Catalyst · Live intelligence
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Real-time geopolitical event analysis with AI predictions across 38 global assets — crypto, stocks, commodities, and forex. Refreshed every 5 minutes.
Real-time geopolitical event analysis with AI predictions across 38 global assets — crypto, stocks, commodities, and forex. Refreshed every 5 minutes.
We trace every move back to the events driving it — wars, sanctions, supply shocks, central-bank decisions — with mechanisms and confidence scores. Rebuilt every two minutes.
Catalyst is a real-time AI market intelligence engine that traces every move in stocks, crypto, gold, oil, and forex back to the geopolitical events driving it — with directional calls, impact ranges, and confidence levels.
In 2026, AI stock predictions have moved beyond pattern-matching on price history. Catalyst tracks 28 assets in real time — including Bitcoin, NVDA, gold, and oil — and publishes a directional call, an estimated impact range, and a confidence level every five minutes during market hours.
The pipeline ingests live geopolitical events from USGS, NASA FIRMS, ACLED, and GDELT, joined to price feeds from CoinGecko and Twelve Data. An AI reasoning engine evaluates each event against historical precedents to produce a falsifiable prediction — not a vague forecast. Every prediction becomes a permanent timestamped report on the Catalyst track record page.
Unlike technical AI tools that fit curves to past prices, Catalyst answers a different question: which real-world event is moving this asset, and by how much? When Russia invaded Ukraine in February 2022, technical analysis could not predict the 30% oil spike or the 8% gold rally — but the geopolitical transmission mechanism made those moves predictable. Catalyst applies that framework automatically, across all tracked assets, around the clock.
Every market move has a cause — usually three or four overlapping ones. Catalyst surfaces them in ranked order: a stronger-than-expected jobs report can push out Fed rate-cut expectations, lifting Treasury yields and triggering a risk-off selloff in stocks; a Middle East escalation can simultaneously bid up gold and oil while pressuring equity indices through higher input costs.
Instead of guessing, see the live breakdown for each asset class. Each explainer below is rebuilt every 2 minutes from live event data and published with confidence scores, mechanism descriptions, and direct links to the underlying news sources:
For every geopolitical event, Catalyst traces a clear causal chain: Event → Market Mechanism → Specific Asset Impact. When new tariffs are announced on semiconductor imports, the system identifies the direct revenue impact on affected companies, the second-order effects on supply chain partners, and the broader market sentiment shift that reprices related indices and currencies.
Each prediction is calibrated against historical precedents. If the current event resembles the 2018 US–China trade war, the system references the actual market moves from that period as calibration points and scales estimates based on relative severity and scope. Confidence levels are assigned honestly: HIGH for direct first-order impacts (oil up on supply disruption), MEDIUM for second-order correlations, LOW for speculative third-order effects. This honesty is the point — most AI stock predictors hide their misses; Catalyst publishes them.
Crypto markets are uniquely sensitive to live event flow. Regulatory announcements, ETF approvals, exchange incidents, and macro liquidity shifts move Bitcoin, Ethereum, and Solana in minutes — long before traditional analysts publish takes. Catalyst tracks 10 cryptocurrencies including BTC, ETH, SOL, XRP, ADA, AVAX, LINK, MATIC, BNB, and DOGE, with predictions refreshed every 5 minutes.
Unlike sentiment-only crypto prediction tools that look at social-media volume, Catalyst grounds its calls in identifiable events with verifiable source chains — the same methodology applied to traditional markets. See live crypto predictions on the tracked assets hub or browse individual asset pages for full prediction history.
Bloomberg Terminal costs around $24,000 per year and is designed for institutional traders who need everything in one place — chat network, full data suite, execution tools, news wire. Catalyst is not trying to replace all of that. It targets the single capability most retail traders and analysts actually use Bloomberg for: monitoring how live events move prices.
| Capability | Bloomberg Terminal | Catalyst |
|---|---|---|
| Live geopolitical event feed | ✓ Premium news | ✓ USGS, ACLED, GDELT, NASA |
| AI market impact predictions | Add-on (BBG GPT) | ✓ Built in, every 5 min |
| Causal-chain explainers | — | ✓ Event → Mechanism → Asset |
| Public, auditable track record | — | ✓ Every prediction timestamped |
| Order execution + chat network | ✓ | — |
| Annual cost | ~$24,000 | Free |
If you need the full Bloomberg suite, Bloomberg is irreplaceable. If you want institutional-grade event monitoring with AI market predictions for $0, that's the slice of the market Catalyst is built for.
Active crypto and forex traders use Catalyst predictions to anticipate market-moving events before they are fully priced in. Financial analysts and risk managers rely on systematic monitoring of geopolitical risk with quantified market correlations. Journalists and researchers use real-time event tracking with verified source chains for situational awareness. Catalyst is free for all of them.
AI-powered predictions for crypto, stocks, indices, commodities, and forex — updated every 5 minutes with multi-timeframe analysis.
Catalyst provides predictions across three timeframes for each tracked asset. Short-term analysis (24-48 hours) captures immediate event-driven price reactions — the kind of moves that happen when sanctions are announced, a supply disruption occurs, or a major geopolitical development breaks. Medium-term analysis (1-2 weeks) tracks how initial shocks propagate through supply chains, policy responses, and market repositioning. Long-term analysis (1-3 months) assesses structural shifts in market dynamics.
Each timeframe uses different weighting for event severity, historical precedent, and market structure. A trade war escalation might have a moderate short-term impact but a significant long-term structural effect on affected supply chains. Conversely, a natural disaster may cause an immediate price spike that mean-reverts within weeks as supply chains adapt.
Every Catalyst prediction is published as a timestamped report with a specific directional call, estimated impact range, and timeframe. This creates a fully auditable track record — unlike institutional intelligence platforms that rarely publish specific, falsifiable predictions.
Review our historical prediction accuracy on the Catalyst track record page, where you can see how past predictions performed against actual market outcomes. View all published reports on the tracked assets hub.
AI cannot predict stock prices with certainty, but it can forecast directional probabilities by tracing the causal chain from a real-world event to a specific asset. Catalyst’s approach is fundamental, not technical: when an event happens (sanctions, supply disruption, central bank decision, conflict escalation), the system identifies the transmission mechanism (commodity flow, rate expectations, safe-haven demand) and publishes a directional call with a numeric impact range and confidence level. Accuracy is highest for first-order impacts (oil spiking on supply shocks) and lower for speculative third-order effects.
The stock market moves on a mix of macro data (jobs, inflation, Fed expectations), corporate earnings, and geopolitical events. Catalyst breaks every market move into the specific events driving it. See the live causal-chain explainers under “Why is X moving?” for stocks, gold, oil, and crypto — each shows the ranked drivers of today’s move with confidence scores.
No single AI stock predictor is universally accurate — accuracy depends on asset class, time horizon, and event type. Catalyst publishes every prediction as a timestamped report, giving you an auditable track record across 28 assets. Compare actual outcomes against predictions on the Catalyst track record page; this transparency separates accountable AI prediction tools from black-box services that only highlight winners.
Yes. Bloomberg Terminal costs around $24,000 per year and is built for institutional traders. Catalyst delivers a focused subset of that capability — live geopolitical event monitoring with AI market impact predictions across 28 assets — entirely free. You won’t get Bloomberg’s full data suite, chat network, or execution tools, but for monitoring how events drive prices in real time, Catalyst is comparable institutional-quality intelligence at zero cost.
Catalyst predictions are updated every 5 minutes. The aggregation pipeline runs every 15 minutes to collect new event data and price feeds, while the AI reasoning engine processes and publishes new reports every 5 minutes during active market hours.
Catalyst tracks 28 assets across 5 asset classes: 10 cryptocurrencies (BTC, ETH, SOL, XRP, ADA, AVAX, LINK, MATIC, BNB, DOGE), 8 stocks (NVDA, AAPL, MSFT, TSLA, GOOGL, AMZN, META, TSM), 3 indices (S&P 500, Dow Jones, Nasdaq 100), 3 commodities (Gold, Silver, Oil), and 4 forex pairs (EUR/USD, USD Index, USD/JPY, USD/CNY).
Technical analysis tools rely on price history, chart patterns, and indicators. Catalyst focuses on fundamental event-driven analysis — tracking how real-world geopolitical events (wars, sanctions, trade policies, natural disasters) affect market prices through identifiable causal chains. Both approaches complement each other.
Catalyst ingests data from USGS (earthquakes), NASA FIRMS (wildfires), ACLED (conflicts), GDELT (global events), CoinGecko (crypto prices), and Twelve Data (stocks, forex, commodities). Event data is classified by AI and cross-referenced against multiple sources before being used in predictions.
No. Catalyst predictions are AI-generated analysis for informational purposes only and do not constitute financial advice, investment recommendations, or solicitation to trade. Always conduct your own research and consult a qualified financial advisor before making investment decisions.
Important Disclaimer
Catalyst predictions are generated by AI for informational purposes only and do not constitute financial advice, investment recommendations, or solicitation to buy or sell any assets. The World Now is not a registered investment advisor, broker-dealer, or financial planner.
Past performance does not guarantee future results. Cryptocurrency and financial markets are highly volatile and involve substantial risk of loss. Always conduct your own research and consult a qualified financial advisor before making investment decisions. The World Now and its affiliates accept no liability for any losses arising from the use of this information.
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“Causal mechanism: JPMorgan tokenized push benefits cross-border tokens like XRP via banking adoption sentiment. Historical precedent: November 2021 majors rally XRP +15% in 48h. Key risk: legal overhang resurfacing.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: Crypto-specific volatility not systemic, limiting safe-haven flows into gold. Historical precedent: During 2022 FTX collapse, gold stayed flat intraday. Key risk: Spillover risk-off drives modest inflows.”
Farage faces UK standards probe over $7M gift from crypto billionaire
“Causal mechanism: Rebound to $80K on JPMorgan tokenized funds drives immediate sentiment-led buying, ignoring hot CPI. Historical precedent: November 2021 bull run started with BTC +10% in 48h to $69K. Key risk: liquidation cascades from overleveraged longs.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: Oracle/security focus heightens hack sensitivity, correlating to BTC dump. Historical precedent: 2022 Ronin hack (oracle ties) dropped LINK 15% in 48h. Key risk: Chainlink proves resilient.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: Indirect AI/crypto link minor vs cloud/growth drivers. Historical precedent: Flat during 2022 FTX volatility. Key risk: AI hack fears hit sentiment.”
May 13, 2026
“Causal mechanism: Crypto rebound spills over to broader risk-on equity sentiment, ignoring hot CPI as tech/financial stocks benefit from adoption themes. Historical precedent: November 2021 crypto surge saw SPX rise 4% in a week on correlated risk appetite. Key risk: AI malware fears amplifying tech sector selling.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: BTC-led rebound pulls altcoins like SOL higher on momentum and thin liquidity. Historical precedent: November 2021 BTC surge saw SOL +25% in 48h. Key risk: recent -2.92% momentum reversal on profit-taking.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: Risk-on crypto surge reduces safe-haven demand for USD as capital flows to higher-yield assets. Historical precedent: Similar to November 2021 crypto bull run when USD index fell 1.5% over two weeks amid risk appetite. Key risk: renewed CPI-driven Fed hike fears sparking safe-haven bid.”
May 13, 2026
“Causal mechanism: Mistral AI malware highlights sector vulnerabilities, pressuring AI-exposed stocks like GOOGL via sentiment contagion. Historical precedent: No direct historical precedent; estimating based on 2025 DeepSeek AI release when NVDA dropped 17% intraday. Key risk: crypto surge offsetting with risk-on bid.”
NY judge pushes back hearing for Aave’s bid to unfreeze $71M in ETH
“Causal mechanism: AI malware in Mistral pressures META's AI investments via sector risk-off. Historical precedent: 2025 DeepSeek event META dipped 5% intraday on AI fears. Key risk: crypto risk-on lifting social/ad platforms.”
Farage faces UK standards probe over $7M gift from crypto billionaire
“Causal mechanism: Crypto rebound spills risk-on to mega-cap tech, with AAPL less exposed to AI malware risks. Historical precedent: November 2021 crypto surge saw AAPL +3% in 48h. Key risk: hot CPI weighing on consumer spending narrative.”
Bank of England reconsiders strict stablecoin regime
“Causal mechanism: BTC rebound and JPMorgan tokenized funds lift ETH as a crypto major via sentiment correlation and ecosystem flows. Historical precedent: November 2021 BTC surge to $69K saw ETH rise 20% in 48h. Key risk: profit-taking after recent -0.64% dip extends.”
Ex-Celsius exec sentenced to time served after guilty plea
“Causal mechanism: Crypto-specific hacks have negligible transmission to safe-haven CHF flows absent systemic financial stress. Historical precedent: No direct historical precedent; estimating based on 2022 Ronin hack when CHF was flat. Key risk: Crypto contagion triggers global risk-off, boosting CHF.”
Crypto Hacks Surge Amid Regulatory Advances and Market Shifts
“Causal mechanism: AI malware raises chip demand uncertainty for AI training, hitting semis like TSM. Historical precedent: 2025 DeepSeek release caused NVDA/TSM peers -10-17% short-term. Key risk: crypto mining rebound offsetting.”
Crypto Markets Surge Amid AI Risks and Institutional Shifts
May 13, 2026
“Causal mechanism: Tech-heavy QQQ sees trivial crypto risk-off contagion absent direct exposure. Historical precedent: During 2022 Ronin hack, QQQ traded sideways. Key risk: Tech firms' blockchain ventures amplify downside.”
Crypto Hacks Surge Amid Regulatory Advances and Market Shifts
“Causal mechanism: Crypto hacks lack transmission to EUR via trade or policy absent EU specifics. Historical precedent: No direct historical precedent; estimating based on 2016 DAO non-impact on EUR. Key risk: EU regulatory response weakens EUR.”
Crypto Hacks Surge Amid Regulatory Advances and Market Shifts