Massive

Earnings aren't coin flips. @earnings_watch built a platform to prove it, on Massive data and 1,000+ options traders use it daily. Here are the Massive products they use: → Options Contracts + snapshots power the earnings simulator and VolScanner → Fair Market Value cleans up the rankings → Stocks Aggregates drive post-earnings drift analysis One API pattern across every tool. No mismatched data between screening, simulating, and analyzing. Read more in the case study. massive.com/blog/case-stud…

😲🤯Another day another model release. Just tested GPT-5.6 Sol on the new @massive_com Remote MCP Server with this monster query… Using the massive (pun intended) Massive data, it analyzed the latest FOMC rate decision’s impact on QQQ + options: - 1-min QQQ bars from 30 min before the statement to 90 min after the press conference - One liquid 25-45 DTE expiration - ATM call/put + ~5% OTM call/put - Price & volume reaction, bid-ask spreads, IV changes, downside skew, gamma exposure - Statement vs press conference: which one actually moved the market more? - Plus the exact graphs requested No code. No manual data pulls. Just one prompt → full professional-grade event study in seconds complete with a graph. 📈📊

Woah 🤯 I connected @SpaceXAI's Grok 4.5 to @massive_com using their new remote MCP server - asked it to analyze @Tesla performance and create a powerpoint with the results. Did it all in under two minutes. Pretty blown away by this. This is just the tip of iceberg too. I haven't even tried my hard queries yet.

You can find the Massive Market Data Claude connector here: claude.ai/directory/conn… Click install, add your api key, and give Claude permission. That's all you have to do to give Claude access to real time market data across Massive's MASSIVE data portfolio. 📈📊

Without accurate stock market data, Claude guesses or makes data up. That is where Massive comes in. Here Claude Sonnet 5 is querying major memory stocks over the last year. It correctly uses the Massive Market Data connector, builds a chart and provides an easy to read overview of everything related to the historic run up. All it took was a quick install and simple prompt. Connect Claude to the market now.

Checkout this LULD monitor if you need real-time awareness of volatility guardrails across U.S. equities. This example connects to Massive's stock WebSocket feed and subscribes to LULD events. It shows upper and lower price bands, indicator codes, tape, timestamps, and sequence numbers, then turns the raw feed into a monitor that is easier to read under market pressure. The practical pattern is selective and high signal: show routine band updates for a watchlist, while surfacing halt and resumption indicators across the market. Indicators 17 and 18 are available for Nasdaq-listed securities, so the copy and example keep that scope explicit. massive.com/blog/luld-mass…

@marcusjihansson It is on our roadmap to create. It does look like someone has made one before - github.com/kezzlock/massi…

@massive_com Hi @massive_com , I am writing a Rust sdk for your api. As there were non as far as I could see. Is there a chance I could get an API key so I could test every endpoint? I just want to make sure everything works! Would be greatly appreciated!

The very first tick of $SPCX. 58,206,084 shares for $150 at 11:46:45.910 ET on Nasdaq. Conditions: Cross, Market Center Opening Trade, and Trade-thru Exempt. Captured straight from the tape.

Request URL: api.massive.com/v3/trades/SPCX…

@humblebillionz @PT_Trader1 @MartinShkreli x.com/massive_com/st…

@massive_com @PT_Trader1 @MartinShkreli Can you sling something my way?

This is every stock and every market. Oldest arbitrage there is!

@TSLAshareholder @PT_Trader1 @MartinShkreli x.com/massive_com/st…

@massive_com @PT_Trader1 @MartinShkreli Hook me up!

@hirschibar @PT_Trader1 @MartinShkreli Jk what data are you interested in?

@hirschibar @PT_Trader1 @MartinShkreli Hey, we’re not a charity

@PT_Trader1 @MartinShkreli Dm me your account and I’ll sling some data your way

@MartinShkreli Claude with a @massive_com connector. I only pay for 2 years data buy if Massive wants to hook me up with an upgraded subscription, i'll run the test

The $25,000 day-trading minimum is gone. As of today, June 4, FINRA's Rule 4210 amendment retires the Pattern Day Trader rule and its $25,000 minimum. So we measured what that barrier actually cost. Using 5-minute bars for every S&P 500 ticker across every May session, we scanned for each 2%+ intraday round trip a day trader could have caught. Our analysis flagged 4,679 potential trade opportunities. Under the old rule, a PDT-restricted trader could have only taken 12 of them, about .3% of the total. Now that the limit is gone, we may see much broader market participation. Dig into the relevant OHLCV data using our aggregates endpoint: massive.com/docs/rest/stoc…

@SteveDJacobs @investfromdata Thanks for the callout Steve!

@investfromdata The data is provided by @massive_com, which is processed through a series of custom Python algorithms and then visualized in a web-based, interactive UI.

📈How over-extended are S&P500 stocks? One popular metric to determine if a stock is over-extended is to measure the distance of the stock price from the SMA50. Below is a mapping of $SPY stocks to their ATR-to-SMA50 extension. Font colors: 🟢 Buyable 🟠 Trend inflection point upward 🟡 Restore full position if trimmed 🔵 Reduce position 50% 🔴 Sell 100%

After 45 Days, 70+ traders, and $100K paper portfolio each, the winner of Clawstreet Season One is LIRA! ICYMI: a couple of months ago we partnered with @clawstreethq to run an industry leading agentic trading competition where traders used paper money in hopes to win the ultimate prize of a Mac Mini. 💻 You can find out more on how LIRA won in the Clawstreet blog. clawstreet.io/contest/results

S&P 500 Top 10 Movers for week ending May 29th, 2026. Top Gainers @Dell Technologies led the pack at +43% after reporting Q1 FY2027 results with 88% revenue growth to $43.84B, 214% EPS growth to $4.86, $24.4B in new AI server orders, and a $51.3B backlog, prompting management to raise full-year guidance to $165-169B. @Supermicro followed at +30% on halo from Dell's results and its own announcement of a new Taiwan government partnership to combat illegal diversion of its AI server hardware. @MicronTech added +29% after UBS raised its price target to $1,625, citing a structural shift in high-bandwidth memory demand and validating the company's sold-out HBM supply through 2026. @RobinhoodApp gained +28% on growing investor excitement ahead of the SpaceX IPO scheduled for June 12, with Robinhood selected as a primary retail distribution platform offering access to users with no minimum balance requirement. @AppLovin rounded out the top five at +27% after an Edgewater analyst note removed competitive overhang ahead of the AXON AI advertising platform launch, with the move extended by macro tailwinds from falling oil prices. Top Losers @bostonsci led decliners at -16% after management cut full-year organic growth guidance to 6.5%-8% at a Bernstein conference on May 27, triggering an 11.7% single-day drop and a wave of analyst downgrades and price target cuts from Wells Fargo, Wolfe Research, and Citigroup. @autozone dropped -14% after reporting fiscal Q3 results that missed revenue expectations at $4.84B versus the ~$4.88B estimate, with domestic same-store sales of 4.1% against the 4.7% consensus, prompting multiple analysts to slash price targets. Rollins fell -11% after announcing CFO Kenneth Krause's resignation on May 27, followed by a Bernstein downgrade from Outperform to Market Perform with a price target cut from $70 to $52. @ONEOK dropped -11% alongside the broader energy sector as oil prices fell on Iran nuclear deal optimism and OPEC production increase speculation, compressing midstream multiples across the board. @Lumentum rounded out the losers at -10%, pulling back on profit-taking after surging 169% year-to-date through mid-May, with no specific catalyst as investors rotated out of high-multiple AI-infrastructure names. All data was pulled using Massive's aggregates API. Music: Sydney's Skyline by ALBIS (CC BY)

@Whats_Up_Rob 💯 great example of how Massive is a platform built for developers by developers. 💻

@massive_com One API across asset classes is the part that matters. Curious to see what people build with it.

Massive Futures are now generally available. Until today, adding futures to a cross-asset trading system meant a second API provider, a second auth pattern, and a second response schema to normalize into your data pipeline. Futures data includes over 1500 products across CME, CBOT, COMEX, and NYMEX.

Futures data has been a complicated path for indie builders for a long time. @massive_com just shipped ES, GC, CL on the same REST API as equities and options. Changes what one person can build solo. Combine with other APIs and build something cool. massive.com/blog/futures-d…