# Octagon

> AI-powered market intelligence platform that seamlessly integrates public and private market intelligence in a single API.

## Description

Octagon is a market intelligence platform for prediction markets, public equities, and private companies. Prediction markets are exchanges where traders buy and sell contracts on the outcomes of real-world events — elections, economic indicators, sports, and culture — so each contract's price reflects the crowd's implied probability of that outcome. Octagon's prediction-market coverage centers on Kalshi, pairing those live odds with research that weighs model-estimated probabilities against the market price. It publishes continuously updated market research, news analysis, answer-library explainers, and API documentation for human readers and AI agents.

Octagon provides real-time data on public equities, private market deals, company fundamentals, filings, investor networks, and prediction market research. This site features continuously updated research reports on Kalshi prediction markets with cited sources and probability analysis.

Key features:
- Research reports on Kalshi prediction market events
- Model probability vs market price comparisons
- Cited sources with automatic updates
- API and MCP access for programmatic use

## Attribution

- When quoting, summarizing, or reproducing Octagon content, attribute the material to Octagon.
- Link to the Octagon source URL for the specific page used as the source.
- Preserve nearby source links and cited references when they are available.
- If a specific page or report is used, cite that page rather than only the site homepage.

## Docs

- [Markets Index](/markets/): Browse all prediction market categories and reports
- [News](/news/): AI-assisted prediction market analysis reviewed by Octagon analysts, with cited sources, updated daily.
- [Answer Library](/answer-library): Curated answers on prediction market fundamentals and strategy
- [API Documentation](https://docs.octagonai.co/): Octagon API reference
- [MCP Server](https://docs.octagonai.co/guide/mcp-server.html): Model Context Protocol integration

## News

- [News Hub](/news/): AI-assisted prediction market analysis reviewed by Octagon analysts, with cited sources, updated daily.

## Categories

- [Climate and Weather](/markets/climate-and-weather/)
- [Commodities](/markets/commodities/)
- [Companies](/markets/companies/)
- [Crypto](/markets/crypto/)
- [Economics](/markets/economics/)
- [Elections](/markets/elections/)
- [Entertainment](/markets/entertainment/)
- [Exotics](/markets/exotics/)
- [Financials](/markets/financials/)
- [Mentions](/markets/mentions/)
- [Politics](/markets/politics/)
- [Science and Technology](/markets/science-and-technology/)
- [Sports](/markets/sports/)

## Reports

- [2026 World Soccer Cup Winner](/markets/sports/soccer/2026-world-soccer-cup-winner.md) (20.4%) | Volume: $516,214,951.4: Model estimates winner probability at 37.4% vs 20c (20.4%), implying 4.9x payout from strong France performance.
  - Q1: How does the performance and squad depth of host nation USA compare against that of a traditional contender like Portugal?
  - Q2: What performance metrics from the group stage support France's status as a leading contender for the 2026 World Cup title?
  - Q3: How might injuries or suspensions to key players on teams like the Netherlands or Belgium impact their odds heading into the knockout rounds?
  - Q4: How do the offensive strategies of Brazil and Argentina compare in the 2026 World Cup group stage?
  - Q5: What evidence from the tournament so far substantiates England's chances of overcoming its historical struggles in knockout play?
- [Finals Series Winner: New York vs San Antonio](/markets/sports/basketball/finals-series-winner-new-york-vs-san-antonio.md) (82.0%) | Volume: $301,884,252.15: Model's 83.8% probability implies a 1.2x payout multiple vs 82c market, as New York leads 3-1.
  - Q1: How could the remaining series schedule, including home-court advantage and travel, impact the performance of the Knicks and Spurs?
  - Q2: What key performance metrics from the first four games of the 2026 Finals justify the prediction markets' high confidence in a Knicks victory?
  - Q3: How do the Knicks' and Spurs' key players compare in head-to-head performance and statistical output through the first four games of the series?
  - Q4: How has the bench production and depth of the New York Knicks compared to the San Antonio Spurs throughout the 2026 NBA Finals?
  - Q5: What is the historical precedent for teams overcoming a 3-1 deficit in the NBA Finals, and what is the Spurs' path to achieving this?
- [2028 Democratic presidential nominee](/markets/elections/2028/2028-democratic-presidential-nominee.md) (1.0%) | Volume: $126,141,273.14: Model and market probabilities align at 1.0% (1c), indicating no implied probability gap.
  - Q1: How do Gavin Newsom and Kamala Harris compare on early fundraising and endorsements from key Democratic constituencies ahead of 2028?
  - Q2: What evidence from national polling and prediction markets supports the consensus view of Gavin Newsom as a top-tier candidate for 2028?
  - Q3: What are the key procedural milestones, such as primary calendar changes or debate rules, that could alter the 2028 Democratic nomination landscape?
  - Q4: What public polling data for the 2028 Democratic primary is available from major pollsters like Emerson College and YouGov as of late 2026?
  - Q5: What impact could the 2026 midterm election outcomes have on the presidential viability of governors like Gretchen Whitmer and Josh Shapiro?
- [U.S. Open Winner](/markets/sports/golf/u-s-open-winner.md) (3.3%) | Volume: $104,294,816.01: Model estimates 4.5% probability versus 3.3% market price, a +1.2 point gap, as dark horse contenders emerge.
  - Q1: What key performance metrics underpin Scottie Scheffler's status as the leading contender for the 2026 U.S. Open?
  - Q2: How do Wyndham Clark's power game and Akshay Bhatia's ball-striking skills translate to the specific challenges presented by Shinnecock Hills?
  - Q3: Which players outside the current top 20, such as past champion Bryson DeChambeau, have a viable path to contention based on 2026 qualification criteria and early-season performance?
  - Q4: What statistical profile of past winners at Shinnecock Hills provides the best predictor for success in the 2026 U.S. Open?
  - Q5: What outcomes in the 2026 Masters and PGA Championship could most significantly impact the odds for contenders like Xander Schauffele and Ludvig Åberg?
- [Stanley Cup® Winner: Vegas Golden Knights vs Carolina Hurricanes](/markets/sports/hockey/stanley-cup-winner-vegas-golden-knights-vs-carolina-hurricanes.md) (57.0%) | Volume: $59,135,853.15: Model's 61.6% for Vegas vs 57c (+4.6pp gap) offers 1.8x payout, citing strong special teams.
  - Q1: How do the special teams units of the Vegas Golden Knights and Carolina Hurricanes compare in the 2026 Stanley Cup Final?
  - Q2: What do advanced analytics from Games 1-4 reveal about which team, Vegas or Carolina, holds a sustainable performance edge?
  - Q3: What strategic adjustments might coaches Bruce Cassidy (Vegas) and Rod Brind'Amour (Carolina) make for the pivotal Game 5?
  - Q4: Which players, beyond team captains, are leading the Golden Knights and Hurricanes in key performance indicators through the first four games?
  - Q5: How does the goaltending matchup between Carolina's Brandon Bussi and the Vegas Golden Knights' starter compare based on series performance?
- [California Governor winner?](/markets/elections/us-elections/california-governor-winner.md) (89.0%) | Volume: $46,920,489.02: Model's 94.9% estimate exceeds the 89c market price for Becerra, suggesting a +5.9pp gap and 1.1x payout.
  - Q1: What do recent polling aggregates and voter registration data indicate about Xavier Becerra's lead over Steve Hilton for the November 2026 election?
  - Q2: How do Xavier Becerra's and Steve Hilton's stated policy positions on key California issues like housing, climate, and the economy differ?
  - Q3: How might the national political climate, such as federal policy debates or presidential approval ratings, influence voter turnout for Becerra versus Hilton?
  - Q4: Where can historical precinct-level voting data from the 2022 California gubernatorial election be found to model potential 2026 turnout scenarios?
  - Q5: What are the key dates for the gubernatorial debates between Xavier Becerra and Steve Hilton that could shift voter sentiment before November 2026?
- [RBC Canadian Open Winner](/markets/sports/golf/rbc-canadian-open-winner.md) (0.2%) | Volume: $42,118,685.34: Event concluded June 14, 2026, winner unstated; market's 0.2% price implies a 500x payout if correct.
  - Q1: How do top Canadian contenders Corey Conners and Taylor Pendrith compare in recent form and historical performance at the RBC Canadian Open?
  - Q2: What do the opening betting lines from major oddsmakers reveal about the consensus favorites for the 2026 RBC Canadian Open?
  - Q3: Which player skills are most rewarded by the TPC Toronto at Osprey Valley course layout, and how do contenders like Collin Morikawa and Matt Fitzpatrick align with these demands?
  - Q4: What historical player performance data is available for TPC Toronto at Osprey Valley from past professional tournaments that could inform 2026 predictions?
  - Q5: How do the 2026 season performances of international stars Brooks Koepka and Viktor Hovland compare on key metrics like Strokes Gained: Off-the-Tee and putting average?
- [2027 Pro Football Champion](/markets/sports/football/2027-pro-football-champion.md) (1.0%) | Volume: $37,806,848.73: The model estimates 0.9% probability for Denver, 0.1 points below the 1c market, lacking specific championship evidence.
  - Q1: What evidence from the 2026 offseason supports the Los Angeles Rams' position as the betting favorite for Super Bowl LXI?
  - Q2: How do the AFC's top contenders, the Buffalo Bills and Baltimore Ravens, compare on key offensive and defensive metrics from the 2025 season?
  - Q3: Which critical dates in the 2026-27 NFL calendar, from the trade deadline to the conference championships, are most likely to cause significant shifts in Super Bowl LXI odds?
  - Q4: What do historical betting odds from the 2023-2025 seasons indicate about how the Super Bowl futures market typically evolves from preseason to playoffs?
  - Q5: Beyond the top favorites, which dark horse teams like the Green Bay Packers or Detroit Lions show underlying statistical strengths suggesting potential Super Bowl LXI contender status?
- [Men's French Open Final: Zverev vs Cobolli](/markets/sports/tennis/men-s-french-open-final-zverev-vs-cobolli.md) (78.0%) | Volume: $33,900,520.71: Model's 78.5% for Zverev vs 78c market price shows a +0.5pp gap, despite his 0-3 Grand Slam final record.
  - Q1: How do Alexander Zverev and Flavio Cobolli compare on key performance metrics specifically on clay courts leading into the 2026 final?
  - Q2: What does analysis of Alexander Zverev's performance in his three previous Grand Slam finals reveal about his ability to close out a major title?
  - Q3: What are the most critical in-match scenarios or statistical thresholds that could act as catalysts for a momentum shift in the Zverev vs. Cobolli final?
  - Q4: What advanced analytics and predictive models, based on 2026 season data, are forecasting for the outcome of the French Open men's final?
  - Q5: Based on their most recent meeting at the 2026 Munich Open, what tactical adjustments might each player make for the best-of-five-set format at Roland Garros?
- [Series Winner: San Antonio (2) vs Oklahoma City (1)](/markets/sports/basketball/series-winner-san-antonio-2-vs-oklahoma-city-1.md) (78.0%) | Volume: $31,931,614.96: Model sees 80.6% for OKC (+2.6pp gap vs 78c market), with Thunder one win away from advancing.
  - Q1: What key performance indicators from the first five games demonstrate why the Oklahoma City Thunder hold a 3-2 series lead?
  - Q2: How does the home-court advantage at Frost Bank Center historically benefit the Spurs, and what does this imply for the must-win Game 6?
  - Q3: How have the coaching adjustments and rotational strategies of the Thunder and Spurs evolved over the first five games of the series?
  - Q4: How have the betting markets' series winner probabilities for the Thunder and Spurs shifted after each of the first five games?
  - Q5: If the series extends to a Game 7, what factors related to Oklahoma City's home-court advantage could prove decisive?
- [More tech layoffs in 20​26 than in 2025?](/markets/economics/more-tech-layoffs-in-20-26-than-in-2025.md) (89.5%) | Volume: $31,403,661.62: Model's 93.2% probability surpasses the 89.5% market price, suggesting an implied 1.1x payout due to AI-driven layoffs.
  - Q1: How does the volume of tech layoffs in H1 2026 compare to the volume in H1 2025?
  - Q2: What is the relationship between major AI investment announcements and subsequent layoff events at large tech firms in 2026?
  - Q3: How do the stated reasons and scale of 2026 layoffs differ between FAANG-level companies and VC-backed startups?
  - Q4: What are the key methodological differences and data discrepancies between major 2026 tech layoff trackers like Layoffs.fyi and Challenger, Gray & Christmas?
  - Q5: Which Q3 and Q4 2026 macroeconomic indicators, such as CPI or GDP growth, could signal a reversal of the current tech layoff trend?
- [Eastern Conference Champion](/markets/sports/basketball/eastern-conference-champion.md) (10.0%) | Volume: $30,319,144.03: At 10c, Detroit's 10.1% model probability suggests a 10.0x payout, reflecting its rare 3-2 comeback challenge.
  - Q1: How might the injury status of key players like Jalen Brunson or Donovan Mitchell affect their teams' chances for the remainder of the 2026 conference playoffs?
  - Q2: What statistical models and expert analyses support the New York Knicks' current status as the betting favorite to win the 2026 Eastern Conference?
  - Q3: How do the key playoff performance indicators for the Knicks, Cavaliers, and Pistons compare head-to-head in the 2026 postseason?
  - Q4: What does historical data show about the success rate of NBA teams, like the Detroit Pistons, when attempting to come back from a 3-2 series deficit?
  - Q5: What key factors in the upcoming Cavaliers vs. Pistons games will determine the final matchup against the New York Knicks?
- [Colombia vs Congo DR](/markets/sports/soccer/colombia-vs-congo-dr.md) (68.0%) | Volume: $29,687,460: Market at 68c for Colombia win prices above 66.4% model, despite reports of a 0-0 draw.
  - Q1: How does Colombia's attacking strategy under Néstor Lorenzo compare to DR Congo's defensive system led by Sébastien Desabre?
  - Q2: What on-field evidence from recent matches supports the case for a DR Congo upset or draw against the favored Colombian side?
  - Q3: What are the specific qualification scenarios for Colombia and DR Congo in Group K entering this final group stage match?
  - Q4: How have betting odds for the Colombia vs. DR Congo moneyline and total goals evolved since the markets opened?
  - Q5: How do key offensive players like Colombia's Luis Díaz and James Rodríguez match up against DR Congo's main scoring threat, Yoane Wissa, based on recent performance?
- [Will the U.S. confirm that aliens exist?](/markets/science-and-technology/space/will-the-u-s-confirm-that-aliens-exist.md) (1.0%) | Volume: $26,822,141.92: Model's 0.5% estimate is 0.5 points below market's 1.0%, reflecting consistent U.S. government denials of alien evidence.
  - Q1: What specific type of discovery from NASA or another scientific body would meet the threshold to trigger an official government confirmation before 2027?
  - Q2: Based on the Pentagon's AARO reports released through 2026, what are the primary prosaic explanations for the most-analyzed UAP incidents?
  - Q3: How do the evidentiary standards of scientific bodies, like Avi Loeb's Galileo Project, compare to the testimonial claims from intelligence sources like Luis Elizondo?
  - Q4: What is the publicly available timeline and scope for further UAP document declassification by U.S. agencies between now and the end of 2026?
  - Q5: What legislative actions or whistleblower testimonies scheduled before 2027 could compel the Pentagon to change its official stance on UAPs?
- [Ghana vs Panama](/markets/sports/soccer/ghana-vs-panama.md) (8.0%) | Volume: $26,569,625.74: Model's 9.2% vs 8c market, implying 12.5x payout; external markets projected Ghana's win probability at 45%.
  - Q1: How did Ghana's and Panama's offensive and defensive statistics compare throughout their respective 2026 World Cup qualifying campaigns?
  - Q2: What key player fitness concerns or late roster changes for either Ghana or Panama could have impacted betting odds before the June 17 match?
  - Q3: What performance data and recent form supported the pre-match prediction markets that slightly favored Panama over Ghana?
  - Q4: Given this was their first-ever meeting, what is Ghana's historical performance record against teams from the CONCACAF region?
  - Q5: How do the coaching styles of Ghana's Carlos Queiroz and Panama's Thomas Christiansen compare in major tournament settings?
- [Bitcoin price at the end of 2026](/markets/crypto/btc/bitcoin-price-at-the-end-of-2026.md) (2.6%) | Volume: $26,405,190.83: Model sees 3.0% probability vs 3c market price, implying a 38.5x payout multiple for a bearish outcome.
  - Q1: What are the year-end 2026 Bitcoin price targets from major financial institutions like Standard Chartered, Ark Invest, and JPMorgan, and what assumptions underpin their models?
  - Q2: What potential U.S. regulatory actions regarding digital assets from the SEC or Treasury could act as a major price catalyst for Bitcoin before the end of 2026?
  - Q3: How does Bitcoin's performance and volatility throughout 2026 compare to traditional safe-haven assets like gold, particularly in response to global inflation data?
  - Q4: Which data sources provide the most reliable tracking of institutional flows for spot Bitcoin ETFs, and what does their H2 2026 data reveal about demand trends?
  - Q5: How might the market's anticipation of the 2028 Bitcoin halving influence institutional accumulation strategies and price models during the second half of 2026?
- [Will the Citrini scenario happen?](/markets/economics/will-the-citrini-scenario-happen.md) (29.0%) | Volume: $25,827,898.4: Market at 29c exceeds the 18.9% model for an AI-driven crisis by 2028, implying overvaluation.
  - Q1: What evidence from mainstream 2026-2028 economic outlooks, such as Deloitte's, lends credibility to an AI-driven downturn?
  - Q2: What specific AI adoption milestones by Fortune 500 companies between 2026 and 2027 would serve as leading indicators for the Citrini scenario?
  - Q3: Which high-frequency data sources are available to track the Citrini scenario's specific triggers of unemployment, S&P 500 decline, and home values through 2028?
  - Q4: How does the Citrini model's causal mechanism for an economic collapse differ from the AI-related downside risks outlined in Deloitte's Q1 2026 forecast?
  - Q5: How might the Federal Reserve's monetary policy respond in 2026-2027 to early signs of mass white-collar unemployment as described by Citrini Research?
- [2028 Republican nominee for President?](/markets/elections/us-elections/2028-republican-nominee-for-president.md) (1.3%) | Volume: $25,693,763: Model's 1.6% probability is 0.3 pts higher than market's 1c, reflecting the early, unformed candidate field.
  - Q1: How Is JD Vance Building a 2028 Presidential Bid?
  - Q2: What Foreign Policy Narrative Dominates Conservative Media Shows?
  - Q3: Which Super PACs Show Early 2027 Financial Investment in Carve-Out States?
  - Q4: Do Governor Candidates Show Superior Grassroots Fundraising Efficiency?
  - Q5: What is Trump's 2028 Endorsement Strategy According to Surrogates?
- [When will traffic at the Strait of Hormuz return to normal?](/markets/politics/international/when-will-traffic-at-the-strait-of-hormuz-return-to-normal.md) (1.0%) | Volume: $19,854,047.04: Octagon's 0.5% model implies a 100x payout at 1c, contrasting the market's 1.0% amid ongoing high-risk, low-traffic conditions.
  - Q1: What specific military or diplomatic actions by the US or Iran could derail the June 2026 MOU and halt the recovery of Hormuz traffic?
  - Q2: How does real-time AIS shipping data for the second half of 2026 compare to projections from the Dallas Fed and IMO for a return to pre-war traffic levels?
  - Q3: How do alternative export routes, like the Saudi East-West Pipeline, compare to the Strait of Hormuz in terms of current oil-flow capacity, cost, and security?
  - Q4: Beyond suppressed AIS signals, what satellite imagery and maritime intelligence sources can track 'dark' commercial vessel traffic in the Strait of Hormuz?
  - Q5: What changes to the IMO's risk classification or maritime insurance premiums would trigger a full-scale return of commercial shipping lines to the Strait?
- [U.S. Open End of Round 1 Leader](/markets/sports/golf/u-s-open-end-of-round-1-leader.md) (8.9%) | Volume: $19,239,370.13: Ludvig Aberg's 15.2% model probability, as a leading FRL contender, implies an 11.2x payout versus 9c market price.
  - Q1: How Might the Shinnecock Hills Weather Forecast Create an Advantage for Morning vs. Afternoon Tee Times?
  - Q2: What Do Recent Betting Odds and Analyst Selections Indicate About the Consensus First-Round Leader at the 2026 U.S. Open?
  - Q3: How Do Jon Rahm and Ludvig Åberg Compare on Key Performance Metrics Suited for a U.S. Open Setup?
  - Q4: What Real-Time Data Sources Will Be Crucial for Tracking the Round 1 Leaderboard at the 2026 U.S. Open?
  - Q5: What Statistical Evidence Underpins Scottie Scheffler and Rory McIlroy as Favorites to Lead After Round 1?
- [All Reports](https://octagonai.co/markets.md)

## Answers

- [Are prediction markets accurate compared to polls or expert forecasts?](/answers/are-prediction-markets-accurate-compared-to-polls-or-expert-forecasts.md): Prediction markets are often as accurate as polls and expert forecasts, especially close to resolution. Their strength comes from incentives, real-time updates, and the ability to aggregate diverse information into a single probability.
- [Best Fintool Alternatives in 2026](/answers/best-fintool-alternatives-in-2026.md): The best Fintool alternative depends on which parts of Fintool you actually used, especially filings research, transcript analysis, metric extraction, and finance-oriented AI workflows.
- [Best Kalshi alternatives in 2026](/answers/best-kalshi-alternatives-in-2026.md): The best Kalshi alternatives in 2026 include Polymarket, Robinhood event contracts, PredictIt, and sports-focused apps for trading, plus research layers like Octagon that work across every venue.
- [Best prediction market tools in 2026](/answers/best-prediction-market-tools-in-2026.md): The best prediction market tools in 2026 fall into three layers: trading venues, data and intelligence platforms, and monitoring or alerting tools. The right pick depends on whether you want to trade, research, or automate.
- [Can I hedge real-world risk using prediction markets?](/answers/can-i-hedge-real-world-risk-using-prediction-markets.md): Yes—prediction markets can hedge exposure to discrete outcomes (policy changes, rate decisions, approvals, disruptions). The hedge works best when the contract outcome closely matches your real-world exposure and timing.
- [Can prediction markets be used to forecast geopolitical events?](/answers/can-prediction-markets-be-used-to-forecast-geopolitical-events.md): Yes—prediction markets are especially useful for geopolitical forecasting because they aggregate fragmented, asymmetric information that is difficult to model formally.
- [Can prediction markets help forecast IPO timing?](/answers/can-prediction-markets-help-forecast-ipo-timing.md): Prediction markets can sharpen IPO-timing forecasts by attaching live probabilities to "files by," "prices by," or "debuts before" questions, best used alongside an IPO tracker and filing flow.
- [Fintool vs Octagon: Which research workflow fits better?](/answers/fintool-vs-octagon-ai-which-research-workflow-fits-better.md): Fintool was built around filings, transcripts, and finance-focused AI research. This comparison shows how Octagon serves teams doing the same kind of public-company research.
- [How are contracts settled on Polymarket compared to Kalshi?](/answers/how-are-contracts-settled-on-polymarket-compared-to-kalshi.md): Kalshi contracts settle based on predefined, regulator-approved data sources, while Polymarket contracts rely on oracle mechanisms and platform-defined resolution processes.
- [How do analysts use prediction markets in company or sector research?](/answers/how-do-analysts-use-prediction-markets-in-company-or-sector-research.md): Analysts use prediction markets as a probability layer over fundamental research, weighting scenarios, timing catalysts, stress-testing theses, and surfacing sector read-throughs from a single event.
- [How do fees and platform rules affect prediction market prices?](/answers/how-do-fees-and-platform-rules-affect-prediction-market-prices.md): Fees and platform rules directly affect pricing by widening spreads, discouraging arbitrage, and biasing prices away from theoretical probabilities.
- [How do I calculate expected value (EV) for a trade in a prediction market?](/answers/how-do-i-calculate-expected-value-for-a-trade-in-a-prediction-market.md): EV compares what you expect to win on average vs what you pay. For a $1 "Yes" contract: EV = (your probability × $1) − price − fees.
- [How do I handle correlated markets and avoid double-counting the same thesis?](/answers/how-do-i-handle-correlated-markets-and-avoid-double-counting-the-same-thesis.md): Correlated markets move together because they share drivers (e.g., economic data affecting both rates and elections). If you hold multiple correlated positions, you may be taking much more risk than you realize.
- [How do I read a prediction market price as a probability?](/answers/how-do-i-read-a-prediction-market-price-as-a-probability.md): For a standard binary contract, the price roughly equals the implied probability.
- [How do investors use prediction markets for event-driven investing?](/answers/how-do-investors-use-prediction-markets-for-event-driven-investing.md): Event-driven investors use prediction markets to put live probabilities on catalysts like approvals, deals, and data releases, to time entries and exits, and to hedge discrete outcomes.
- [How do Polymarket and Kalshi differ in regulation and legal structure?](/answers/how-do-polymarket-and-kalshi-differ-in-regulation-and-legal-structure.md): Polymarket and Kalshi operate under fundamentally different legal structures. Polymarket is a crypto-based platform operating outside U.S. financial regulation, while Kalshi is a U.S.-regulated exchange overseen by the Commodity Futures Trading Commission (CFTC).
- [How do prediction markets differ from options markets?](/answers/how-do-prediction-markets-differ-from-options-markets.md): Prediction markets pay a fixed amount on a discrete yes or no outcome, while options derive value from an underlying asset's price and pay along a continuous range. The payoff shape is the core difference.
- [How do prediction markets react to Fed decisions, CPI, and jobs reports?](/answers/how-do-prediction-markets-react-to-fed-decisions-cpi-and-jobs-reports.md): Prediction markets reprice scheduled macro releases like FOMC decisions, CPI, and jobs reports in seconds, often before the cash and rates markets fully digest the print.
- [How do you build alerts for major probability changes?](/answers/how-do-you-build-alerts-for-major-probability-changes.md): Build probability alerts by defining a baseline, a trigger threshold, and a delivery channel, then filtering for liquidity and a catalyst so you are notified on real moves, not noise.
- [How do you monitor prediction market moves automatically?](/answers/how-do-you-monitor-prediction-market-moves-automatically.md): You monitor prediction markets automatically by pulling live probabilities through an API or MCP server, defining the contracts and thresholds you care about, and routing changes into a feed, dashboard, or agent.
- [How does settlement and resolution work, and why do rules matter more than headlines?](/answers/how-does-settlement-and-resolution-work-and-why-do-rules-matter-more-than-headlines.md): Prediction markets settle based on the contract's written resolution criteria, not what people "meant" or what headlines imply. A market can resolve against popular intuition if the rules are strict or the outcome is defined narrowly.
- [How should investors use prediction markets alongside traditional research?](/answers/how-should-investors-use-prediction-markets-alongside-traditional-research.md): Prediction markets work best as a complement to traditional research—providing probabilistic context, timing signals, and consensus checks rather than standalone answers.
- [How to Migrate from Fintool to Octagon](/answers/how-to-migrate-from-fintool-to-octagon-ai.md): A practical migration guide for former Fintool users who want to rebuild their finance and research workflow inside Octagon with minimal friction.
- [How to use prediction markets for earnings season research](/answers/how-to-use-prediction-markets-for-earnings-season-research.md): Prediction markets give earnings-season researchers a live, probability-weighted read on outcomes like beats, guidance cuts, and price reactions, complementing estimates and call transcripts.
- [What are the most common mistakes people make when using prediction markets?](/answers/what-are-the-most-common-mistakes-people-make-when-using-prediction-markets.md): The most common mistakes are overtrusting prices, ignoring liquidity and rules, and confusing probability with certainty.
- [What does a prediction market actually measure: belief, probability, or truth?](/answers/what-does-a-prediction-market-actually-measure-belief-probability-or-truth.md): Prediction markets measure tradeable belief, not objective truth. Prices reflect what participants are willing to risk capital on under current information and constraints.
- [What does market manipulation look like in prediction markets, and how can I spot it?](/answers/what-does-market-manipulation-look-like-in-prediction-markets-and-how-can-i-spot-it.md): Manipulation typically looks like pushing the price with aggressive trades to shape perception, then reversing later. You can often spot it through sudden price jumps without new info, thin order books, and quick mean reversion.
- [What happened to Fintool? Options for former users](/answers/what-happened-to-fintool-options-for-former-users.md): Fintool's homepage now states that Microsoft has acquired Fintool, which changes the product story from independent startup to acquisition and transition.
- [What is a prediction market, and how is it different from betting?](/answers/what-is-a-prediction-market.md): A prediction market is a marketplace where prices represent the crowd's implied probability of a future event.
- [What is arbitrage in prediction markets, and when is it actually possible?](/answers/what-is-arbitrage-in-prediction-markets-and-when-is-it-actually-possible.md): Arbitrage is a low-risk profit from inconsistent prices (e.g., "Yes" + "No" priced below $1 combined). In practice, true arbitrage is rare because fees, slippage, limits, and timing risk often eliminate it.
- [What is liquidity, and why does it matter so much in prediction markets?](/answers/what-is-liquidity-and-why-does-it-matter-so-much-in-prediction-markets.md): Liquidity determines how easily you can trade without moving the price. Low liquidity increases spreads, slippage, and exit risk.
- [What is the difference between prediction markets and futures markets?](/answers/what-is-the-difference-between-prediction-markets-and-futures-markets.md): Prediction markets settle on whether a discrete event happens, while futures settle on the future price or level of an asset or index. One prices an outcome, the other prices a value.
- [What makes a prediction market signal trustworthy versus noisy?](/answers/what-makes-a-prediction-market-signal-trustworthy-versus-noisy.md): A trustworthy prediction market signal usually has deep liquidity, clear resolution rules, and a move backed by real information. Noise comes from thin books, vague rules, and unexplained spikes.
- [What types of markets are listed on Polymarket versus Kalshi?](/answers/what-types-of-markets-are-listed-on-polymarket-versus-kalshi.md): Polymarket lists a wide range of global markets, including politics, geopolitics, and cultural events, while Kalshi focuses on regulated, event-based markets such as U.S. economic data, policy decisions, and legally permissible political outcomes.
- [What's the difference between Polymarket and Kalshi?](/answers/whats-the-difference-between-polymarket-and-kalshi.md): Polymarket and Kalshi are both prediction market platforms, but they differ fundamentally in regulation, user access, and market structure. Polymarket operates globally using crypto infrastructure, while Kalshi is a U.S.-regulated exchange designed to operate within traditional regulatory frameworks.
- [Who can legally use Polymarket and Kalshi by geography?](/answers/who-can-legally-use-polymarket-and-kalshi-by-geography.md): Kalshi is legally accessible to eligible users within the United States, while Polymarket primarily serves non-U.S. users due to regulatory restrictions affecting U.S. participation.
- [Why do prediction market probabilities change so quickly after news events?](/answers/why-do-prediction-market-probabilities-change-so-quickly-after-news-events.md): Prediction markets react quickly because they reprice probabilities, not narratives. A single credible data point can materially shift expected outcomes, causing sharp price moves even when headlines seem incremental.
- [Why do prediction markets sometimes disagree with financial markets?](/answers/why-do-prediction-markets-sometimes-disagree-with-financial-markets.md): Prediction markets and financial markets price different things: discrete outcomes versus continuous economic impact. Disagreement often reflects different assumptions, time horizons, or risk premia.
- [Why do prediction markets sometimes look wrong, even when they're popular?](/answers/why-do-prediction-markets-sometimes-look-wrong-even-when-theyre-popular.md): Markets can be "wrong" due to new information not yet absorbed, biased participation, or structural frictions like low liquidity and fees. The displayed price is a tradeable consensus—not a guarantee of accuracy.
- [Why do some prediction markets stay mispriced for long periods?](/answers/why-do-some-prediction-markets-stay-mispriced-for-long-periods.md): Mispricings persist due to low liquidity, unclear resolution rules, capital constraints, and lack of arbitrage incentives—especially in niche or long-dated markets.

## Optional

- [Octagon](https://octagonai.co/): Parent company providing market intelligence
- [Public Markets](https://octagonai.co/public-markets/): 8,000+ public equities coverage
- [LLMs Full Instructions](https://octagonai.co/llms-full.txt): Attribution and usage guidance for AI systems