Retail Didn’t Collapse — It Rotated

1Introduction

Between 2020 and 2021, millions opened a trading account for the first time. The phenomenon was global and massive: in the US, retail came to account for 25–30% of equity volume, Brazil sextupled its individual investors, and India added tens of millions of derivatives traders. Three years later the conversation flipped: headlines describe a “defeated” retail crowd retreating, chastened by losses. This paper starts from a simple suspicion —that this reading confuses a drop in relative participation with a disappearance— and tests it against the data.

The suspicion turns out to be well founded, but the full answer is richer than “it didn’t leave.” What the numbers show is that retail did three things at once: it corrected from an unrepeatable peak, it rotated toward other instruments and geographies, and —across much of the emerging world— it moved toward rails that do not even appear in the statistics of the major futures markets. Understanding that movement matters for a reason beyond the academic: where retail enters, and why it stays or leaves, determines who can build deeper capital markets, especially in the economies that most need them.

A framing note, because it sets the tone for all that follows: this is a neutral, public-interest analysis. It describes the phenomenon and its causes with primary sources; it sells no business thesis, is addressed to no company, and recommends no investment. Where the data suggests an opportunity or a risk, it merely shows it; the interpretation is left to the reader.

The contribution is threefold. First, we reframe the “fall” as a correction from an extraordinary peak followed by a rotation. Second, we map where retail moved —across instruments and geographies— with a focus on Latin America. Third, we show that much of that growth does not flow through listed futures markets but through other rails, and we analyze why. The roadmap: data and method (§2), the global correction (§3), instrument rotation (§4) and crypto (§5), geographic rotation (§6), segmentation and the gap with listed markets (§7), why retail picks those rails (§8), the minimums to trade (§9), a market-design discussion (§10), why almost no one wins (§11), and the scarring cycle that explains why they don’t return (§12).

2Data and method

This paper relies exclusively on public, verifiable primary sources. On the regulatory side, we use publications from SEBI (India), the CFTC and SEC (US), ESMA, the FCA and ASIC (Europe, UK, Australia), and reports from IOSCO and the BIS at the international level. On the market side, official statistics from CME Group, B3, A3/Matba Rofex and local exchanges, plus monetary data from the BCRA and the Banco Central do Brasil. On the academic side, peer-reviewed papers and working papers from NBER, SSRN and journals. And, where relevant, reports from listed brokers (for example, SEC filings) and data vendors such as Chainalysis, Vanda Research, and the JPMorgan Chase Institute.

The integrity rule is strict and worth stating up front: every third-party figure is cited with its source and date —a figure that belongs to others is never presented as our own—, and the “live” figures drawn from the platform accompanying this paper carry their lineage (origin, capture date, and method). When a value is unavailable, it is declared as such; it is not filled in with estimates disguised as official data. Where we estimate, we label it as an estimate.

A methodological caveat runs through the entire work and is worth pausing on, because much of the argument depends on it: “retail” is neither a single nor a well-measured category. At least four proxies coexist, each with its blind spot. In US futures, the standard is the CFTC COT “non-reportable” positions: an aggregated black box that does not distinguish account type and leaves out, for instance, prop-firm accounts trading in simulated environments. In equities, retail participation is estimated from order flow routed to wholesalers. In apps, one counts accounts or active users, metrics a single person can inflate across several platforms. And in crypto, one looks at wallets and on-chain volumes, which mix retail, treasuries, and bots.

The consequence is twofold. First, the claim that “retail is falling” or “retail is growing” is incomplete until one specifies which segment is measured and with which proxy: as we will see, measuring relative participation (the % share) versus absolute level (dollars or contracts) can yield opposite answers about the same market and the same period. Second, much of the public debate conflates these planes. We therefore carefully distinguish both dimensions throughout, and where a segment lacks clean data we triangulate across sources and say so explicitly rather than forcing a number. The analysis period is 2020–2026, with a geographic focus on Latin America —Argentina, Brazil, and Mexico as cases— and on the large mirror markets (the US and India).

It is worth stating why this window. The study period is 2020–2026 because it is the unit of time that contains the full phenomenon: 2020 marks the origin of the modern retail boom —pandemic, fiscal stimulus, zero rates, zero commissions, and trading apps—, and only by measuring from that peak do the subsequent correction and the rotation this paper documents make sense. Narrowing the window to the last two or three years would amputate the boom and, with it, the paper’s very premise. Within that period, the core evidence comes from Argentina and Brazil —with primary data from BYMA, A3 Mercados, B3, the central banks, and Chainalysis—, and the US and India act as mirrors. The foundational literature explaining why retail loses or distrusts —loss, trust, and financial-education studies predating 2020— is cited as a mechanism baseline, not as a series of the period, and is distinguished as such.

3The global boom and correction

The 2020–2021 boom was not spontaneous: it had an identifiable macroeconomic engine. The pandemic response combined massive fiscal stimulus with zero interest rates, and that mix met millions of people who were locked down, had free time, and —for the first time— had access to commission-free trading platforms. Greenwood, Laarits, and Wurgler quantify the fiscal channel with unusual precision: they estimate that roughly US$100 billion of US stimulus checks flowed straight into the stock market, and show that the price peaks of the era’s emblematic assets —GameStop, AMC— closely track the stimulus disbursements of April 2020 and January 2021.^[31]

That push was reinforced by structural accelerants that did not vanish with the pandemic: zero commissions (which became the industry standard in 2019), fractional shares, and instant mobile onboarding. Leverage came along: retail margin debt climbed roughly 60% after March 2020, stood around US$778 billion by year-end, and kept rising to an all-time high of about US$936 billion in October 2021. The result was an unprecedented expansion of the participant base, with a risk component that the very speed of the cycle would help expose later.^{[22, 8]}

The turn came with monetary policy. Between March 2022 and July 2023, the Federal Reserve raised its benchmark rate from ~0% to 5.25–5.50% in eleven moves. Free money ended, the cost of leverage rose, and risk appetite cooled. Retail’s relative share of US equity volume —which JPMorgan puts at around 20–25% on average, with episodic spikes to as high as 35% in moments of euphoria (2021 and, again, 2025)— compressed in 2022–2023. Seen only through that share, the story looks like a collapse: hence the “defeated retail” headline.

But a share is a fraction, and a fraction also falls when the denominator grows. Looking at the absolute level, the conclusion inverts: dollar flows did not collapse, they rebounded. The retail net purchases tracked by Vanda Research in the first half of 2025 even exceeded those of the same period in 2021, at the height of the meme frenzy; and total retail activity in stocks and ETFs reached US$5.4 trillion in 2025, a 47% year-over-year increase and the highest level on record. Retail did not leave the market: the market grew faster than it did, and the optics of the share disguised as a retreat what was, in fact, a normalization on a record base.^{[47, 45, 46]}

The takeaway is sober but consequential: there was a correction from an unrepeatable peak —the one produced by stimulus and zero rates—, not a death. What fell was the relative share; the absolute level is at record highs. Distinguishing these two planes is not a technicality: it is the difference between concluding that “retail left” and understanding that retail stayed, larger than ever in dollars, even as it was diluted within a market that grew even more.

That leaves the question that organizes the rest of the paper. If retail appetite did not disappear but merely changed shape, where did it move? The answer has two axes —instrument and geography— and is the heart of this paper.

4Instrument rotation

If speculative appetite did not disappear but changed shape, the first axis of that transformation is the instrument. The clearest case is same-day-expiry options —0DTE, for “zero days to expiry”—: contracts that are born and die within a single session. They went from 5% of S&P 500 options volume in 2016 to about 59% in 2025. The trigger was by design: when Cboe filled out weekly expirations in 2022 to cover every trading day, it effectively enabled a low-cost daily lottery, and retail —already about half of US options volume— adopted it en masse.^{[43, 35]}

The appeal is transparent: for a few dollars one buys a bet with enormous implicit leverage and an outcome within hours —the financial equivalent of a lottery ticket, plus the rush of intraday action—. It is no coincidence that the star instrument of 2021, single-name meme stocks (GameStop, AMC), gave way by 2023–2025 to ultra-short index options. It is the same impulse, channeled into a vehicle that is faster, cheaper to enter, and harder to win at consistently.

And 0DTE options are not alone. In parallel, other homes for retail speculation grew: crypto and its perpetual futures (§5), the “funded-account” prop firms that sell the dream of trading someone else’s capital (§8), and prediction markets —Kalshi, Polymarket, and even CME’s own Event Contracts— that turn any event into a one-dollar binary bet. The pattern, then, is not contraction but fragmentation: the same appetite spread across more vehicles, each with less entry friction than a traditional listed future. The largest of these vehicles deserves its own chapter.

5Crypto: substitute or complement?

No discussion of retail rotation is complete without crypto, because it is the vehicle that absorbed much of the past decade’s speculative appetite. Between 2020 and 2023, crypto and equities rode the same risk-on wave —stimulus, zero rates, apps— but as two distinct bets, with little population overlap. The 2022 “crypto winter” (the collapse of Terra/Luna and then FTX) hit crypto far harder than stocks, a sign they were not the same crowd. And the approval of spot Bitcoin ETFs in January 2024 institutionalized the asset: it drew fund capital, not necessarily new retail.^{[32, 21]}

Toward late 2024 the relationship flipped sign. JPMorgan documents that the retail-buying correlation between crypto and equities reversed: instead of buying both as risk assets, retail began treating them as substitutes, rotating from one to the other within the same app. But “substitute” does not mean identical. Kogan and coauthors, across 200,000 retail traders, show a revealing behavioral asymmetry: the same individual is contrarian in stocks (buys what falls) and momentum in crypto (buys what rises). They are two arenas with different mental models. The implication for our thesis is direct: if you count crypto, the “retail curve” does not contract —it changes asset—.^{[46, 32]}

In Latin America the logic is different again, and it is central to this paper. There crypto competes less with equities and more with the currency: it is money before it is a bet. In Argentina, 61.8% of crypto volume is stablecoins —a hedge against inflation and devaluation, not a speculative position—, well above the global average. In Brazil and Mexico the use is mixed: investment and speculation, but also remittances and payments (Bitso processed billions in the US–Mexico corridor). The regional pattern confirms the §2 caveat: much of what global statistics count as “crypto trading” is, in LatAm, hedging and utility. Regional retail did not leave risk; in many cases it was never speculating: it was defending itself from its own currency. Brazil confirms it from the top down: both its Central Bank and the Federal Revenue Service report that about 90% of the country’s crypto volume is stablecoins.^{[48, 49, 52, 10]}

6The geographic rotation

The second axis of rotation is geographic, and it is the one that matters most here. While participation normalizes in developed markets, in emerging ones it grows strongly. The World Federation of Exchanges sums it up with a line that doubles as a thesis: “in developed markets we sell securities to retail; in emerging markets we sell the market itself.” The difference is not of degree but of stage: where the US or Europe already have a mature retail base that expands and contracts with the cycle, emerging markets are still bringing their middle class into capital markets for the first time.^[24]

India is the sharpest mirror —and the world’s largest natural laboratory—. The explosion of individual derivatives traders was so large it forced the regulator to intervene; we return to their losses (§11), but as a participation phenomenon it is unparalleled. Brazil followed a similar trajectory at smaller scale: it sextupled its individual investors in B3 between 2018 and 2023 —from about 800,000 to over 5 million—, powered by the mini contracts (WIN, WDO) that cut the entry ticket to ~R$100. That growth plateaued after the pandemic boom —holding around 5.5 million individual equity investors by 2025—, a reminder that onboarding is not linear.^{[40, 13]}

Argentina adds an engine of its own: inflation. With the peso losing value chronically, investing stops being a luxury and becomes a defense; retail brokerage accounts at the Caja de Valores grew 87% in a single half of 2024, and by 2026 the country surpassed 24.6 million accounts —12.3 million investors, 55% of the economically active population—. Mexico, with a smaller base but aggressive fintechs (GBM+ multiplied its accounts twelvefold in three years), moves in the same direction. The common denominator is demographic and technological: young populations, high mobile penetration, and a layer of neobrokers and wallets that turned the phone into the market’s front door.^{[50, 12]}

But “retail grows in LatAm” hides a question almost no one asks, and it is the analytical heart of this paper: grows where? Because it is one thing for more people to invest, and quite another which market they end up trading in. The answer, as we will see, reframes the entire debate.

7Segmentation: the gap with listed markets

Here is the paper’s structural finding, and it starts with a deceptively simple question: who is “retail” for a big US futures exchange like CME or ICE? There is no single definition. These derivatives exchanges typically count as retail anyone trading through their partner brokers, with no capital threshold; the CFTC COT uses non-reportable positions as a proxy. But neither definition captures the bulk of the retail that is growing in Latin America, for a simple and under-discussed reason: that retail is not trading on CME or ICE —it trades on local exchanges, which are listed too.

The region’s retail growth lands on four rails, and CME/ICE listed futures capture only a fraction. The figure is telling: in the first quarter of 2026, CME’s LatAm-attributable volume hovered around 224,000 contracts per day, while B3 —Brazil alone— traded 13.2 million per day. That is a 58-to-1 ratio in favor of the local exchange. The region’s futures retail is not, for the most part, in Chicago: it is in São Paulo, in Buenos Aires, in a crypto app, or in a prop firm’s simulated environment.^{[39, 40]}

It is worth unpacking each rail. The first is the “funded-account” prop firms, huge in Argentina, Brazil, and Mexico. But the detail matters: in most firms, even the “funded” stage runs in a simulated environment —it sends no real orders to any exchange—; only a fraction, that of some futures props via Tradovate or Rithmic, routes real flow to the US futures exchanges (CME). For the trader the experience is identical; for those exchanges’ volume, the difference is between existing and not existing. Much of Latin America’s “funding boom” is, literally, invisible to CME and ICE.^[16]

The second and third are neobrokers and local exchanges. Nubank, Mercado Pago, Ualá, and GBM+ democratized access, but they offer local stocks, ETFs, fixed income, and crypto —not CME or ICE futures—; the few that do offer futures (IOL, Cocos in Argentina) route to A3, the local exchange. And where retail does trade futures, it does so at home: B3’s mini index requires ~R$100 of margin and is among the most-traded contracts on the planet, while A3 (formerly Matba Rofex) traded 293 million financial contracts in 2025 (+120% year-over-year), of which the dollar future was 98.7%. The fourth rail, crypto, we already covered: another entire lane that does not pass through CME or ICE.^{[40, 41, 11]}

None of this means the two big global futures venues —CME and ICE— ignore retail; on the contrary, CME courts it actively: Micro E-minis are already about 40% of its index volume, it added one-dollar Event Contracts, and it reports more than 500,000 global retail traders. The point is geographic: for both, Latin America is a marginal fraction of their international volume (~2% for CME). And a measurement problem compounds the diagnosis: the standard proxy —the COT’s non-reportable positions— is a black box that sees neither simulated props nor the retail trading on local exchanges or in crypto, so official statistics systematically under-represent where retail is growing. Put neutrally, as befits a work like this: Latin American retail growth is real, but it mostly lands outside listed futures. It is a measured observation, not a verdict; what to do with it —if anything— is left to the reader.^{[36, 39, 42]}

8Why retail picks those rails

With the map of where retail lands documented, the why remains: if regulated futures offer, in theory, better costs and more protection, why does retail pick the other rails? The answer has two layers —friction and behavior— and it is worth taking them separately. Friction first. Access to the various vehicles forms a brutally uneven ladder. Opening a crypto position takes minutes and a dollar; entering a prop firm, a US$100–500 fee and a form; a local neobroker account, a few taps in an app already used for payments. At the other end, accessing international listed futures from Latin America requires a foreign broker, US dollars —amid capital controls—, and weeks of onboarding with its tax complexity; even the cheaper local future can demand notarized paperwork and several weeks’ wait.

Table 1 lays out that ladder. The lesson is that friction is not an operational detail: more than cost or product quality, it is the variable that decides where retail enters. Between a regulated future that takes weeks and an app that settles in fifteen minutes, retail chooses the latter almost every time —even when the former would suit it better—.

The second layer is behavior, and here product design stops being neutral. Gamified platforms do not just lower friction: they exploit it. Robinhood users came to trade 9 to 40 times more than at a traditional broker per dollar invested, and IOSCO documents that “digital engagement practices” —notifications, confetti, streaks— increase trading frequency most among the financially less literate; the Massachusetts regulator went so far as to sanction those mechanics for inducing overtrading. On that terrain the usual biases operate: overconfidence (Barber and Odean), a preference for lottery-like bets (Kumar), and the present bias that privileges today’s thrill over tomorrow’s outcome.^{[29, 20, 18, 28, 30]}

A third factor is missing, tacit but decisive: the marketing asymmetry. Prop firms, CFDs, and crypto are promoted by an army of finfluencers paid an affiliate commission for every account they bring —a model that aligns their incentives with volume, not with the follower’s outcome—. Regulated futures, by contrast, are barely marketed to retail: no affiliate commission funds their reach. The result is a tilted playing field, where the riskiest vehicles are also the most advertised, and where the voice reaching retail usually carries a conflict of interest that is rarely disclosed. That asymmetry returns, in full force, in §12.^[19]

9The minimums to trade

The “minimum to trade” —how much capital it takes to get in— is the most concrete barrier of all, and in recent years it moved in two opposite directions at once. On one side, a wave of democratization lowered the floor. CME’s Micro E-minis (2019) cut the size —and margin— to a tenth of the standard contract; Mexico launched a Mini Dollar future ten times smaller in 2025; B3 sustains its minis with ~R$100 margins; zero commissions became standard in 2019; and, the most resonant change, FINRA scrapped the US$25,000 minimum required to day-trade, effective June 2026. The direction is unmistakable: making entry ever cheaper.^{[37, 38, 26, 7]}

On the other side, and sometimes in the same window, other regulators raised the floor to protect. The most drastic case is India: SEBI tripled the minimum F&O contract size in 2024 (from ₹5–10 lakh to ₹15–20 lakh), added upfront premiums, and cut weekly expiries; equity-derivatives volume fell from 16 billion to 4 billion contracts —about 75%— between October 2024 and March 2025, and the number of individual F&O traders dropped from 61.4 to 42.7 lakh. Earlier, ESMA (2018), the FCA (2019), and ASIC (2021) had capped CFD leverage, with a measurable effect at the other end: retail net losses fell by up to 94% in Australia after the cap.^{[2, 4, 5, 6]}

The tug-of-war is not a contradiction: it is the expression of a dilemma with no technical solution. Lowering the floor broadens access —and, with it, the exposure of inexperienced people to instruments the majority does not win at—. Raising it protects those who lose, but also shuts out those who might still learn. Each regulator picks a side according to what it fears more: financial exclusion or investor harm. That same dilemma —inclusion versus protection— reappears immediately in the design discussion that follows, and is, at bottom, the thread that ties this whole paper together.

10Discussion: should futures be fractionalized?

The previous section leaves a natural question, the one that most excites anyone who looks at the micros’ success: if shrinking the contract widened access so much, why not go on and allow trading 0.1 or even 0.01 of a contract, like the nano lot that already exists in forex? The answer, counterintuitively, is that the barrier is not regulatory: it is structural and economic. The CFTC does not prohibit a fractional contract; the machinery of listed futures simply does not admit one. In a centrally cleared market, the clearing house steps in as counterparty to both sides —“novation”— and the unit that clears, settles, and marks to market is the whole contract. There is no way to clear “0.1 of a contract”: the system is discrete by design.^[25]

Economics compounds this. Each contract pays a fixed exchange and clearing cost —on the order of cents on the dollar—; below a certain size, that fixed cost eats the tick value and the instrument stops being profitable for market makers. That is why forex fractionalizes and futures do not: retail forex is OTC —the broker is the counterparty and nets positions internally, with no clearing house—, and fractional shares work because a custodian splits one whole share among several owners, with no leverage and no novation. None of those tricks transfers to a leveraged, centrally cleared future: fungibility and the central guarantee, which are the system’s strength, are also what make it indivisible.^[17]

What the industry does, then, is not to fractionalize but to create new, smaller —yet whole— contracts. The progression is sharp: from the E-mini to the Micro (2019), from Micro Bitcoin to Coinbase’s Nano Bitcoin (0.01 BTC) —the smallest regulated future in existence today—, and even one-dollar Event Contracts. The real frontier of fractionalization is moving elsewhere: on-chain tokenization, where a derivative could be split into fractions outside traditional clearing. The CFTC already launched a tokenized-collateral pilot in 2025; it is the territory where the question might, someday, have a different answer —with its own, still-untested systemic risks—.^{[17, 53]}

But even if it were technically possible, the question of whether it is a good idea would remain —and there the underlying tension reappears—. More granularity lowers the barrier and widens access, yes; but it also accelerates retail’s exposure to leveraged instruments that, as we will see, the vast majority does not win at. This is not theory: it is exactly why India did the opposite and raised the minimum size. Fractionalizing futures is, then, neither a panacea nor an absurdity: it is a lever that moves the same old dial —inclusion on one side, protection on the other— and whose desirability depends on which of the two one weighs more. This work does not settle that choice; it lays it out with the mechanics and the evidence in plain view.^[2]

11Why almost no one wins

Beneath all the rotation lies an uncomfortable, well-documented fact: the vast majority of retail loses money. In India, 93% of individual F&O traders lost (FY22–24); in Brazil, 97% of persistent day traders; in European CFDs, between 74% and 89% of accounts. Barber and Odean showed it back in 2000: the more retail trades, the worse it does.^{[1, 3, 33, 4, 27]}

And this is neither old news nor foreign to our period: an FGV study of the pandemic era found that nearly 968,000 Brazilians collectively lost R$9.9 billion day-trading between 2020 and 2023 —96.4% of days closed in the red for individuals—, and a 2025 survey found that 72% of retail day traders lost again. The loss is not the artifact of an old study: it is a pattern that recurs within this paper’s very window.^{[15, 14, 33]}

The reasons for the losses are well known: transaction costs that erode any edge, overtrading fueled by overconfidence, a preference for lottery-like bets, and a structural disadvantage against faster, better-informed institutional players. But how much retail loses does not, by itself, explain what matters most for this paper’s thesis: why participation does not recover. For that we must look at what happens after the loss —and that is where the most underrated mechanism in this whole story appears.^{[30, 28]}

12The scarring cycle: why they don’t come back

If losing money were an isolated event, it would matter little: people would dust themselves off and try again, more cautious. The problem is that it is not so. Behavioral economics documented long ago that bad market experiences leave a scar that lasts years, sometimes decades. Malmendier and Nagel, in a now-classic study, show that those who lived through low returns over their lifetime take less financial risk, participate less in the stock market —a gap of up to twelve percentage points across cohorts— and are more pessimistic about the future, and that the effect persists long after the event that caused it. The first experience weighs disproportionately: whoever starts out losing, starts out scarred.^{[54, 59]}

The scar is not only risk aversion: it is distrust. And trust is, literally, a prerequisite for participating in a market. Guiso, Sapienza, and Zingales show that trusting the market more raises the probability of investing in stocks by about 6.5 percentage points —an effect so large it explains why even wealthy people stay out—. Distrust operates through two channels: an objective one (the quality of the legal and anti-fraud framework) and a subjective one (the belief that one will be cheated). When that belief spreads, stigma appears: “trading is a rigged game, a scam.” And stigma does not distinguish between the person who lost by trading badly and the one who was actually defrauded.^{[55, 57]}

This is where the damage from scams and fake gurus comes in, which is greater than it looks because it carries an externality. Each fraud does not just empty its victim’s account: it poisons the well for everyone. The evidence is stark. The FTC reported US$5.7 billion in investment-fraud losses in a single year, the largest fraud category. FINRA found that between 68% and 69% of finfluencer-followers who were targeted by a scam lost money —far more than those who don’t follow them—. IOSCO estimates that about 70% of finfluencers breach some substantive rule. And the Madoff case revealed the aggregate mechanism: after the fraud, hundreds of billions of dollars were withdrawn even from uninvolved advisers, and firms in the affected areas closed far above average. Fraud does not subtract a client: it drives away a generation.^{[61, 60, 51, 34, 19, 65, 66]}

The intuitive reaction is “we must educate people.” But the evidence is uncomfortable: financial education, as it has been done, changes behavior less than believed. The meta-analysis by Fernandes, Lynch, and Netemeyer —across 201 studies— finds that educational interventions explain barely 0.1% of the variance in financial behavior, and that the effect fades within months. It is the central paradox of our time: there has never been so much financial “content” —courses, videos, finfluencers— and yet outcomes do not improve. The reading is not that education is useless, but that quantity is not quality: early, independent, conflict-free education matters more than the volume of affiliate-monetized tutorials. In Latin America the problem is twofold: financial-literacy scores sit below the OECD average, and public programs exist but with no known impact evaluation.^{[56, 58, 64]}

The cycle, then, closes like this: retail enters optimistic → loses (74–97% do) → grows disillusioned and, often, is defrauded → loses trust in the market as an institution → leaves → and does not return, because the scar and the distrust persist. The attrition data back this up: Robinhood’s monthly active users fell from 21.3 million (mid-2021) to 10.3 million (2023) —half did not return—, India’s active F&O traders dropped by about 26%, and in Brazil account openings plateaued after the boom. The cost is not only individual: it is forgone participation in capital markets and destroyed financial human capital —especially severe in emerging economies, which most need to deepen their markets and can least afford a generation that turns its back on formal saving and investing—.^{[62, 63, 40]}

Limitations

This work inherits its sources’ limits. No public dataset links the same person trading stocks, crypto, and futures, so evidence of substitution vs. addition is indirect. LatAm regulators publish little retail disaggregation. Prop firms do not disclose what share of their funded accounts route real orders. And no US regulator publishes the number of retail accounts: where we estimate, we label it as an estimate.

13Conclusion

The thesis we opened with —that retail “died”— does not survive the data. What happened between 2021 and 2025 was a correction from an unrepeatable peak, followed by a rotation. Relative participation compressed —JPMorgan puts it around 20–25%, with spikes as high as 35%—, but the absolute level returned to record highs: US$5.4 trillion of retail activity in 2025. Mistaking the drop in share for the disappearance of the phenomenon is the reading error this paper set out to correct.^{[47, 46]}

The rotation was twofold. Across instruments: speculative appetite migrated from meme stocks toward 0DTE options —from 5% to 59% of SPX volume—, crypto, prop firms, and prediction markets; it did not switch off, it fragmented. And across geographies: as developed markets plateau, emerging ones grow. On that second rotation rests the paper’s structural finding: in Latin America, retail futures growth mostly lands outside CME/ICE listed markets —captured by local exchanges (B3 trades ~58× CME’s regional volume), crypto, and apps—. Regional retail is not absent from the futures market; it is in a different futures market.^{[43, 39, 40]}

Beneath the rotation lies a fact no growth narrative should ignore: between 74% and 97% of retail loses money, depending on market and product. And that loss is not neutral. The behavioral evidence suggests that those who get burned do not simply leave: they distrust, and distrust is sticky. A bad experience depresses risk appetite for years; fake-guru fraud harms not only its victim but stigmatizes the whole activity —“trading is a scam”— and drives away people who never return. The result is forgone participation and opportunity that does not show up in volume statistics, but is real.^{[1, 33, 4, 27]}

The Latin American case arranges these pieces with a logic of its own. Where there is inflation and capital controls, crypto competes not with equities but with the currency: a hedge before a bet. Where friction to the global market is high —US dollars, international brokers, weeks or months of paperwork—, retail takes the path of least resistance: the local app, the stablecoin, the funded account. And where quality financial education is scarce, the void is filled by an army of affiliate-incentivized finfluencers. Each of these conditions pushes retail toward rails other than listed futures, and explains why the regional growth map looks the way it does.^{[48, 23, 19]}

There remains, finally, a dilemma that is not technical but political. Lowering the barrier —micros, scrapped minimums, fractional contracts— broadens access; raising it —as India did— protects those who lose. Both paths have costs. The way out is not to pick an extreme, but to build the infrastructure the debate usually skips: quality financial education (not more content, but better), rules that pursue fraud before it erodes trust, and products designed so retail can participate without being wiped out. The market does not grow for whoever has the biggest budget, but for whoever meets retail where it already is —and treats it as a participant to protect, not a flow to extract—. This document does not close that debate; it opens it with the data in plain view, and will keep updating as the data changes.^{[7, 2, 24]}

References

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Appendix A · Retail voices

Appendix B · Notes

Glossary

0DTE

An option that expires the same day it is traded.

PFOF

Payment for Order Flow: what a market maker pays a broker for its orders.

PDT

Pattern Day Trader: US rule that required US$25,000 to day-trade.

Non-reportable

Positions below the COT threshold; a retail proxy.

ADV

Average Daily Volume of contracts.

Novation

The clearing house steps in as counterparty to both sides.

Data availability

All cited sources are public and linked in the references; every third-party figure carries its source and date. The paper’s figures use values fixed as of each version (reproducible), not live feeds. The qualitative sentiment evidence is the “Retail Voices” corpus (Appendix A), frozen and verified; the platform’s live social engine is a separate exploratory tool, not part of the cited evidence.

Version history