Most people who spend enough time in markets can point to one or two buys that haunt them. The position they exited far too early.The company that looked too messy to touch at the time and the chart that now reads like a slow-moving billboard saying "you were wrong." This is exactly why learning how to evaluate pre-IPO opportunities is so critical.These stories are usually told as if there were some mystical quality to the winners. A visionary founder here, a huge total addressable market there, some narrative about optionality and world-changing potential. Small caps, high growth, big dreams, hold forever. The folklore repeats with minor variations every missed opportunity. The IPO Genie team has dived deep into Anna Yartseva’s working paper The Alchemy of Multibagger Stocks to help you avoid such mistakes in the future.The paper, instead of retelling a handful of famous case studies, collects every United States-listed company that actually delivered a tenfold return between 2009 and 2024 and then asks a simple question: when you strip away the slogans, which measurable characteristics really distinguish these 10x outcomes from the rest of the market?The answer is not particularly mind-blowing, but it does an excellent job of informing a well-developed investing thesis. The factor “free cash flow divided by stock price” quietly sits at the center of it all.Size, value and profitability still matter, but in a far more specific configuration than most “growth at any price” stories suggest. Many of the variables that dominate investor conversations turn out to add almost nothing at the margin once you look across hundreds of winners and thousands of non-winners.The value of the paper is that it turns multibagger hunting from a campfire genre into something that can at least be discussed in a more disciplined way.The study in plain languageYartseva starts by defining her universe. She identifies 464 American listed companies that increased in value by at least ten times over their respective runs between 2009 and 2024. Each of these names is then embedded into a broader panel that covers the rest of the market across roughly two decades. For every firm and every year in the panel, she tracks a dense set of variables: a variety of valuation measures, profitability and quality metrics, capital allocation behavior, balance sheet indicators, technical patterns and a small set of macro conditions.The first step is to see whether the familiar five-factor model does anything useful inside this special group. Size, value, profitability and investment intensity are tested in the standard way. Unsurprisingly, the basic patterns that show up in the wider asset pricing literature do not vanish when you focus only on 10x winners. Smaller firms tend to outperform larger ones. Companies with higher book to market ratios tend to beat expensive glamour stocks. Firms with stronger operating profitability tend to deliver better future returns.The interesting part is the way these levers combine.Once you stop looking at simple averages and pay attention to medians inside portfolios, the raw “small-cap premium” weakens. Small on its own is not a superpower. What survives is a much sharper picture. Small plus cheap plus genuinely profitable works. Small plus cheap plus weak profitability does not. In other words the typical 10x outcome is not a random micro-cap lottery ticket. It is more often a smaller business that already has its economic engine in order and happens to be mispriced by the market.That already cuts against a lot of multibagger rhetoric. The companies that go on to deliver extreme long-term returns are not systematically those with the most aggressive top-line growth or the most dramatic stories. They cluster where size, value and profitability intersect in a specific way.From there, the paper becomes more aggressive. It expands the model to include more than one hundred fifty additional variables. That enlargement is not cosmetic. It is designed to let the data kill weak stories.
What 10x stocks are notA large part of the paper’s contribution sits in what fails to survive once all the candidate variables are thrown into the same framework.Earnings growth, which dominates so much investor marketing and fund reporting, does not show up as a robust predictor of which companies will go on to 10x. Whether you look at one-year changes or longer multi-year compound rates, historical earnings growth does not add much explanatory power once size, value and profitability are controlled for.Revenue growth behaves in a similar way. High historical sales growth might make for an exciting slide in a deck, but in this dataset it does not do the heavy lifting in distinguishing the extreme winners from the rest.Even free cash flow growth, which sounds intuitively closer to the mark, does not perform particularly well as a predictor on its own. The fact that a company is increasing cash flow is less important than the level of cash flow it generates relative to the price you pay today.Standard financial health indicators mostly fade into the background as well. Leverage ratios, current and quick ratios, off-the-shelf-composite scores and many of the red flag metrics that fill textbooks do not emerge as central drivers of 10x outcomes once the core factors are in place. They matter as hygiene, not as primary selectors.Capital allocation behavior, in the narrow sense, also disappoints. Dividend yields, share buybacks and patterns of new equity or debt issuance are widely debated in practitioner circles. In the models they play a supporting role at best. Once valuation and profitability are in the picture they add relatively little incremental information about who will deliver tenfold returns.Taken together, these results are uncomfortable because they poke directly at the dominant narratives in public markets. The paper does not claim that growth, balance sheet strength or capital allocation are irrelevant. It shows that as aggregate statistical signals they do not provide the edge that many investors assume when the real goal is to identify future 10x outcomes.Free cash flow yield at the center of the mapIf most of the usual checklists lose power when tested properly, something else has to drive the model.In Yartseva’s work, the simple free cash flow to price ratio takes that role. This is further referred to in the article as “free cash flow yield”. Expressed differently, the free cash flow yield becomes the single most powerful variable for distinguishing eventual 10x winners from the rest once other factors are accounted for.There is a straightforward economic intuition behind that result.Accounting earnings can be managed over surprisingly long periods. Revenue can be bought for a while through discounting, marketing spend or acquisitions. Even reported margins can be flattered over short horizons. Free cash flow is harder to fake consistently. It incorporates working capital needs, capital expenditure and the friction of actually running a business in the real world. When you divide that cash flow by the price you are being asked to pay for the equity you effectively ask how much economic oxygen you receive per dollar invested.The models in the paper show that, in this universe, high free cash flow yield goes hand in hand with a much greater probability of very strong future returns. That is true even after adjusting for traditional value ratios like book to market. In many specifications the coefficient on free cash flow yield dominates the rest.Two nuances matter here.The first is that free cash flow yield does not operate in isolation. It interacts with basic measures of quality and investment discipline. The paper tracks the relationship between asset growth and earnings before interest, tax, depreciation and amortisation. When a firm’s asset base grows faster than its EBITDA, subsequent returns tend to be much weaker. In other words, aggressive investment that is not backed by a corresponding expansion in economic earnings is a warning sign, not a badge of growth.The second nuance is the role of the balance sheet. Companies with negative equity, where total liabilities exceed total assets, perform very poorly on average even if they sometimes appear optically cheap on simple multiples. Cheapness driven by a broken capital structure rarely morphs into a 10x outcome in this sample. The interaction between free cash flow yield, quality and a roughly sound balance sheet seems to matter more than any single metric.Once you put these pieces together the profile of a typical 10x company in the data looks quite different from the popular image. It is not usually a chronically loss making story stock that eventually figures out how to print cash. It is more often a smaller firm that was already generating solid free cash flow relative to price, trading on modest value metrics, reinvesting in a way that its earnings power could sustain and ignored by the wider market at the outset.
Momentum, timing and the entry problemThe paper does not treat technical variables as an afterthought bolted on to a fundamentally driven model. They are pulled into the same structure and evaluated with the same discipline.Two patterns emerge.The first is that entry near recent highs is not characteristic of the 10x profile. Once you condition on fundamentals and valuation, stocks that sit at or near their twelve month highs at the point of purchase deliver weaker subsequent returns than those trading closer to the lower end of their one year range.The second is that the dynamics around those lows are not slow and gentle. Many 10x paths involve what the paper describes as complex momentum effects. Prices can fall sharply as sentiment sours, then reverse quickly once it becomes clear that free cash flow remains robust or that prior pessimism overshot reality. The attractive entry points are often located in periods where the chart looks uncomfortable and the news flow is unexciting or outright negative.For a discretionary investor this matches a familiar psychological pattern. The positions that later look most impressive in a track record often felt like awkward contrarian steps at the time. The numbers suggested that the business was fundamentally sound, cheap on free cash flow and not destroying its balance sheet. The chart and the prevailing narrative made the position hard to justify in social terms.The study’s forecast exercises, where models estimated on earlier years are tested on later out-of-sample periods, strengthen this point. They show that these combined patterns were not just artefacts of overfitting historical noise. The same configuration of fundamentals, valuation and technical context continued to tilt the odds in the right direction when exposed to fresh data.What this means for screening and portfolio constructionIt is tempting to treat a paper like this as a ready-made recipe. One could simply filter a universe for smaller companies with high free cash flow yields, attractive book to market ratios, reasonable returns on assets, asset growth that does not outrun EBITDA growth and no sign of negative equity. One could then require that prices sit closer to twelve month lows than highs and construct a diversified portfolio from the survivors.There is nothing inherently wrong with building such a screen. It will almost certainly improve on a purely narrative-driven approach. Several practitioners have already implemented similar rule sets for developed markets.The deeper value of the research sits elsewhere. For the IPO Genie team, it provides a set of disciplined priors that shape how we think about screening and portfolio construction on the platform.It reminds you that valuation never fully disappears as a driver of extreme outperformance. Even in a world saturated with stories about network effects and “winner takes most” dynamics, the companies that delivered 10x outcomes in this sample tended to be cheap on traditional value metrics at the point where their runs began, at least relative to their cash generation.It shifts the focus from headline growth rates to the economics of growth. The winners were not simply those with the fastest revenue or earnings trajectories. They were the firms that combined acceptable growth with high incremental returns on capital and with free cash flow that the market initially underappreciated.It reframes quality away from abstract composite scores toward concrete relationships in the accounts. Return on assets, the link between investment and operating earnings, and the absence of chronic balance sheet stress matter more than whether a company fits into a generic “high quality” bucket.It also forces you to confront your own discomfort around buying what currently looks bad. The mathematics of the paper pushes you into zones where price has already fallen, sentiment is fragile and the story is not fashionable, provided that the fundamentals line up in the way described.
Momentum, timing and the entry problemThe paper does not treat technical variables as an afterthought bolted on to a fundamentally driven model. They are pulled into the same structure and evaluated with the same discipline.Two patterns emerge.The first is that entry near recent highs is not characteristic of the 10x profile. Once you condition on fundamentals and valuation, stocks that sit at or near their twelve month highs at the point of purchase deliver weaker subsequent returns than those trading closer to the lower end of their one year range.The second is that the dynamics around those lows are not slow and gentle. Many 10x paths involve what the paper describes as complex momentum effects. Prices can fall sharply as sentiment sours, then reverse quickly once it becomes clear that free cash flow remains robust or that prior pessimism overshot reality. The attractive entry points are often located in periods where the chart looks uncomfortable and the news flow is unexciting or outright negative.For a discretionary investor this matches a familiar psychological pattern. The positions that later look most impressive in a track record often felt like awkward contrarian steps at the time. The numbers suggested that the business was fundamentally sound, cheap on free cash flow and not destroying its balance sheet. The chart and the prevailing narrative made the position hard to justify in social terms.The study’s forecast exercises, where models estimated on earlier years are tested on later out-of-sample periods, strengthen this point. They show that these combined patterns were not just artefacts of overfitting historical noise. The same configuration of fundamentals, valuation and technical context continued to tilt the odds in the right direction when exposed to fresh data.
What this means for screening and portfolio constructionIt is tempting to treat a paper like this as a ready-made recipe. One could simply filter a universe for smaller companies with high free cash flow yields, attractive book to market ratios, reasonable returns on assets, asset growth that does not outrun EBITDA growth and no sign of negative equity. One could then require that prices sit closer to twelve month lows than highs and construct a diversified portfolio from the survivors.There is nothing inherently wrong with building such a screen. It will almost certainly improve on a purely narrative-driven approach. Several practitioners have already implemented similar rule sets for developed markets.The deeper value of the research sits elsewhere. For the IPO Genie team, it provides a set of disciplined priors that shape how we think about screening and portfolio construction on the platform.It reminds you that valuation never fully disappears as a driver of extreme outperformance. Even in a world saturated with stories about network effects and “winner takes most” dynamics, the companies that delivered 10x outcomes in this sample tended to be cheap on traditional value metrics at the point where their runs began, at least relative to their cash generation.It shifts the focus from headline growth rates to the economics of growth. The winners were not simply those with the fastest revenue or earnings trajectories. They were the firms that combined acceptable growth with high incremental returns on capital and with free cash flow that the market initially underappreciated.It reframes quality away from abstract composite scores toward concrete relationships in the accounts. Return on assets, the link between investment and operating earnings, and the absence of chronic balance sheet stress matter more than whether a company fits into a generic “high quality” bucket.It also forces you to confront your own discomfort around buying what currently looks bad. The mathematics of the paper pushes you into zones where price has already fallen, sentiment is fragile and the story is not fashionable, provided that the fundamentals line up in the way described.
How to think about 10x hunting after reading this paperOne way to absorb The Alchemy of Multibagger Stocks is as an extended argument for putting free cash flow yield at the center of any serious multiyear equity process. Another way is to see it as a quiet audit of the things investors have been telling themselves for decades.The audit is not flattering.It questions the idea that you can reliably find 10x stocks by screening for the highest historical earnings or revenue growth. It shows that many finely sliced capital allocation narratives do not buy much marginal edge. It reduces a range of financial health metrics to what they truly are: necessary risk controls, not engines of outperformance.At the same time it upgrades a metric that is often treated as an afterthought. Free cash flow yield is not just one more line in a valuation table. In this work it is the central quantity around which the other useful signals orbit.It also offers a bridge between two often separate worlds. On one side sits factor investing, which usually talks in terms of broad cross sections, moderate edges and thousands of positions. On the other side sits the cult of multibaggers, which tends to rely on anecdote and hero worship. Yartseva's paper takes factor-style tools and applies them to the extreme right tail of outcomes. The result is one of the few pieces of research that both a systematic allocator and a bottom-up stock picker can read and recognise as relevant.For a discretionary investor who wants to keep a qualitative lens, the practical takeaway is straightforward. Use the paper as a filter on your own beliefs. When your process leans heavily on earnings growth charts, narrative excitement and very high recent price strength, recognise that you are operating outside the zone that this work identifies as fertile for 10x outcomes. When you come across a smaller company with strong free cash flow relative to price, acceptable profitability, disciplined investment and an unpopular chart, recognise that you are much closer to that zone.None of this guarantees that any single name will go on to 10x. Markets do not hand out certainty. What the paper does provide is a map of where past 10x results actually came from and which signals showed up again and again once the noise was stripped away.ClosingA single working paper cannot tell you which specific stock in your watchlist will compound at sixteen percent or more per year for the next decade and a half. That is beyond the reach of any model.What The Alchemy of Multibagger Stocks can do is narrow the search space and puncture several myths that keep investors looking in the wrong places. It shows that size matters, but only in concert with value and profitability. It shows that earnings growth on its own is a weak guide. It restores balance sheet strength to its proper role as a prerequisite rather than a source of alpha. Most of all, it moves free cash flow yield from the margins to the center of the story.In a field that constantly tries to seduce you with the next big narrative, there is something quietly radical about building a process around cash generation, sensible reinvestment and patient entry into temporarily unpopular names.Stories about the one that got away will always exist. They are part of how humans remember markets. This line of research suggests a different focus. Instead of trying to collect better stories, pay closer attention to the simple, stubborn signals that were present in the 10x outcomes we already have. Growth will always be exciting. Narratives will always be seductive. In the long run, only the cash that actually reaches shareholders and the price paid for the right to receive it have ever compounded capital.Even though this paper studied companies that managed a 10x+ over a period of 16 years, which is a century in Web3 terms, the same principles apply.These principles guide the IPO Genie team's dealflow and are being embedded into the platform, including the IPO Genie Vault where curated deals are managed with built-in risk protection, as we open IPO Genie to early backers through the IPO Genie presale.Source paper: https://www.open-access.bcu.ac.uk/16180/
Frequently Asked QuestionsQ: What is a 10x stock?A 10x stock is a company whose share price increases tenfold from its initial purchase price over time. These are also called "multibaggers," a term popularized by investor Peter Lynch. Achieving a 10x return typically requires holding through years of volatility and identifying companies before the broader market recognizes their value.Q: What traits do multibagger stocks share?Research on 464 US-listed 10x stocks found that the strongest common trait was a high free cash flow yield, meaning the company generated substantial cash relative to its stock price. Winners also tended to be smaller firms with solid profitability and disciplined investment, rather than the highest-growth or most hyped names.Q: Can retail investors realistically find 10x opportunities?Yes, but it requires discipline and patience. Building a diversified approach, as we describe in how to build a pre-IPO portfolio, is key. The research suggests focusing on companies with strong free cash flow relative to price, sound balance sheets, and modest valuations rather than chasing narrative-driven momentum. Screening for these fundamentals and buying during periods of market pessimism has historically tilted the odds in favor of finding outlier returns.
