The trillion-dollar prediction market: Why does everyone want to "trade everything"?
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The trillion-dollar prediction market: Why does everyone want to "trade everything"?
This is not an evolved version of Memecoin, but the next evolution of the stock market.
Navigating Web3 tides with focused insightsAuthor: eric
Translation: TechFlow
In prediction markets, I rarely hear people use the word "betting." Instead, they say "trading."
This distinction is crucial.
Once the stigma of gambling is removed, the total addressable market (TAM) expands to nearly everyone: macro investors, Pokémon card unpackers, your classmates and coworkers.
Light speculative behavior has already become mainstream across various groups. Office March Madness pools and fantasy leagues, gacha mechanics in video games, zero-commission day trading and 0DTE (zero days to expiration) options, crypto perpetual contracts, and meme coins. As long as it's called "trading" or "asset allocation" instead of "gambling," people flock to it rather than avoid it. @j0hnwang wrote an excellent piece on soft-gambling—though InfoFi wasn't explicitly mentioned, the connection is obvious. Prediction markets will soon be seen as non-taboo, just like stock markets. Combined with the potential to profit from culture (@dkposts gave a perfect example: https://x.com/dkposts/status/1961569826410823725), prediction markets will become a mass-market entry point.
Two Key Reasons Prediction Markets Are Detaching From Gambling
(1) No fear of the "house." Regardless of whether this is actually true, users feel they have an edge, so they view trading in prediction markets as an ordinary activity akin to portfolio management.
(2) Clear, understandable themes. Contracts settle based on observable data and real-world events: CPI on a certain date, ETF approval deadlines, election vote counts, launch windows, etc. You can profit by gathering information, simulating outcomes, and timing your moves. This application of intellect to risk significantly reduces the stigma of "gambling."
Additional Reasons to Be Bullish on Prediction Markets
(1) More Direct Event Pricing with Faster Feedback
In day trading, stocks (and commodities/forex) typically act as proxies for world events. For example, when war breaks out, Lockheed Martin and Brent crude oil prices rise; when key shipping routes are disrupted, Maersk's stock goes up; when the Fed unexpectedly hikes rates, the dollar strengthens and gold falls. Prediction markets, however, price events directly, resulting in clearer attribution and faster feedback.
(2) Prediction Markets Are Excellent Hedging Tools
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Consumer case: If you're planning an outdoor wedding and rain would require renting a $2,000 tent, you could buy a "Will it rain in City X on Date Y?" contract at $0.20 per share. If the outcome is "yes," the payout offsets most of the tent cost.
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Institutional case: A portfolio heavily weighted in growth tech stocks faces risks from unexpected inflation. They could buy a "U.S. CPI YoY ≥4.0% (September)" contract at $0.18 per share. If CPI hits ≥4.0%, the portfolio might drop ~3% (~$6 million). Each "yes" share nets $0.82, so buying ~7.3 million shares costs ~$1.3 million but yields ~$6 million if the event occurs; otherwise, the premium is the protection cost.
(3) Simple Market Mechanics with Low Financial Engineering Barriers
Prediction markets may be the most accessible form of cutting-edge financial engineering. Examples include:
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Commodity futures: "Will orange juice reach $X per gallon in June?"
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Credit default swaps: "Will Argentina default before 2026?"
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Interest rate swaps: "Will the average policy rate exceed 4.75% next year?"
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Volatility swaps: "Will S&P 500 volatility exceed 20% in March?"
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Traders see real-time probability changes—not cryptic sports betting odds (e.g., -140 to +50 or +500 to +200)—but simple percentages.
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Like stocks, traders can sell their positions before resolution, unlike traditional sports betting which only offers binary (0 or 100) outcomes.
(4) Strong Historical Performance in Predicting Major Events
Historically, prediction markets have been key players in forecasting major global events. For instance, during the 2024 U.S. election, Polymarket priced Trump’s win probability at 99% at 1:30 AM ET while Fox News didn’t call it until 1:47 AM, with other outlets lagging further. Continuous arbitrage and rising marginal costs of deviating from fair value make prediction market errors brief and self-correcting.
(5) Association With Intelligence and Skill Drives Adoption Among Elite Groups
Whether true or not, young people want to appear smarter or be perceived as such. For example, I've seen Harvard students mock DraftKings (seen as low impulse control) but proudly discuss prediction market arbitrage or correctly calling the outbreak of the Russia-Ukraine war. This association with skill and intellect drives adoption among highly educated university circles and investment professionals.
(6) Prediction Markets Will Gradually Replace Demand for Private Company Tokenization
Tokenizing private companies is difficult due to founder resistance, legal risks, illusory "governance" rights, and poor liquidity. Prediction markets can more easily fulfill similar needs.
(7) The Market Is Still Early
We’re absurdly early. Polymarket’s total value locked (TVL) is only $148 million (source: DeFiLlama), dwarfed by previously discussed TAM estimates or its ~$400 million peak TVL during the 2024 election. Kalshi only recently began diving deep into crypto.
Expected Trends Over the Next Six Months
In the next six months, I expect these trends:
(1) Prediction Market Data Becomes Standard in News Reporting
Market forecasts from Polymarket and Kalshi will regularly appear on screens across major news outlets. Every journalist making predictions will need to reference prediction market probabilities to maintain credibility.
(2) Regulatory Clarity = Viable Federal Framework Emerges
Polymarket’s confirmed U.S. market entry and Kalshi’s recent legal victory at the CFTC mean clearer paths for listing and clearing event contracts and attracting institutional capital.
(3) Influx of Professional Capital and Trading Teams
From the launch of an eight-figure (tens of millions USD) dedicated prediction market trading fund (to my knowledge, @curiouscamilo is preparing this) → to major trading firms (especially quant shops) establishing specialized prediction market desks (directional micro-teams, not just market-making, e.g., SIG’s services for Kalshi).
(4) Prediction Market Data Becomes Terminal-Grade Standard
Prediction market probabilities will appear on terminals like Bloomberg and Refinitiv alongside other price data—real-time quotes, historical records, alerts, charts, native API integrations with Excel/Python and CMS systems. Editors and trading teams will treat these probabilities just like any other data stream.
Most Likely-to-Succeed Prediction Market-Related Projects
Which prediction market-related projects are most likely to succeed?
(1) Reduce Choice Overload
The smartest move is using AI to automatically recommend three personalized markets daily. A general rule: AI that performs predictive functions autonomously (without user input, making decisions for users) tends to succeed more easily.
(2) Projects Focused on Social and Gamified Experiences
Prediction markets are inherently social, consumer-facing products. They must feature native gamified social graph elements: live streams, teams and leagues, copy trading, creator-led rooms, quarterly leaderboards, "club" wallet pools, market-linked chat, referral ladders, shareable trade slips that auto-rebuild upon click.
I particularly like "shareable trade slips"—a link that pre-fills specific bet details for others. You create a slip: select market, yes/no, amount, and conditions like "only bet if odds are below 65%." Click "share" to generate a link. When friends click, the app opens with everything filled in—they just review and confirm. Imagine:
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Like a Spotify playlist that loads the same songs when clicked.
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Like an Amazon cart where all items are already added when you send it to a friend.
(3) Infrastructure Projects: The "Picks and Shovels" of Prediction Markets
Leverage underlying prediction market architecture to deliver distribution, clean UX, and data processing power for mainstream demand. For example, Kalshi employee @kxchefsteve actively encourages developers to build wrapper tools ("ready-made control waiting to be used").
(4) Projects Solving Market Fragmentation
As @ryohhno pointed out, market fragmentation is structural: the same event exists across platforms without shared IDs, so liquidity and rules naturally split. The solution (though hard to implement) is building an NBBO (National Best Bid and Offer) and router for events—standardizing questions, routing orders to best price and depth, compensating for differing settlement terms and collateral currencies. Like a CUSIP-style event ID with depth-aware smart order routing, enabling identical trades to be rebuilt from any interface, including social networks.
(5) Infrastructure Projects Around "Multiverse Finance"
Earlier this year, @dave__white wrote a great piece on "Multiverse Finance." Assets exist in a universe where a condition holds; users can only borrow and trade within that universe; balances revert to the base world once oracles resolve. Related opportunities involve building universe-aware infrastructure:
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ERC-20 wrappers and credit tools that price split/pull operations
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A lending layer allowing 'notFiredUSD' to safely back 'notFiredETH', since both go to zero if the event resolves as "Fired."
Prediction Markets Have Greater Potential and Momentum Than Any Other Subsector
I feel prediction markets have stronger product-market fit and momentum than any other subsector. Just look at these headlines from recent weeks:
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"Robinhood partners with Kalshi to launch prediction markets."
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"CFTC drops appeal in Kalshi election contract case, paving way for regulated political markets."
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"Polymarket hits $1.16 billion in monthly volume."
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"Polymarket acquires CFTC-licensed QCEX for $112 million to re-enter U.S. market."
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"Donald Trump Jr. joins Polymarket as advisor, also advising Kalshi."
I disagree with the idea that prediction markets are the evolution of Memecoins. I believe they are the next evolution of stock markets. The potential here is limitless, and I am extremely confident in their future.
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@ericli1_
