10xResearch

Prediction markets are exploding into the mainstream, but most participants still treat them like entertainment, not like a system that quietly rewards the few who understand structural edge.
While retail chases long-shot narratives, disciplined traders harvest probability and time-decay, capturing outcomes that are not just likely, but mathematically inevitable. This report shows how those edges form.
Here, the winners aren’t the loudest traders with the boldest predictions, they’re the quiet ones who understand microstructure, flow imbalances, and volatility decay.
Part 1 (see previous post) showed that prediction markets have reached a structural turning point: liquidity is scaling, regulatory clarity has finally arrived, and retail participation is accelerating just as professional desks position themselves to harvest spread, flow imbalance, and information asymmetry.
It established the architecture, the liquidity map, the regulatory unlock, and the historical analogs that demonstrate a recurring truth: when new trading venues open, informed participants don’t chase narratives, they monetize those who do.
Part 2 (see previous post) stripped away the myth of collective wisdom. Prediction markets are not guided by “the crowd,” but by a tiny, informed minority who price probability, hedge exposure, and extract premium from retail-driven longshots.
Most users behave like sports bettors, trading narrative and novelty for discipline and expectancy, while a small cohort quietly profits from mispriced optimism and late-stage convergence dynamics.
Part 3 distills this into ten executable trading frameworks, presented as a set of golden rules, and details ten prediction market strategies ranked from low to high risk.
Part 4, publishing next, turns theory into execution: real contracts, real order flow, and exactly how we would position across Polymarket using the strategies introduced in Part 3.
See also previous report "The Polymarket Bitcoin Trade Paying 63% Annualized With Near-Certain Odds" (link in previous post).
Here is the link to part 3 of out 4 part series: https://update.10xresearch.com/p/prediction-markets-the-10-strategies-and-10-golden-rules-that-separate-arbitrage-from-entertainment
@Kalshi @Polymarket

Why this report matters
For some, prediction markets represent a gamified extension of financial trading; for others, they sit uncomfortably in a regulatory grey zone between wagering and market making.
Although operators consciously avoid being labeled as (sports) betting platforms, that category still drives the majority of volume, while niche markets, including Bitcoin and crypto outcomes, offer targeted opportunities.
These markets often pit casual retail participants against highly informed, data-driven traders, which can create extreme information asymmetry and meaningful arbitrage windows.
It is a valuable reminder that nearly every major crypto trading venue operated its own market-making or “treasury” desk, not just to provide liquidity, but to stand on the other side of retail flow, and rarely at a loss.
We have spent time dissecting this landscape, developing ten core rules for navigating it, and identifying trades that justify real capital deployment. Broader frameworks and structural insights will be shared in subsequent reports.
Main argument
I remember Arthur Hayes presenting to professional traders in 2015 in Hong Kong, highlighting the retail-driven inefficiencies his leveraged crypto exchange had unlocked.
Korean retail traders were paying implied funding rates near 200% to buy Bitcoin futures, and his crypto exchange, Bitmex, simply needed ‘professional’ flows to sell into that demand.
The edge wasn’t directional; it was structural: capture the spread without caring where Bitcoin traded.
A few years later, the same dynamic reappeared with the Grayscale GBTC trust, where retail buyers, largely accessing it through OTC brokerage platforms, pushed the product to premiums of 100%+ over NAV.
Institutions could subscribe to GBTC at par, hedge Bitcoin exposure immediately on day one, wait out the six-month unlock, and exit directly into retail excess.
But there are countless examples of professional crypto desks trading directly against retail flows, and whenever structural mispricings emerge, those who understand the mechanics capture them first.
With prediction markets poised to expand significantly in 2026, this felt like the right moment to take a closer look, before liquidity deepens and the easy edges disappear.
Please read below Part 1 of our three-part series: https://update.10xresearch.com/p/prediction-markets-the-next-structural-arbitrage-arena-bitcoin-traders-can-t-ignore-part-1-of-3

This was originally prepared as a Strategy report, but given its importance to active allocators, we are sharing it here.
Why this report matters
Crypto is crowded with misleading narratives and surface-level analysis that lack statistical rigor yet spread quickly whenever they hint at overnight riches.
Retail traders often get caught in this cycle, driven more by emotion than evidence.
But beneath the noise, the market can be assessed quantitatively; it just requires proper data access, disciplined modeling, and independent thinking rather than hype.
Conceptual frameworks such as stock-to-flow and global liquidity overlays became deeply fashionable.
Yet, none of them signaled selling anywhere near the last cycle peak—in fact, most doubled down as Bitcoin was already breaking lower.
Now, the same voices insist the four-year cycle has “evolved” into a five-year one, rather than acknowledging their models failed at the exact moment they were needed.
Below, we outline the only driver that truly explains the four-year rhythm, and examine whether it remains intact or has finally broken.
Main argument
In previous reports, we highlighted that the widely cited stock-to-flow model had already broken down during the last cycle (see the May 10, 2024, report).
Instead of the near-constant 10x appreciation it projected as supply declined, Bitcoin delivered diminishing cycle returns of 560x → 108x → 21x → 4x, roughly one-fifth of the prior cycle each time.
This framework is why a $70,000 peak for 2024 was a realistic expectation, a level that did, in fact, cap price action from March until early November 2024, just before the post-election breakout.
There is no mathematical law dictating that returns must compress by exactly one-fifth each cycle, but the stock-to-flow model clearly failed to serve as the infallible guide many believed it to be.
In this cycle, the popular “global liquidity drives Bitcoin” narrative only seemed convincing when the dataset was cut off at November 2023, and Bitcoin’s move was artificially lagged by 13 weeks.
That 13-week delay has no theoretical or mechanical basis, and it assumes liquidity flows into Bitcoin linearly, which isn’t how risk-asset transmission works.
If you want to understand what actually drives Bitcoin’s cycle, and why next year could trap most investors, you’ll need to keep reading.
Full report: https://update.10xresearch.com/p/the-bitcoin-cycle-didn-t-break-traders-just-forgot-what-drives-it

There are two dominant trading approaches: reversal trading and trend trading.
The most successful traders are not those who permanently stick to one, but those who know when to switch between the two, a skill that is far easier to describe than to execute.
When bullish or bearish trends reach capitulation levels, conditions often become ripe for reversal strategies.
If that reversal then gains momentum and starts attracting fundamental and narrative support, price action can evolve into a new trend.
This allows traders to transition from a short-term reversal position into a broader trend trade, having secured a strong entry and the ability to stay comfortably positioned as the trend develops.
Trading reversals does not necessarily mean going outright long or short. It can also involve fading extreme, fully-priced scenarios, for example, when implied volatility is highly elevated because many market participants have already bought crash protection.
This is precisely what we outlined in Monday’s Kickoff report (https://update.10xresearch.com/p/10x-weekly-crypto-kickoff-how-to-trade-this-btc-and-eth-reversal) and reflects the risk-reward profile of a post-correction normalization phase.
Bitcoin’s implied volatility for the November 28 expiry has now fallen below the levels seen when it made new all-time highs in early October.
After trading around 58% on Monday, implied volatility has since collapsed by roughly 20 points, with December expiries also down about 8 points.
As we highlighted, our reversal and sentiment indicators had reached extreme levels where prices have often staged rebounds, even when broader downtrends remain firmly in place.
Those trend regimes are tracked through our dedicated Trading Signals dashboard, which gives subscribers a clear, real-time view of prevailing bullish and bearish conditions.
Despite October’s reputation as Bitcoin’s strongest historical month, our models signaled that this cycle would be different when trend signals flipped bearish.
Our Ethereum trend model turned bearish on October 10, with ETH trading at $3,843, and our Bitcoin trend model followed a day later as BTC rolled over toward $110,808.
While we flashed this bullish reversal (https://youtu.be/i4og6b68a1E), the central question is now "fade the bounce or fade the downtrend"? -> https://update.10xresearch.com/p/bitcoin-fade-the-bounce-or-fade-the-downtrend