Why Most Options Buyers Lose: What the Academic Research on Retail Options Trading Shows

Retail options buyers lose money on average, according to the major peer-reviewed studies of their trades, and the losses come less from bad luck than from structure: wide bid-ask spreads, time decay, and paying more for volatility than the stock later delivers. Most of the money lost by retail traders flows to the market makers and option sellers on the other side.

In short: a 2023 Journal of Finance study by Bryzgalova, Pavlova, and Sikorskaya estimated that US retail options traders lost about $2.1 billion between November 2019 and June 2021, with losses concentrated in purchases of options expiring within a week, which carried an average quoted spread of 12.6%. A Review of Finance study by de Silva, Smith, and So found retail investors lost 5% to 9% on average on options bought around earnings announcements, and 10% to 14% around the most volatile ones. An earlier study of Dutch investors (Bauer, Cosemans, and Eichholtz, 2009) found option traders lost far more than stock traders. The evidence is not unanimous (a Cboe-supported 2025 working paper disputes some of these estimates), but the mechanics point the same way: you pay the spread on the way in and out, time value decays to zero, and implied volatility tends to be priced above what later happens.

A note on what “lose” means here

These studies measure average outcomes across very large numbers of trades. They do not say every buyer loses, or that any particular trade will. They also measure returns on trading, not on hedging: someone who buys a put to protect a stock portfolio and “loses” the premium may have got exactly what they paid for, the same way a home insurance policy that never pays out was not a mistake. The question is whether buying options as a speculative bet has been a good deal for retail traders on average. The evidence says no.

Study 1: Bryzgalova, Pavlova, and Sikorskaya (Journal of Finance, 2023)

“Retail Trading in Options and the Rise of the Big Three Wholesalers,” by Svetlana Bryzgalova, Anna Pavlova, and Taisiya Sikorskaya of London Business School, was published in the Journal of Finance (volume 78, issue 6, December 2023). The authors used new flags in US options transaction data to identify trades executed by the wholesalers that handle retail orders, and built a measure of retail options trading covering November 2019 to June 2021.

Their main findings:

Retail trading grew rapidly. By their measure, retail trading recently reached over 60% of total US options market volume. They note that this growth was facilitated by payment for order flow, and that nearly 90% of options payment for order flow came from three wholesalers.
Retail traders preferred short-dated, cheap options. About half of retail trades were in options with less than a week to expiry. Those options had an average quoted bid-ask spread of 12.6% and an average effective spread (what traders actually paid relative to the midpoint, after price improvement) of 6.6%.
They favoured calls and at-the-money strikes. Calls made up 69% of retail volume. 72% of trades were at the money and 23% slightly out of the money, where the average quoted spread was 29%.
Small trades were especially expensive. 42% of retail trades were “micro” size, up to $250, with an average quoted spread of 23.5%.
They lost money on average. Assuming a 10-day holding period, the aggregate retail portfolio lost about $2.1 billion over the sample. The worst month was January 2021, the meme-stock frenzy, at about $672 million.
Costs drove the losses. The authors estimated the indirect cost of trading (the distance between trade prices and the quote midpoint) at $6.4 billion across all retail trades in the sample, against about $900 million in direct commissions.
Buyers lost; sellers didn’t. Losses were concentrated in buying short-term options. The paper identifies two types of retail traders: those who buy short-term options and lose money, and those who sell them and earn significant profits, even after costs.

Study 2: de Silva, Smith, and So (Review of Finance)

“Losing is Optional: Retail Option Trading and Expected Announcement Volatility,” by Tim de Silva, Kevin Smith (both Stanford), and Eric So (MIT), was published in the Review of Finance (volume 30, 2026; online October 2025). It used Nasdaq data that breaks down options buying and selling by type of trader, across 32,758 quarterly earnings announcements between 2010 and February 2021.

The authors found that retail investors are drawn to options by anticipated volatility. They buy options in concentrated bursts before earnings announcements, especially those expected to cause big moves, and they shift toward options over stocks as expected volatility rises. In doing so they make three costly mistakes:

They overpay relative to the volatility that follows. Implied volatility before announcements tends to exceed the move that actually occurs.
They pay very wide bid-ask spreads. Spreads widen ahead of high-volatility announcements. For those announcements, the authors estimate that paying half the spread alone costs retail buyers about 9% of their investment.
They close positions slowly. After the announcement, implied volatility collapses and option prices predictably decay, but retail traders tend to hold for weeks.

The result: estimated losses of 5% to 9% of option investments on average around announcements, and 10% to 14% for the high expected-volatility announcements, totalling about $3 billion over the sample. Market makers were the primary beneficiaries. The mechanics of the post-earnings volatility drop are explained in implied volatility explained.

Study 3: Bauer, Cosemans, and Eichholtz (Journal of Banking & Finance, 2009)

“Option Trading and Individual Investor Performance,” by Rob Bauer, Mathijs Cosemans, and Piet Eichholtz, published in the Journal of Banking & Finance (volume 33, 2009), studied account-level records of individual investors at a Dutch online broker. It predates commission-free apps, which makes it a useful check: the pattern is not unique to the 2020s.

The paper found that most investors lost substantial amounts on their options trades, much more than on stock trading. The authors attributed this mainly to poor market timing, driven by overreaction to past market returns, and to high trading costs. They concluded that gambling and entertainment were far more likely motives than hedging, and they found strong performance persistence: the investors who lost tended to keep losing. De Silva, Smith, and So summarise the Dutch investors’ average loss as 1.81% per month.

The mechanics behind the losses

The studies identify the same handful of forces. None requires anyone to be cheating; they are built into how options are priced and traded.

1. The spread is a large, invisible fee

Commission-free trading made options feel cheap to trade. It isn’t. If an option is quoted $0.937 bid and $1.063 ask, a 12.6% spread on a $1.00 midpoint, then buying at the ask and later selling at the bid costs $0.126 per share, or $12.60 per contract, on a $1.00 option, even if the stock and implied volatility haven’t changed. That is the full quoted spread, paid in two halves. Price improvement reduces it, which is why Bryzgalova and co-authors find an effective spread of 6.6%, but even that is a large hurdle compared with stocks, whose spreads are usually a small fraction of 1%.

Short-dated, low-priced options have the widest spreads in percentage terms, and they are exactly the contracts retail traders favour.

2. Time value always goes to zero

Every option buyer pays for time value, and every option’s time value is zero at expiry. The decay accelerates in the final weeks, as shown in theta and time decay. A buyer needs the stock to move far enough and fast enough to outrun it.

3. Implied volatility tends to be priced above realized volatility

On average, the options market charges a premium for bearing volatility risk. Academic work on index options, such as Carr and Wu’s “Variance Risk Premiums” (Review of Financial Studies, 2009), finds that implied variance on the S&P 500 has exceeded subsequently realized variance on average. The difference is compensation to option sellers for taking the risk of large losses in crashes.

A worked illustration: a 30-day at-the-money call on hypothetical Maple Widgets Inc. at $50, priced at 30% implied volatility and a 4% rate, costs about $1.80 under Black-Scholes. If the stock actually moves with 25% volatility, the same option is “worth” about $1.51: the buyer has overpaid by roughly 16% before any spread. This won’t happen on every trade. When realized volatility exceeds implied, buyers win. But a consistent average gap in sellers’ favour is what the research has found.

4. Lottery-like payoffs feel better than they are

Cheap out-of-the-money options offer the chance of a large percentage gain, and a preference for lottery-like payoffs among individual investors is well documented (for example, Alok Kumar’s “Who Gambles in the Stock Market?”, Journal of Finance, 2009). Consider a 7-day Maple Widgets call with a $52.50 strike (5% out of the money), priced at 30% implied volatility: about $0.13, or $13 per contract.

In a simulation where the stock moves exactly as the 30% implied volatility assumes, so the option is fairly priced and there is no hidden edge against the buyer:

The call expires worthless about 88% of the time.
It finishes worth more than its cost about 11% of the time.
Its average payoff roughly equals its price, so the expected profit is about zero.

Now add costs. Paying half of a 12.6% spread on the way in raises the cost to about $0.139. Holding to expiry, the expected result becomes a loss of about 6% of the amount paid. Add the volatility premium from point 3, and the expected result gets worse. Rare big wins can hide this for a long time, because most people remember their wins.

5. Behaviour and attention

De Silva and co-authors link retail options buying to media attention ahead of earnings. Bryzgalova and co-authors find retail options volume concentrated in attention-grabbing stocks and in the January 2021 meme-stock period. Bauer and co-authors find option traders reacting to past market returns and persisting in losing. Buying in bursts when a stock is in the news is often buying when options are most expensive.

Who is on the other side

When a retail trader buys an option, the seller is most often a market maker, sometimes another investor. Market makers hedge their exposure (see delta explained) and earn the spread plus, on average, the volatility premium. That is their business model, and it carries real risk: in a sudden crash, short-volatility positions can lose large sums quickly. The structure of who trades with whom is covered in how options markets work.

The research does not show that selling options is a reliable strategy either. Sellers’ profits come with exposure to rare, large losses, as described in options risks explained honestly.

The counter-evidence

The findings are not unanimous, and the strongest challenge is worth knowing. “New Evidence on the Performance of Customer Options Trades,” an April 2025 working paper by Diego Amaya, Pedro Garcia-Ares, Neil Pearson, and Aurelio Vasquez, was supported by a data research grant from Cboe’s Options Institute and used Cboe trade data that records which side initiated each trade. The authors argue that the Bryzgalova, Pavlova, and Sikorskaya estimates are sensitive to how trade direction is inferred and to measuring performance using quotes before expiration rather than values at expiration. Measured to expiration, they find that Cboe customer trades in the same price-improvement auctions were on average profitable in their January 2020 to June 2021 sample, although the average profits were not statistically significant. That period was a strong bull market, which favoured call buyers.

The same paper criticises a widely cited study of retail 0DTE trading for relying on a retail proxy that captures only 4% to 6% of S&P 500 index option trading. As of its April 2025 version it was a working paper, not a peer-reviewed article. Bryzgalova and co-authors themselves report that their results differ by horizon, with losses concentrated at short horizons and in short-dated contracts.

What the debate does not change: the spread, time decay, and volatility-premium mechanics described above apply to every option buyer regardless of how researchers classify trades.

What can go wrong when reading this research

Survivorship and selection. Studies average across all trades. Individual results vary hugely, and a few big wins can hide years of small losses.
Measurement choices. Bryzgalova and co-authors show that results depend on assumed holding periods and on leverage assumptions; their headline numbers use a 10-day holding period.
Different periods. The samples cover 2010-2021 (de Silva et al.), 2019-2021 (Bryzgalova et al.), and the 2000s (Bauer et al.). Market structure has changed since, including the rise of daily-expiring index options.
Retail identification is imperfect. Each study infers which trades are retail from data flags or trader classifications, and, as above, other researchers dispute some of those inferences.

Takeaway

Across different countries, periods, and data sources, peer-reviewed research finds that retail options traders lose money on average, with losses concentrated in buying short-dated options. The causes are structural: wide spreads, time decay, a volatility premium that favours sellers, and lottery-seeking behaviour around attention-grabbing events. Understanding those forces is more useful than any single trade idea, which is why this site does not offer any.