Specs were already net short the Nasdaq at a 1-year extreme before Tuesday's crash.

Found this digging around in the COT data. Going into Tuesday (KOSPI −9.99%, MU −13%, SK Hynix −12.5%) the big speculators were already net short Nasdaq futures at the 5th percentile of the past year. They'd been short for like two months while the index kept making highs.

Funny part: the same crowd was also net short VIX, basically betting on calm. So they got the direction right and the vol completely wrong. Short the index and short the insurance at the same time.

Insiders were trimming too. NVDA had 5 insiders sell $40M on a single day (6/17), including Huang and the CFO, though that's probably just a scheduled 10b5-1 thing.

Anyway the move wasn't even a Micron miss, MU reported the next day. It was the Korea selloff plus the Fed flipping to a hike signal on the 17th.

kresmion.com
u/_SG9 — 12 days ago
▲ 2 r/Polymarket_Traders+1 crossposts

Released about 47 days of Polymarket crypto Up/Down binary market data on Hugging Face

I built a Polymarket arbitrage bot earlier this year and it was collecting orderbook and market snapshot data on the BTC/ETH/SOL/XRP Up/Down binary markets. Shut the bot down recently to rework it and figured the historical data could be useful to others. Also doubles as marketing for a platform im building ahhaha

What's in it:

- 4 assets: BTC, ETH, SOL, XRP

- 4 timeframes: 5m, 15m, 1h, 1d (1h and 1d are BTC-only since Polymarket doesn't run those for the other three)

- 60-second polling cadence

- Per asset/timeframe: snapshots file (top-of-book, implied probability, market metadata, volume, liquidity) + orderbook file (5 levels each side with cumulative depth)

- Parquet format, loads in one line via pandas or the Hugging Face datasets library

Time period covers roughly 2 months with some collection gaps documented in the README. Worth knowing about the gaps before building anything serious on this they're not huge but they're there.

Data was pulled from Polymarket's two public APIs (Gamma for metadata/volume, CLOB for live orderbook). No auth required, standard rate limits respected.

Released under CC-BY-4.0. The README has the full schema, methodology, known limitations, and a few suggested analyses if anyone wants ideas for what to do with it.

Link: huggingface.co/datasets/Solal9/polymarket-crypto-updown-binary

u/_SG9 — 1 month ago

Premier Air Charter (PREM) discloses going-concern doubt in 10-Q $288K cash, $3.85M debt, while jet fuel costs rising

Premier Air Charter Holdings filed a 10-Q on May 15 with going-concern language. The filing states substantial doubt about the company's ability to continue operating, citing global economic conditions and market volatility.

The balance sheet:

- Revenue: $7.2M

- Gross profit: $537K

- Accounts receivable: $3.5M

- Cash: $288K

- Debt: $3.85M

Cash position is 7.5% of total debt and roughly equal to one month of operating expenses. The accounts receivable to cash ratio (12x) suggests collections are stretched.

The interesting context is the operating environment. PREM is a charter aviation operator. Jet fuel is their largest input cost and tracks crude. Crude was up roughly 10% over the past week on Hormuz tension and rejected diplomacy with Iran. A microcap aviation company already running on $288K of cash facing rising fuel costs is the kind of setup where the macro tail matters more than usual.

The framing of the going-concern is also worth noting. They're attributing it to "global economic conditions and market volatility" rather than company-specific issues like covenant breaches or customer concentration. That's unusual language for a microcap and reads more like setup for a restructuring narrative than an operational fix.

Caught this on kresmion.com . The platform scans 10-Q filings as they hit EDGAR and flags "substantial doubt" appearing within 100 characters of "going concern" with confidence scoring. Saves manually scanning new filings.

Filing reference: SEC EDGAR accession 0001683168-26-004025, PREM 10-Q dated 2026-05-15. Anyone can pull the underlying document and verify.

Not a recommendation. Going-concern doesn't mean bankruptcy is imminent companies often resolve through capital raises, debt refinancing, or business pivots. But the next 8-K is worth watching for credit facility news, and the next 10-K (early 2027) will tell you whether the doubt was resolved or reaffirmed.

reddit.com
u/_SG9 — 2 months ago
▲ 2 r/CryptoMarkets+1 crossposts

Solo founder. Building for a few months with claude.

It's not a signals platform the site surfaces events with context and historical comparables and lets you decide what to do with them.

What it actually does:

- 47 Telegram channels + web scrapers feed an OSINT layer that clusters related events by entity and region, with one-line summaries. Non-English content translates to English on ingest, original revealable per event.

- Compound signal detector fires when OSINT + COT + price action converge on the same thesis. Cross-source agreement is the bar, not a single indicator.

- 13F filings group by filer-quarter (Bridgewater's 17 Q1 position changes show as one card with direction summary, not 17 rows). Berkshire's actual book size verified against public 13F data.

- Bond issuance, insider trades, ETF flows, congressional trades, whale wallet movements, funding rates, COT extremes all in one place with source attribution on every event.

- Methodology page documents every formula and what's rule-based vs LLM. LLM is prose only translations, cluster summaries. Classification and scoring are deterministic Python.

What it doesn't do yet:

- Mobile UX is rough

- Track record dashboard exists but needs more days of price history accumulating to be useful

Free signup, no card. Built for pro traders, not retail hype. I lurk on this sub so roast it honestly in the comments that's how I find what to fix next.

kresmion.com

reddit.com
u/_SG9 — 2 months ago
▲ 330 r/stocks

Berkshire just tripled its GOOGL stake and bought Delta again

Three moves stood out in Berkshire's Q1 13F, but the story is the rotation between two of them:

GOOGL: position more than tripled, from 17.8M shares to 54.2M. Roughly $5.6B → $15.6B. About $10B of fresh capital deployed in a single quarter.

CVX: cut from 130.2M shares to 84.4M, down 35%. Still a large $17.5B position but the trim is meaningful this is the same quarter they tripled GOOGL.

DAL: Delta added back as a new position, 39.8M shares (~$2.65B). Notable because Berkshire fully exited airlines in 2020 after the COVID-era impairment.

Reading these together: capital rotating from legacy energy into mega-cap tech. This is also the first full year of the post Buffett CEO era under Greg Abel, with Weschler and Combs handling more of the equity allocation. A $10B GOOGL build in one quarter is a bigger statement coming from them than it would have been as a Buffett move.

The DAL re-entry is the headline a lot of outlets will run with, but it's a smaller position. The real signal is the energy-to-tech rotation.

Question for the sub: does this rotation signal a meaningful shift in Berkshire's allocation philosophy under Abel/Weschler/Combs, or is it just normal portfolio drift now that Buffett isn't actively steering?

(Caught this on kresmion com it groups 13Fs by filer-quarter instead of line-by-line. Free.)

reddit.com
u/_SG9 — 2 months ago
▲ 15 r/tradingmillionaires+4 crossposts

I Got Tired of Institutional Trading Tools Being Too Expensive, So I Built My Own

I’ve been building the trading intelligence platform I always wanted: cross-asset signals, macro regime tracking, whale transactions, congressional trades, COT positioning, and analysis tools in one place.
Most of the data serious traders need is locked behind expensive institutional subscriptions, so I built my own version for retail traders.

Kresmion gives you:

Market intelligence feed — OSINT, SEC filings, insider trades, congressional trades, whale transactions, ETF flows, activist investors, FDA approvals, bond issuances, and COT extremes in one unified feed.

Macro regime engine — a daily risk-on/risk-off score built from yield curves, real yields, credit spreads, DXY, AUD/JPY, copper/gold, SPX momentum, VIX, MOVE, and economic surprise data.

Whale + institutional tracking — BTC/ETH/SOL large transactions, exchange wallet flows, ETF inflows/outflows, 13F holdings, and other capital flow signals.

Trading tools — position sizing, correlation matrix, drawdown tracker, relative strength heatmap, sector rotation, currency strength, yield curve animator, COT dashboard, screener, and signal accuracy tracking.

Portfolio + alerts — encrypted portfolio tracking, stress testing, watchlist-based signal alerts, price alerts, and HMAC-signed webhooks for quant workflows.
Every intelligence event is classified by direction, severity, confidence, market context, and what to watch next.
It’s free right now while I build it out. No credit card required.

kresmion.com

What data or signals do you find hardest to access as a retail trader?

u/Toptieruser123 — 2 months ago