Searching for how to research U.S. stocks or crypto with AI? Here is one real AstraEye Labs report, published and readable without an account, taken step by step: what each part is, how to check it, and where its data came from.
Start with the assets you follow: U.S. stocks, ETFs, crypto, or a ready-made market slice such as the S&P 500, a sector or the top 100 coins. Then pick analyses from the catalog, or start from a research template that already combines them. A run shows its price in Astra Credits before it starts.
The introduction is SAGE's summary of the whole run: what was researched and what stood out. Read it first for the shape of the findings, then go to the desks for the evidence.
Market conditions in late September 2026 show divergent technical postures between crypto and equity assets. Crypto exhibits persistent bullish momentum and timeframe alignment, while equities display a broader contraction phase with individual pockets of strength. The correlation matrix, breadth indicators, momentum scans, and trend analyses from ATLAS collectively map these opposing forces across a 100-asset sample split evenly between the two classes.
Each section is one specialist AI scientist's analysis, such as technical structure, fundamentals, news or on-chain data. Each works by its own method, and the figures in it were computed in code from market data, not recalled by a language model.
Cross-Asset Correlation: The 50 crypto tokens and 50 equities in this run formed tight intra-crypto clusters and sparse intra-equity pairs, reflecting concentrated risk in digital assets and modest sectoral linkages in stocks. The core BTC-ETH-SOL-BNB cluster held correlations between 0.75 and 0.87, the DeFi set (AAVE, RENDER, LINK, LIT) between 0.74 and 0.79, and the meme layer (DOGE, XRP, PEPE, ENA) between 0.76 and 0.90. Privacy coins XMR and ZEC stayed isolated at only 0.28. Equities produced only two pairings above the 0.65 threshold: ACGL/L at 0.85 and CDNS/XYL at 0.79. Cross-class pairs ranged from -0.3 to +0.3, pushing the overall diversification score to 51 out of 100 - equity portion ~65, crypto ~35. The crypto half of the sample remains exposed to clustered drawdown risk while equities offer mild but uneven diversification.
Equity Market Breadth: On 18 September 2026 the broader US equity universe - proxied by 518 priced names - posted 161 advancers against 356 decliners. The advance/decline ratio of 0.45 and an advancer share of only 31.14 % among the 517 names that moved classified the session as risk_off. The 50-stock sub-sample tracked 20-day and 60-day returns: eight names (A, DGX, INTC, JNJ, PSX, TECH, TMO, VLO) sat above all three moving averages (20, 50, 200), and 27 names remained above the 200-day line, yet the 20-day average return stood at -3.29 %. Three readings flagged regime durability limits: the share gap between advancers and decliners reached 37.64 points, the average 1-day return was -0.44 %, and a single flipped name could not lift the share above the 40 % risk_off threshold. Equity breadth data conveys a clear short-term downtrend with isolated defensive or thematic leaders holding above their moving averages.
Market Breadth Analysis: The 100-asset cohort produced a mixed regime label: crypto registered expanding with 44 % new 30-day highs and a 9-to-1 advancer/decliner ratio, while equities shrank with 76 % new 30-day lows and a 0.35 ratio. Across the full set, 58 assets advanced, 42 declined, and 62 % sat above their 200-bar averages. Crypto’s readings for 20-bar, 50-bar, and 200-bar all reached saturated levels (no further improvement distinguishable). The cross-class tension suppresses the aggregate label, yet crypto’s unbroken expansion leaves its half of the sample under sustained positive pressure. The mix masks persistent crypto strength versus broad equity contraction, highlighting the regime split inside the cohort.
Momentum Scan: Daily MACD histograms split the cohort into 51 bullish and 39 bearish labels. Crypto dominated the bullish tally (43 of 50) against only 11 bullish equities, while 37 of the 39 bearish labels traced to stocks. Scaled histograms (histogram/price %) ranged from -1.63 % (BTW) to +4.04 % (ZEC and NEAR). Seven crypto bulls - BTC, ETH, BNB, DOGE, SHIB, LINK, BTW - carried negative histograms, and three equity bears - CINF, L, XYL - carried positive histograms. The divergence was especially sharp in the tails: COO (equity) led with a -2.39 % scaled histogram, ZEC and NEAR (crypto) with +4.04 % each. The scan confirms short-term crypto momentum remains structurally stronger than equity momentum, despite pockets of disagreement between histogram direction and composite label.
Multi-Timeframe Alignment: Across daily, weekly, and monthly charts, 22 crypto assets (AAVE, BNB, BTC, ETH, SOL, XMR, etc.) reached aligned_bullish, matching their histogram strengths. Only seven equities stayed aligned (A, DGX, JNJ, PSX, TECH, TMO, VLO), while 24 moved to leaning_bearish and six (CDNS, CI, EME, ETR, REG, RL) fell into aligned_bearish. Crypto produced no aligned bearish readings; equities produced no aligned bullish majority. The most sensitive reading - moving one asset across states - shifts each class by ~2 points. Crypto assets converged upward across all three timeframes, while equities diverged downward, reinforcing the technical-regime split.
Trend & Structure Analysis: Deterministic moving-average rules placed 29 assets in uptrend: 22 crypto (BTC, ETH, SOL, XRP, etc.) and seven equities (A, DGX, JNJ, PSX, TECH, TMO, VLO). Five equities (CDNS, COO, DPZ, HD, XYL) marked downtrends, leaving 66 in sideways. The crypto uptrend group repeatedly registered overbought RSI(14) readings (AAVE 69.8, ENA 81.9, HYPE 78.0, INJ 80.4, NEAR 85.5, WLD 74.5, ZEC 89.6) and rangePositionScores above 95, yet only OP crossed firmly above its 50-bar band. Valero (VLO) exemplified the equity cohort’s strongest uptrend, trading 10 % above the 20-bar line, 22 % above 50-bar, and 66 % above 200-bar, yet its RSI(14) also pierced 80. Trend-sensitive metrics keep most crypto assets in uptrend regimes despite elevated RSI, while equities split between sideways consolidation and emerging downtrends.
For any figure, look for the window and date it covers, the rule it applies, the method behind it and the source of the data. A figure that carries none of these has not been shown to be right, however precise it looks.
A real statement taken apart this way is in the guide Seven checks before you trust an AI's stock or crypto numbers.
The bottom line pulls the desks together: where they agree, where they conflict, and what the run could not measure. It describes what the data shows; it does not tell you what to do.
The research surfaces a clear regime divergence: crypto assets maintain persistent bullish multi‐timeframe alignment, firm trend structures, expanding breadth, and strong momentum, consistently beating their 20/50/200-day averages, while equities contract broadly - 76 % posting new 30-day lows - fragmenting into isolated pockets of uptrending names. The indicator split, not a consensus, is the market’s defining feature and warrants independent review of asset-class risk exposure.
Every report ends with the providers whose data it used, credited as each provider requires, so you can go to the source and compare for yourself.
SAGE, the research guide, answers questions about any finished report: what a reading means, why two desks disagree, or what a method cannot support.
You can ask in AstraEye, or from ChatGPT, Claude, Gemini, Perplexity, Grok or Glama, where AstraEye Labs connects as an app.
Every desk section, the bottom line and the data sources, as published. No account needed.
Choose the stocks or ETFs you follow, run research that computes each figure from market data instead of recalling it, then read the findings with their method and sources. In AstraEye Labs, specialist AI scientists compute technical, fundamental, news and derivatives readings in code on licensed market data, and SAGE, the research guide, writes them up in one report.
The same way: pick the coins, and use research that computes its figures from market and on-chain data rather than a chatbot's memory. AstraEye Labs covers crypto alongside U.S. stocks and ETFs, including on-chain data, derivatives, news and sentiment, in the same report.
Yes. An AstraEye Labs report can cover U.S. stocks, ETFs and crypto in one run, so questions about how the two relate, such as whether they move together, can be measured by the same rules on both sides.
A report in which AI analyses a set of stocks or crypto assets and explains what it found. In an AstraEye Labs report, each analysis states its method and what it could not measure, the figures are computed in code, and the report ends with the data sources it used.
Ask where each number came from, which window and date it covers, and how it was calculated, then compare it with the source: the filing for fundamentals, the price provider for market data. Every AstraEye Labs report lists its data sources and the method behind each analysis, so each figure can be traced.
AstraEye Labs computes from licensed market data (prices, fundamentals, news, on-chain and derivatives data) and named public sources, and every report credits the providers it drew on.
AstraEye Labs research is impersonal and descriptive: it reports what the data shows and how it was measured. Informational research only. AstraEye Labs does not provide financial advice or recommendations. You decide what, if anything, to do.
Yes. AstraEye Labs connects to ChatGPT, Claude, Gemini, Perplexity, Grok or Glama as an app, so the assistant can read your finished reports and their methods, and ask SAGE to price and start new research.
There is a free plan, and paid plans start at $19 a month (Space Analyst). New accounts get a 7-day trial with no card. Every research run shows its price in credits before it starts.
Informational research only. AstraEye Labs does not provide financial advice or recommendations. You decide what, if anything, to do.