Blog
Data-driven insights on chart patterns, market structure, and how visual pattern search works.
AMAT Earnings Recap: Central Tendency Held, IQR Captured The Move
AMAT reported and reacted +0.90%. Pre-print cohort: n=262, 5d median +0.57%, IQR [-2.15%, +3.04%]. Verdict: central tendency hold. Top feature: hy_oas.
DE Earnings Recap: Central Tendency Held, IQR Captured The Move
DE reported and reacted -1.04%. Pre-print cohort: n=266, 5d median +0.37%, IQR [-3.11%, +3.51%]. Verdict: central tendency hold. Top feature: sector_etf=XLK.
PLTR Cohort Snapshot 2026-05-14: Consensus 0.34, Bearish Bias
Today's notable cohort on PLTR: n=90, consensus 0.34, 5d median -1.49%, IQR [-3.96%, +1.25%]. Top feature: relative_volume.
AMZN Cohort Snapshot 2026-05-14: Consensus 0.41, Bullish Bias
Today's notable cohort on AMZN: n=285, consensus 0.41, 5d median +1.17%, IQR [-1.70%, +4.12%]. Top feature: hy_oas.
JPM Cohort Snapshot 2026-05-14: Consensus 0.68, Bearish Bias
Today's notable cohort on JPM: n=281, consensus 0.68, 5d median -0.54%, IQR [-2.40%, +1.19%]. Top feature: sector_etf=XLY.
BABA Pre-Earnings: Moderate Cohort Consensus Heading Into The Print
BABA reports earnings on 2026-05-15. The live cohort_analyze pull on 2026-05-14 returned n=216 historical analogs. 5d median -0.12%, IQR [-3.15%, +1.68%], consensus 0.46 (moderate). Top feature: spy_ret_60d.
JD Pre-Earnings: Weak Cohort Consensus — Analogs Disagree On Direction
JD reports earnings on 2026-05-15. The live cohort_analyze pull on 2026-05-14 returned n=215 historical analogs. 5d median +0.37%, IQR [-4.98%, +5.37%], consensus 0.00 (weak). Top feature: hy_oas.
CSCO Earnings Recap: Central Tendency Held, IQR Captured The Move
CSCO reported and reacted +2.60%. Pre-print cohort: n=234, 5d median -0.02%, IQR [-3.97%, +2.85%]. Verdict: central tendency hold. Top feature: sector_etf=XLU.
Why we stopped backtesting our intelligence layer (and what we found instead)
Backtests are the right tool for trading strategies. They're the wrong tool for AI reasoning infrastructure. We tested Chart Library against itself: two identical Claude agents, one with our tools, one without. A blind LLM judge scored their reasoning across 50 out-of-sample scenarios. The agent with Chart Library won 50-0. Every reasoning dimension lifted. Paired t-statistic above 10 on every dimension. Here's how we got here.
SOFI Cohort Snapshot 2026-05-11: Consensus 0.34, Bearish Bias
Today's notable cohort on SOFI: n=276, consensus 0.34, 5d median -0.85%, IQR [-4.55%, +3.13%]. Top feature: sector_etf=XLF.
AMAT Cohort Snapshot 2026-05-11: Consensus 0.39, Bullish Bias
Today's notable cohort on AMAT: n=264, consensus 0.39, 5d median +0.69%, IQR [-2.21%, +3.10%]. Top feature: hy_oas.
GME Cohort Snapshot 2026-05-11: Consensus 0.24, Bearish Bias
Today's notable cohort on GME: n=243, consensus 0.24, 5d median -0.96%, IQR [-4.63%, +2.88%]. Top feature: credit_spread_state=normal.
CSCO Cohort Snapshot 2026-05-11: Consensus 0.51, Flat Central Tendency
Today's notable cohort on CSCO: n=245, consensus 0.51, 5d median +0.21%, IQR [-3.73%, +2.82%]. Top feature: sector_etf=XLU.
HIMS Cohort Snapshot 2026-05-11: Consensus 0.21, Flat Central Tendency
Today's notable cohort on HIMS: n=196, consensus 0.21, 5d median -0.21%, IQR [-3.45%, +2.67%]. Top feature: realized_vol_20d.
We Mined 4M Chart Patterns. Here's the Cluster-First Paradigm That Came Out.
Traditional chart-pattern intelligence is anchor-first: take a (symbol, date), find its analogs. We tried the opposite — mine the V5 embedding space offline for clusters where forward returns were consistently positive (or negative) across train and test. Top 20 winning clusters and 20 losing clusters with full feature signatures, exposed as MCP tools. Backtested S8 strategy: Sharpe 0.90, max drawdown 6.6% (vs SPY 22.4%).
COIN Earnings Recap: Central Tendency Held, IQR Captured The Move
COIN reported and reacted -2.53%. Pre-print cohort: n=29, 5d median -1.09%, IQR [-3.31%, +2.24%]. Verdict: central tendency hold. Top feature: abs_price_return_z.
DKNG Earnings Recap: Bullish Bucket Realized Inside The IQR
DKNG reported and reacted +5.43%. Pre-print cohort: n=286, 5d median -0.11%, IQR [-4.66%, +4.99%]. Verdict: upper IQR realization. Top feature: sector_etf=XLK.
ABNB Earnings Recap: Central Tendency Held, IQR Captured The Move
ABNB reported and reacted +0.41%. Pre-print cohort: n=254, 5d median +0.53%, IQR [-2.03%, +3.35%]. Verdict: central tendency hold. Top feature: macro_state=bullish.
TTD Earnings Recap: Central Tendency Held, IQR Captured The Move
TTD reported and reacted -2.17%. Pre-print cohort: n=289, 5d median +0.80%, IQR [-4.07%, +5.12%]. Verdict: central tendency hold. Top feature: yield_curve_state=inverted.
RKLB Earnings Recap: Bear Bucket Realized Inside The IQR
RKLB reported and reacted -7.17%. Pre-print cohort: n=229, 5d median -0.03%, IQR [-5.30%, +3.80%]. Verdict: lower IQR realization. Top feature: credit_spread_state=tight.
GILD Earnings Recap: Central Tendency Held, IQR Captured The Move
GILD reported and reacted -1.64%. Pre-print cohort: n=250, 5d median +0.24%, IQR [-2.13%, +2.58%]. Verdict: central tendency hold. Top feature: sector_etf=XLF.
ENB Earnings Recap: Central Tendency Held, IQR Captured The Move
ENB reported and reacted -1.01%. Pre-print cohort: n=271, 5d median +0.08%, IQR [-3.03%, +3.39%]. Verdict: central tendency hold. Top feature: vol_regime=high.
BAC Cohort Snapshot 2026-05-08: Consensus 0.69, Bullish Bias
Today's notable cohort on BAC: n=283, consensus 0.69, 5d median +0.79%, IQR [-0.82%, +2.36%]. Top feature: sector_etf=XLC.
GILD Cohort Snapshot 2026-05-08: Consensus 0.62, Bullish Bias
Today's notable cohort on GILD: n=247, consensus 0.62, 5d median +0.57%, IQR [-1.88%, +3.16%]. Top feature: sector_etf=XLU.
XOM Cohort Snapshot 2026-05-08: Consensus 0.60, Bullish Bias
Today's notable cohort on XOM: n=272, consensus 0.60, 5d median +0.53%, IQR [-1.80%, +2.13%]. Top feature: sector_etf=XLI.
MCD Q1 2026 Earnings: What 12 Years of Reaction Cohorts Say
McDonald's reports Q1 2026 before the open on May 7. Pulled the cohort of MCD earnings analogs back to 2014 — comp-store-sales beat vs. miss is the single feature that flips the 5-day forward distribution from positive to negative.
DDOG Q1 2026 Earnings: The Observability Cohort Going In
Datadog reports Q1 2026 before the open May 7. The cohort of DDOG and adjacent observability/devtools earnings prints shows that net-revenue-retention is the single feature that separates +6% follow-throughs from -8% fades.
CELH Pre-Earnings: A High-Vol Cohort With A Distinct Reaction Pattern
Celsius Holdings reports Q1 2026 before the open May 7. The cohort of CELH earnings prints — and adjacent high-growth beverage analogs — has a distinct two-mode reaction distribution driven by Pepsi-channel commentary.
VST Q1 2026: The AI-Power Cohort Going Into Earnings
Vistra reports Q1 2026 before the open May 7. The cohort of VST earnings analogs has been reshaped by the AI-power thesis since 2023 — and the data center contracted-MW disclosures are now the dominant feature in the post-print reaction.
COIN Q1 2026 Pre-Earnings: What The Cohort Says Before Tonight's Print
Coinbase reports Q1 2026 after the close May 7. The cohort of COIN earnings prints has a distinct interaction with BTC's prior-30-day move — and the spot-ETF-flow feature has reshaped the reaction profile since 2024.
DKNG Pre-Earnings: The Sportsbook Cohort Heading Into Q1
DraftKings reports Q1 2026 after the close May 7. The cohort of DKNG earnings prints has a distinct seasonality interaction with Q1 — March Madness handle is the dominant feature in the post-print reaction.
ABNB Q1 2026 Pre-Earnings: The Travel Cohort And What It's Saying
Airbnb reports Q1 2026 after the close May 7. The cohort of ABNB earnings prints — plus cross-ticker travel-platform analogs — shows that Q2 nights-booked guidance is the single feature that flips the post-print 5-day distribution.
TTD Q1 2026 Pre-Earnings: The Programmatic Ad Cohort
The Trade Desk reports Q1 2026 after the close May 7. The cohort of TTD earnings prints has the widest reaction band in ad-tech — and CTV revenue mix is the dominant feature in the post-print 5-day continuation.
RKLB Pre-Earnings: A High-Beta Cohort Heading Into Q1
Rocket Lab reports Q1 2026 after the close May 7. The cohort of RKLB earnings prints — and adjacent space-launch / defense-tech analogs — has a distinct two-mode reaction pattern driven by Neutron program milestones.
GILD Q1 2026 Pre-Earnings: A Defensive Biotech Cohort
Gilead Sciences reports Q1 2026 after the close May 7. The cohort of GILD earnings prints is one of the tightest in biotech — HIV franchise commentary and Trodelvy uptake dominate the post-print reaction.
ENB Q1 2026 Pre-Earnings: A Tight Energy-Infrastructure Cohort
Enbridge reports Q1 2026 before the open Friday May 8. The 268-match cohort is mildly bullish heading in (5d median +0.49%, 10d +1.44%) — and the dominant feature is the cross-sector technology factor.
WMT Pre-Earnings Coiling: A Tight Cohort With A Defensive-Sector Read
Walmart reports Q1 2026 in two weeks. The live 266-match cohort is one of the tightest in retail (tightness 0.65) — and the 5-day forward distribution sits inside a [-2.1%, +1.8%] IQR with a slight negative bias.
HD Pre-Earnings Drift: A Tight Cohort Leaning Negative
Home Depot reports Q1 2026 on May 19. The 279-match cohort is tight (0.67) and leans negative — 5d median -0.99%, IQR [-3.2%, +1.5%], hit-rate 41%. The dominant feature is consumer-staples sector divergence.
TGT Pre-Earnings: Tight Cohort, Negative Skew Through 10 Days
Target reports Q1 2026 around May 20. The live 278-match cohort is the tightest in retail (0.68) and the 10-day median is -1.67% — bear case dominates.
CSCO Pre-Earnings: A Tight Cohort With Credit-Spread Sensitivity
Cisco reports Q1 2026 mid-May. The 257-match cohort is tight (0.61) — 5d median -0.18%, IQR [-3.5%, +2.5%]. The credit-spread regime is the dominant feature.
AMAT Pre-Earnings: A Wide Cohort With No Decisive Pre-Print Read
Applied Materials reports Q1 2026 mid-May. The 242-match cohort is wide (tightness 0.28) — 5d IQR [-3.7%, +3.9%]. Pre-print shape isn't decisive; the print itself is the signal.
BABA Pre-Earnings: The Most Bullish Cohort Of The Week
Alibaba reports Q1 2026 mid-May. The 272-match cohort is the most bullish setup in our weekly scan — 5d median +1.23%, hit-rate 64%, 10d median +1.96%.
NVDA Pre-Earnings Drift: A Wide Cohort, A Time-Decay Feature
Nvidia reports Q1 2026 in late May. The 258-match cohort is wide (0.24) — pre-print shape isn't decisive yet. Top feature is days-since-earnings, a time-decay signal.
DE Pre-Earnings: A Vol-Sensitive Cohort With Modest Bullish Bias
Deere reports Q1 2026 mid-May. The 286-match cohort is moderate (0.41) and slightly bullish — 5d median +0.20%. The dominant feature is VIX level.
JD Pre-Earnings: A Wide Cohort In A Choppy China-ADR Setup
JD.com reports Q1 2026 mid-May. The 207-match cohort is wide (0.22) and tilts negative — 5d median -0.80%, IQR [-5.2%, +3.3%]. Pre-print shape is choppy.
DDOG Earnings Recap: The Cohort Got The Direction, Missed The Magnitude
Datadog ripped ~28% on Q1 2026. Our pre-print cohort said NRR ≥130% + raised guide → +6.1% with 71% hit-rate. The print delivered exactly that signal, but the magnitude blew through the IQR upper band. A calibration honest-take.
MCD Earnings Recap: Cohort Central Tendency Held, CEO Commentary Faded The Move
McDonald's beat EPS, missed revenue, and posted +3.8% global comps. Stock initially +1% pre-market, then gave back gains as the CEO flagged consumer-environment concerns. The cohort's central-tendency call held; the call-commentary feature is what flipped the day.
CELH Earnings Recap: Acquisition Tailwind Drove A Top-IQR Move
Celsius reported record Q1 revenue (+138% YoY) on the back of Alani Nu and Rockstar acquisitions, beat EPS, and the stock ran +6-10% premarket. The cohort flagged Pepsi-channel velocity as the dominant feature; the actual driver was the M&A roll-up, an external feature that contributed to the upside surprise.
VST Earnings Recap: Solid Print, Soft Reaction — The Contracted-MW Feature Wasn't There
Vistra reported Q1 net income of $1.03B and reaffirmed 2026 guidance, but stock drifted -1.3% on the day. Our pre-print cohort flagged contracted-MW disclosure as the dominant feature; the print landed in the 'no new contract announced' bucket, which historically maps to the lower IQR.
PLTR Pre-Earnings Drift: Setup Heading Into Monday's Print
Palantir reports Q1 2026 earnings Monday after close. We pulled the historical pre-earnings drift pattern for PLTR — what the stock tends to do in the 5 trading days before earnings, and the win rate of long-the-drift since the AI capex cycle began.
PLTR Earnings-Day Base Rates: The Last 12 Quarters
Palantir's earnings-day reactions over the last 12 quarters: how often the stock has held the reaction 1, 5, and 10 sessions later, and which features predicted the difference between a fade and a follow-through.
PLTR Post-Earnings Gaps: Hold or Fade Across the Last 8 Quarters
Palantir's last 8 post-earnings gaps decomposed: which gaps held into the open, which faded by mid-day, and what the cohort retrieval says about the typical 5-day path after a >10% earnings move.
AMD Pre-Earnings Drift: What the Last 14 Cycles Show
AMD reports Q1 2026 earnings Tuesday after close. We pulled the historical pre-earnings drift pattern — what AMD tends to do in the 5 trading days before earnings, and how that's correlated with the AI-capex cycle backdrop.
AMD Earnings Reactions: 14 Quarters of Data, AI Cycle vs Pre-AI
AMD's earnings reactions decomposed across 14 quarters, split between the AI-capex era (2024+) and the prior cycle. The reaction-day moves, hold rates, and feature attribution that explain the difference.
AMD Post-Earnings Gaps: Hold Rate Across the AI Cycle
AMD has gapped on every earnings print since 2024. The hold rate, fade triggers, and what the cohort retrieval shows about the typical 5-day path after a double-digit earnings gap.
Disney Pre-Earnings Setup: Parks, Streaming, and the Capex Question
Disney reports earnings next week. The analog cohort heading into the print, what the parks vs streaming split has historically signaled, and what the capex commentary tends to drive in the 5-day follow-through.
Disney Earnings Reactions: 16 Quarters of Hold-vs-Fade Data
Disney's last 16 earnings-day reactions: how often the stock held the day-0 move 5 and 10 sessions later, and which feature within the cohort separated the holds from the fades.
Vertex Pharma Pre-Earnings Setup: Biotech Earnings Reaction Patterns
Vertex Pharmaceuticals reports earnings next week. Biotech earnings have a distinct reaction profile vs cyclicals — driven by drug-launch trajectories rather than current-quarter beats. The cohort retrieval and what to watch.
Paramount Skydance: First Earnings as a Merged Entity
Paramount Skydance reports its first full quarter as a merged entity. Merger-deal earnings have a distinct reaction pattern dominated by synergy realization commentary and balance-sheet repositioning. The historical analog set and what to watch.
TSLA After a Big Earnings Beat: What Historical Analogs Say
Tesla reported Q1 2026 revenue up 16% and EPS up 52% after Wednesday's close. We pulled historical analogs of TSLA charts that followed similar above-consensus earnings prints to see what typically happens in the next 1, 5, and 10 sessions.
What Happens to TSLA After a Big Earnings-Day Gap: 10-Year Base Rates
TSLA gapped meaningfully after its Q1 2026 print. We ran the historical base rates: how often the gap holds, how often it fades, and what predicts which group a given earnings day ends up in.
INTC Pre-Earnings Drift: Historical Setup Into Tonight's Print
Intel reports Q1 2026 earnings tonight. We pulled the historical pre-earnings drift pattern — what INTC tends to do in the 5 trading days before earnings, and how that's correlated with the actual reaction.
INTC Earnings-Day Base Rates: The Last 20 Quarters
Intel's earnings-day reactions over the last 20 quarters: how often the stock has held the reaction 1, 5, and 10 sessions later, and which features predicted the difference.
LMT Earnings Reaction: How Defense Names Tend to Trade Post-Print
Lockheed Martin reported Q1 2026 earnings today. Defense stocks have a distinct earnings-reaction profile vs. cyclicals. We pulled the historical analog set to see what LMT's current chart typically does next.
AXP After Earnings: What the Credit-Card Tape Tells Us
American Express reported Q1 2026 today. AXP's earnings-day reaction is one of the cleaner real-time reads on consumer credit health. We pulled the historical follow-through base rates and what they implied for broader consumer names afterward.
HON Earnings Reaction: The Industrials Tape Read-Through
Honeywell reported Q1 2026 earnings today. Industrial conglomerates like HON have a distinct earnings-reaction pattern. We pulled the historical base rates and what they signal about the broader industrial complex.
QS +33% Gap on Eagle Line News: What Historical Analogs Do After a Gap This Big
QuantumScape is up +33.7% premarket after reporting the Eagle Line production facility is now operational. Gaps this size on speculative battery names have a specific follow-through profile. Here's what the historical analogs show.
TMO Earnings: Historical Reactions for a Diversified Life-Sciences Print
Thermo Fisher reports Q1 2026 earnings today. TMO's diversified portfolio produces a characteristic earnings-reaction pattern. Here's what the historical analogs show about the likely 5-day follow-through.
UNP Earnings: How Rail Stocks Tend to React Post-Print
Union Pacific reported Q1 2026 earnings today. Rail stocks have a distinctive earnings-reaction profile driven by volume guidance and fuel-cost commentary. Here's what UNP's analog set implies for the next 10 sessions.
One Anchor Said -3.6%. 100 Anchors Said -0.5%. The Perils of Single-Anchor Decompositions.
Decomposing a cohort of 500 historical chart patterns for NVDA produced a striking slice: anchors formed inside an earnings window underperformed by -3.6 percentage points. We ran the same decomposition across 100 different anchors. The real population effect is -0.5pp, and half of it is an event-proximity artifact that also shows up on dividend dates. Here's the audit.
We Added 5 Regime Filters. They Don't Do Much. Here's Why That's Interesting.
Academic papers say VRP, VIX term structure, credit spreads, and yield curve should condition forward returns. We added filters for all of them. Across 200 anchors and 2,400 cohort runs, the distributions barely moved. That's a real finding — and it tells us something specific about where agent-ready base rates actually come from.
From Retrieval to Calibrated Retrieval: Conformal Prediction on Agent Base Rates
Our cohort API was returning quantile bands that were too narrow. Nominal 80% coverage ran at 68% on held-out data. Here's the audit, the conformal fix, and why agents calling any historical-pattern API should demand empirical coverage numbers instead of taking quantiles at face value.
3 Patterns for AI Agents That Analyze Stock Charts
Specific, reusable patterns agent builders can apply today: grounded base rates, the edge-mining loop, and named-analog tagging. Each one addresses a failure mode we see in production stock-research agents.
How to Build a Stock-Research Agent That Doesn't Hallucinate
A working pattern for AI agents that need real historical base rates instead of plausible-sounding guesses. One API primitive, three filter dimensions, full outcome distributions with survivorship flags.
Eval Integrity: How We Found the Leakage and Why Our Baseline Lied
We audited our own pattern-embedding evaluation and found 53% of held-out samples had same-symbol training neighbors within 20 days. Here's what we changed — and why agent developers should demand this kind of rigor from any historical-pattern API.
I Ran 16,438 Chart Pattern Predictions. Here's What Actually Works.
A real forward-testing study across 16,438 automated pattern predictions. Overall accuracy is coin-flip. But three context conditions produce statistically significant edges.
The 85% Win Rate Signal Nobody Is Using: Bearish Patterns on Low-Vol Stocks
When our pattern-match system says bearish on a low-volatility stock, it's been right 85% of the time over 5 days. Here's the specific setup and why it works.
The VIX Paradox: Why Bullish Signals Work Better When Everyone's Scared
Intuitive finance says high VIX = bad time to be long. Our data across 16K+ predictions shows the opposite for pattern-based bullish setups.
Market Breadth Is The Most Underrated Chart Pattern Filter
When fewer stocks are above their 50-day MA, bearish signals hit 78% and bullish signals collapse to 29%. The %-above-MA filter is free, public data, and nobody uses it properly.
Same Chart, Same Regime: Launching Context-Aware Pattern Matching
Chart Library now matches historical patterns by shape AND market regime (VIX, yield curve, credit spreads, breadth). Here's what 16K+ forward tests revealed about when pattern matching works — and when it doesn't.
Tesla (TSLA) Chart Pattern Analysis April 2026: 8-Week Losing Streak
Tesla is in its longest losing streak in years. Historical chart pattern analysis of TSLA after extended selloffs shows what typically happens next.
TSLA Support and Resistance Levels: Where Tesla Finds a Floor
Tesla support and resistance analysis using historical chart patterns. Where TSLA has historically found buyers after extended selloffs.
Palantir (PLTR) Technical Analysis Today: Burry's Bearish Bet
PLTR is down 28% in 2026 as Michael Burry doubles down on put options. Historical chart pattern data shows what happens after Palantir extended declines.
PLTR Similar Chart Patterns: What History Says About Palantir's Decline
Palantir's 28% YTD decline matches several historical patterns. See what happened next when PLTR showed this chart shape before.
Micron (MU) Breakout Pattern: Is MU Setting Up for a Move?
Micron Technology gained 3.15% on heavy volume. Chart pattern analysis shows whether MU's current setup matches historical breakout patterns.
MU Technical Analysis Today: Micron's Chart Setup Heading Into Q2
Micron Technology technical analysis for April 2026. Pattern data shows MU's current chart shape and what similar setups produced historically.
Intel (INTC) Chart Pattern Analysis April 2026: Can the Rally Continue?
Intel gained on heavy trading volume. Chart pattern analysis of INTC shows whether the current setup matches historical continuation patterns.
Is Intel (INTC) Forming a Bull Flag? Pattern Data Analysis
Intel's recent price action may be forming a bull flag pattern. Historical data on INTC bull flags and what they typically produce.
Verizon (VZ) Gap Down Analysis: Biggest Dow Loser on April 10
Verizon dropped 3.62%, the biggest Dow Jones loser. Historical gap down analysis for VZ shows recovery patterns and forward return data.
VZ Support and Resistance Levels April 2026: Where Verizon Stabilizes
Verizon support and resistance analysis after its 3.62% decline. Pattern data shows where VZ has historically found buyers.
Salesforce (CRM) Technical Analysis: Down 3.43% in Dow Selloff
Salesforce dropped 3.43% in the April 10 Dow selloff. Historical chart pattern analysis shows CRM forward returns after sharp declines.
CRM Similar Chart Patterns: What Salesforce's History Tells Us
Salesforce's current chart matches several historical patterns. See what happened when CRM showed similar setups in the past.
Ford (F) Chart Pattern Analysis: April 2026 Breakout Setup
Ford stock surged 5.7% on heavy volume. We analyze F's current chart pattern against 10 years of historical analogs to see what typically happens next.
Ford (F) Gap Up Follow-Through: Does the Rally Continue?
Ford gapped up 5.7% today. Historical data on Ford gap-ups shows whether these moves tend to continue or fade over the next 1-10 days.
Amazon (AMZN) Chart Pattern Analysis April 2026
Amazon is the most active stock today. We analyze AMZN's current chart pattern using historical similarity search across 25M+ embeddings.
Is Amazon (AMZN) Breaking Out or Is This a Bull Trap?
AMZN just broke above its consolidation range. Historical pattern data reveals how often Amazon breakouts sustain vs. fail.
Cloudflare (NET) Down 12%: What Similar Selloffs Have Led To
NET dropped nearly 12% today. We examine what happened historically after similar Cloudflare selloffs using pattern similarity search.
Cloudflare (NET) Similar Historical Chart Patterns After Sharp Drops
Find the most similar historical chart patterns to Cloudflare's current selloff. Pattern similarity search across 10 years of data.
Workday (WDAY) Technical Analysis: Down 6.5% — What History Shows
Workday dropped 6.5% today. Historical pattern analysis of WDAY after large down days, including forward return data and recovery timelines.
Is Workday (WDAY) Forming a Bottom? Pattern Data Says...
WDAY has dropped to $119. Historical chart pattern analysis shows whether Workday's current setup matches previous bottom formations.
Hut 8 (HUT) Up 17%: Breakout Pattern Analysis
Hut 8 surged 17% on heavy volume. We analyze whether Bitcoin mining stock breakouts of this magnitude tend to sustain or fade.
Hut 8 (HUT) Similar Chart Patterns: Crypto Miner Historical Analogs
Find historical chart patterns similar to Hut 8's current setup. Cross-stock pattern search includes MARA, RIOT, and other Bitcoin mining stocks.
ServiceNow (NOW) Down 7%: Technical Analysis and Pattern Data
ServiceNow dropped 7.4% today. Historical analysis of NOW after large selloffs, including recovery patterns and forward return statistics.
Is ServiceNow (NOW) a Buy-the-Dip? What Pattern History Shows
NOW at $90 after a 7% drop. Historical chart pattern data reveals whether ServiceNow dips of this size are typically buying opportunities.
How to Backtest Stock Chart Patterns: A Step-by-Step Guide Using Real Data
Learn how to backtest chart patterns against 25M+ historical embeddings. Step-by-step guide using Chart Library's API to test bull flags, breakouts, and more with real forward return data.
Bull Flag Success Rate: Updated Data From 24 Million Chart Patterns
Updated 2026 analysis of bull flag success rates across 25M+ historical chart patterns. Real win rates by timeframe, what separates winners from losers, and how bull flags compare to random entries.
How AI Agents Analyze Stocks: A Complete Guide to Chart Library's MCP Tools
Learn how AI agents like Claude and ChatGPT use MCP tools to analyze stock charts. Set up Chart Library's MCP server in 5 minutes and give your AI access to 25M+ historical chart patterns.
What NVDA Typically Does After Earnings (10 Years of Data)
A data-driven look at how NVIDIA stock has behaved after quarterly earnings reports. Base rates, average 1/5/10-day moves, and the pattern intelligence behind NVDA's post-earnings drift.
NVDA Gap Up History: Follow-Through and Fade Rates
Historical data on what happens after NVDA gaps up at the open. Win rates, average continuation, and when to fade versus chase.
NVDA Breakout Pattern: Success Rate and Average Return
How often does NVDA break out above a 20-day high and actually follow through? Historical win rates, average forward returns, and the role of volume confirmation.
NVDA Historical Volatility: What the Numbers Actually Mean
NVIDIA's typical daily range, largest single-day moves, realized volatility by year, and what it tells you about position sizing.
How NVDA Moves on Fed Days: A Decade of Data
NVIDIA's historical reaction to FOMC decisions — average moves, win rates, and how NVDA compares to SPY on rate announcement days.
What TSLA Typically Does After Earnings (10 Years of Data)
A data-driven look at how Tesla stock behaves after quarterly earnings. Win rates, average 1/5/10-day moves, and the wide distribution of post-earnings reactions.
TSLA Gap Up History: Data on Continuation vs Fade
How often Tesla gap ups follow through versus fade. Win rates by gap size, intraday patterns, and 5-day forward returns.
TSLA Breakout Pattern: Success Rate and Average Return
How often Tesla breaks out above a 20-day high and follows through. Historical win rates, average forward returns, and the effect of volume.
TSLA Historical Volatility: The Real Numbers
Tesla's realized volatility by year, typical daily range, largest historical moves, and how volatility regimes affect forward returns.
How TSLA Moves on Fed Days: A Decade of Data
Tesla's historical reaction to FOMC meetings. Win rates, average moves, and the dovish vs hawkish asymmetry for one of the most rate-sensitive mega-caps.
What AAPL Typically Does After Earnings (10 Years of Data)
Apple's post-earnings behavior across a decade. Base rates, average 1/5/10-day moves, and why AAPL reactions have become more muted over time.
AAPL Gap Up History: Follow-Through Data
How Apple stock behaves after gapping up. Win rates, intraday fade probability, and 5-day forward returns across a decade.
AAPL Breakout Pattern: Success Rate and Average Return
Apple's historical breakout follow-through data. Win rates on 20-day highs, the volume filter effect, and comparisons to other mega-caps.
AAPL Historical Volatility: What the Numbers Say
Apple's realized volatility, daily range statistics, tail event frequency, and how volatility regimes affect forward returns.
How AAPL Moves on Fed Days: A Decade of Data
Apple's historical FOMC reactions. Win rates, average moves, dovish vs hawkish asymmetry, and why AAPL is less rate-sensitive than people think.
What AMD Typically Does After Earnings (10 Years of Data)
AMD's post-earnings behavior. Base rates, average 1/5/10-day moves, and why AMD earnings reactions have grown more volatile as the company has scaled.
AMD Gap Up History: Follow-Through Data
How AMD behaves after gapping up. Win rates by gap size, intraday fade probability, and 5-day forward returns.
AMD Breakout Pattern: Success Rate and Average Return
AMD's historical breakout data. 20-day high follow-through rates, volume effect, and comparison to other semis.
AMD Historical Volatility: What the Numbers Say
AMD's realized volatility, daily range, tail events, and how volatility regimes affect forward returns.
How AMD Moves on Fed Days: A Decade of Data
AMD's historical FOMC reactions. Win rates, dovish vs hawkish asymmetry, and why semis are among the most rate-sensitive groups.
What SPY Does Around Earnings Season: A Decade of Data
SPY's behavior during earnings season. Average moves during peak weeks, base rates for earnings-season rallies, and why SPY reactions are muted but systematic.
SPY Gap Up History: Follow-Through and Fade Data
How the S&P 500 ETF behaves after gapping up. Base rates, fade probability, and what the gap-direction signal tells you about the broader market.
SPY Breakout Pattern: Success Rate and Average Return
How often SPY breaks out to 20-day highs and what happens next. Historical base rates, volume effects, and the role of market regime.
SPY Historical Volatility: The Baseline for Everything
SPY's realized volatility over a decade, typical daily range, biggest moves, and why SPY is the baseline for all other volatility comparisons.
How SPY Moves on Fed Days: A Decade of Data
SPY's historical behavior on FOMC days. Win rates, average moves, dovish vs hawkish asymmetry, and the notorious 2:30pm reversal pattern.
Pattern Similarity Search vs Traditional Technical Indicators: What's the Difference?
How does vector similarity search compare to rule-based technical indicators like RSI, MACD, and named patterns? We break down the approaches, trade-offs, and when to use each.
How to Use an MCP Server for Stock Analysis with Claude
Install Chart Library's MCP server and give Claude Desktop access to 25M+ historical chart patterns, market regime data, and forward return statistics — all through natural conversation.
What Is a Market Regime Tracker? How Chart Library Identifies Historical Market Parallels
Learn what market regimes are, how Chart Library's regime tracker finds historically similar market conditions, and how to use regime data to inform your trading decisions.
Build a Stock Research Agent with LangChain + Chart Library in 20 Minutes
A hands-on tutorial for building an AI agent that can answer natural-language questions about stock charts, market regimes, and sector rotation using LangChain and Chart Library's pattern intelligence API.
Multi-Agent Stock Research with CrewAI + Chart Library
Build a multi-agent research crew that combines chart pattern analysis with market regime intelligence using CrewAI and Chart Library's API. Two specialist agents collaborate to produce institutional-quality research briefings.
AI Stock Chart Pattern Recognition: How Vector Similarity Finds Historical Analogs
How Chart Library uses mathematical vector embeddings and similarity search to match stock chart patterns against 10 years of historical data — and why it works better than traditional pattern detection.
Double Bottom Pattern: What the Data Shows
We analyzed our database of 16 million chart patterns to measure real double bottom performance. Success rates, average returns, and what separates reliable double bottoms from traps.
Cup and Handle Pattern: Historical Success Rate
What does the data actually say about cup and handle patterns? We measured real success rates, average returns, and optimal entry timing across 16 million historical charts.
How to Read Stock Chart Patterns: A Data-Driven Guide
Learn to read stock chart patterns with data, not dogma. A comprehensive guide to the most common patterns, what the data says about each one, and how to use historical precedents instead of guesswork.
Ascending Triangle Pattern: Does It Actually Work?
We tested the ascending triangle pattern against 16 million historical charts. Real breakout success rates, failure rates, and the volume signals that actually predict outcomes.
What Happens After a Stock Breaks Out? Data from 16 Million Charts
We analyzed breakout patterns across 16 million historical charts to answer the question every trader asks: what actually happens after a stock breaks out? Success rates, follow-through data, and what separates real breakouts from traps.
How to Find Similar Chart Patterns in Seconds
A step-by-step guide to using Chart Library's visual search engine to find historically similar stock chart patterns and see what happened next.
Do Chart Patterns Actually Predict Returns? What the Data Says
We analyzed millions of historical chart patterns to answer the age-old question: do chart patterns have predictive power? Here's what the data shows.
Bull Flag Pattern: What 16 Million Charts Tell Us
We analyzed millions of chart embeddings to measure real bull flag performance. Average returns, win rates, and how to spot the setups that actually work.
Stock Breakout Patterns in 2025: Lessons from the Data
What worked and what didn't in stock breakout patterns during 2025. Data-driven analysis of breakout success rates, failed breakouts, and key takeaways.
Head and Shoulders Pattern: Does It Actually Work?
We measured the real performance of head and shoulders patterns across thousands of stocks. Win rates, average returns, and what separates reliable signals from noise.
Stock Chart Analysis: A Data-Driven Guide for Beginners
Learn the fundamentals of stock chart analysis with a modern, data-driven approach. No guesswork — just patterns, statistics, and what the historical record actually shows.
Chart Pattern Scanners Compared: How Chart Library Is Different
A comparison of chart pattern scanning tools — TradingView, TrendSpider, Finviz — and how Chart Library's embedding-based approach differs from rule-based pattern detection.