equals ~9 average wins
- Max consecutive losses: 2 — but when they come, they hurt badly
Distribution of per-trade results
The sequence of 117 trades
The 10 losing trades, one by one
Every loss corresponds to a real episode of market stress: the 2010 flash crash, the August 2011 US downgrade, the late-2018 selloff, the 2022 bear market. The other 107 trades all expired worthless, handing the seller the full premium.
| Trade | Opened | Strike | SPX at open | SPX at expiry | SPX chg. | P&L |
|---|---|---|---|---|---|---|
| #90 | 2022-04-06 | 4185 | 4,481 | 3,938 | −12.1% | −$20,249 |
| #66 | 2018-11-16 | 2610 | 2,736 | 2,459 | −10.1% | −$13,183 |
| #12 | 2011-07-15 | 1250 | 1,316 | 1,127 | −14.4% | −$11,248 |
| #43 | 2015-12-02 | 1975 | 2,080 | 1,867 | −10.2% | −$9,311 |
| #65 | 2018-10-03 | 2820 | 2,926 | 2,716 | −7.2% | −$8,819 |
| #112 | 2025-03-04 | 5435 | 5,778 | 5,300 | −8.3% | −$8,270 |
| #3 | 2010-04-16 | 1135 | 1,192 | 1,050 | −11.9% | −$7,648 |
| #21 | 2012-10-03 | 1385 | 1,451 | 1,353 | −6.7% | −$2,102 |
| #101 | 2023-09-15 | 4305 | 4,450 | 4,276 | −3.9% | −$823 |
| #93 | 2022-09-07 | 3705 | 3,980 | 3,656 | −8.1% | −$680 |
Year by year: how results are spread over time
Annual profit and loss (in $)
| Year | P&L | Trades | Won | Win% |
|---|---|---|---|---|
| 2010 | −$193 | 7 | 6 | 86% |
| 2011 | −$3,202 | 7 | 6 | 86% |
| 2012 | $4,269 | 8 | 7 | 88% |
| 2013 | $7,280 | 7 | 7 | 100% |
| 2014 | $7,115 | 6 | 6 | 100% |
| 2015 | $11,676 | 7 | 7 | 100% |
| 2016 | $324 | 8 | 7 | 88% |
| 2017 | $8,828 | 8 | 8 | 100% |
| 2018 | −$13,609 | 8 | 6 | 75% |
| 2019 | $13,601 | 7 | 7 | 100% |
| 2020 | $26,370 | 6 | 6 | 100% |
| 2021 | $27,453 | 8 | 8 | 100% |
| 2022 | −$876 | 7 | 5 | 71% |
| 2023 | $20,212 | 8 | 7 | 88% |
| 2024 | $21,780 | 8 | 8 | 100% |
| 2025 | $17,725 | 7 | 6 | 86% |
How much capital do you really need? Returns in perspective
Is a $148,758 profit a lot or a little? It depends on the capital you have to tie up — and, above all, on how much you need to set aside so you don't blow up during the drawdown.
To sell a naked put, your broker requires margin: collateral locked in the account, typically 15-20% of notional under Reg-T. If mark-to-market losses erode the account below the required margin, you get a margin call: either you deposit more capital, or the broker liquidates the position for you — usually at the worst possible moment. That's the mechanism that turns a temporary loss into a permanent one.
The survival math
- Broker margin (Reg-T) for a naked SPX put: ~15-20% of notional = $50,408 on average
- But margin isn't enough: during Covid, equity dropped by −$63,283
- To absorb that hit without a margin call you needed at least ~$70,000-80,000 of dedicated capital per contract
- Anyone trading with less was force-liquidated at the low, locking in the loss
Return on capital (illustrative estimate)
| Average annual profit | $9,304 |
| Prudent capital / contract | ~$75,000 |
| Estimated average annual return | ~12-13% |
| Max drawdown on capital | ~80-85% |
| Net Profit / Max Drawdown | 2.35 |
| MAR ratio | 0.15 |
So, is selling puts worth it?
✓ When it makes sense
- You have ample capital relative to notional (no aggressive leverage)
- You can psychologically handle five-figure drawdowns and months underwater
- You use it as a source of premium within a diversified portfolio, not as your only strategy
- You're willing to hold the position through moments of panic (or you have a structured defense plan)
- You want a steady stream of returns and can stomach the occasional beating
✕ When it's a mistake
- You trade undercapitalized or with stretched margin: the next crisis will liquidate you
- You judge the strategy only by its win rate, ignoring the payoff
- You have no plan for a −$63,000 mark-to-market hit: panic will sell at the low for you
- You need the capital soon: the account is below its previous high 65% of the time
- You confuse "high probability of winning" with "low risk": they're opposites
The data say yes: selling SPX puts was systematically profitable for 16 years ($148,758, PF 2.81, 12 positive years out of 16). But they also say that profitability is not the same as risk: the strategy makes money by selling insurance against crashes, and every so often a crash comes and the claim has to be paid. Success doesn't depend on the ability to "predict the market" — most of the time you don't need to — but on the ability to survive the moments when you're wrong. Those with the capital, discipline and stomach to sit through a −$63,283 drawdown without folding collected a real, repeatable premium. Those without them simply postponed their date with the steamroller. It's not a money machine: it's selling insurance. And like every insurer, you make money in normal times and you survive — or go bust — in exceptional ones.
Beyond naked selling: how professionals sell premium
The backtest answers the question in the title with a "yes, with caveats." In real-world trading my answer is more clear-cut: selling puts, done with the right approach, really does pay — but the "right approach" starts exactly where this backtest ends. The naked, hold-to-expiration version is the perfect case study for understanding the mechanics; no professional, however, stops there: the first requirement is adopting tail-risk protection models.
Market returns don't follow the "normal" curve: extreme events — the crashes of 2008 and 2020 — are far more frequent and more violent than classical statistics predicts. These are the so-called fat tails of the distribution. The naked option seller is, by construction, exposed right there: they profit from the ordinary 90% of scenarios and pay the bill in the extreme 10%.
Protection exists, and it transforms the risk profile: buying further-out puts against the ones sold (the spread has a maximum risk that's defined and known in advance), volatility and regime filters that cut or eliminate exposure when the market enters the danger zone, conservative sizing relative to notional, and hedges on the underlying. These defenses cost part of the premium collected: they are, literally, the insurance premium that even the insurer has to pay. It's the difference between picking up pennies in front of the steamroller and doing it with an escape route already planned.
There's one more clarification that makes the answer more accurate: rather than "selling puts pays," it would be fairer to say that selling options pays. Calls exist too: premium can be harvested on both sides of the market, and sticking to just one side means giving up half the opportunities — and some of the diversification. The right way to do it, though, is more involved than the plain systematic selling we tested here: it calls for synthetic structures, combinations with the underlyings, and targeted hedges built around the market regime.
Personally, I use these models and run this activity alongside my algorithmic trading: two different engines that complement each other — the systems trade stocks directionally, while premium selling monetizes volatility. How these structures are built in practice — spreads, hedges, regime filters — is material for upcoming studies on this blog.
How we ran the numbers
Methodology. Equity curve rebuilt from the backtest's daily mark-to-market series (5,841 observations, 2010-01-04 to 2025-12-31). Drawdown calculated as the distance from the previous cumulative high. Trade metrics calculated on the 117 realized P&Ls. All values are in US dollars on 1 SPX contract (×100 multiplier), before taxes, with commissions already included in the source P&L. Sharpe/Sortino calculated on daily equity changes (rf=0, annualized over 252 days).
This article is also available in Italian.