Alphanume (@alphanume_data)

Article · @alphanume_data

@alphanume_dataAug 30

Monetizing The Golden Age of Short Selling

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Alphanume · Oct 29, 2026 · 1:01 PM UTC

@alphanume_data12s

5,597 us tickers carried a market cap on oct 26. 1,229 of them are worth under $50M. 36.7% sit under $250M. 63.9% sit under $2B. the listed market is mostly companies no index holds. the panel prices every one of them daily.

Dark data card. Headline 36.7 percent: the share of 5,597 US tickers carrying a market cap under $250M on Oct 26. 1,229 of them sit under $50M and 63.9 percent under $2B. Source api.alphanume.com/v1/historical-market-cap.

ALT Dark data card. Headline 36.7 percent: the share of 5,597 US tickers carrying a market cap under $250M on Oct 26. 1,229 of them sit under $50M and 63.9 percent under $2B. Source api.alphanume.com/v1/historical-market-cap.

Alphanume · Oct 29, 2026 · 10:00 AM UTC

@alphanume_data3h

the straddle said UNH would move 4.08%. it moved 22.38%. worst miss in 3,942 scored earnings events. 44 of them underpriced the move by 3x or more. implied, realized and the ratio all ship in the row. go pull it.

Alphanume · Oct 29, 2026 · 7:00 AM UTC

@alphanume_data6h

ask your agent "does alphanume have market cap history for this ticker" -> list_market_cap_tickers -> 9,433 tickers, each with its first available date -> one call, no scraping the catch it just made: 854 of them only start in 2026. a 2019 backtest on those returns nothing.

Dark composed exchange card. The question 'does alphanume have market cap history for this ticker' runs list_market_cap_tickers and returns a ticker and first_available_date table: AETR 2026-10-27, PTIV 2026-10-27, LYCA 2026-10-26, WATR 2026-10-26. Footer: 9,433 tickers, 854 of them only start in 2026.

ALT Dark composed exchange card. The question 'does alphanume have market cap history for this ticker' runs list_market_cap_tickers and returns a ticker and first_available_date table: AETR 2026-10-27, PTIV 2026-10-27, LYCA 2026-10-26, WATR 2026-10-26. Footer: 9,433 tickers, 854 of them only start in 2026.

Alphanume · Oct 29, 2026 · 4:00 AM UTC

@alphanume_data9h

monthly payers recover the ex-dividend drop by the next close 55% of the time. quarterly payers: 52%. weekly payers: 53%. 97,037 scored events, seven payout-frequency buckets, whole spread 47% to 55%. how often a company pays says nothing about whether the drop comes back.

Dark data card. Headline 55 percent: the share of monthly payers whose ex-dividend drop is recovered by the next close. Quarterly 52 percent, weekly 53 percent, across 97,037 scored events in seven frequency buckets, spread 47 to 55 percent. Source api.alphanume.com/v1/dividend-capture.

ALT Dark data card. Headline 55 percent: the share of monthly payers whose ex-dividend drop is recovered by the next close. Quarterly 52 percent, weekly 53 percent, across 97,037 scored events in seven frequency buckets, spread 47 to 55 percent. Source api.alphanume.com/v1/dividend-capture.

Alphanume · Oct 29, 2026 · 1:00 AM UTC

@alphanume_data12h

the same one-day spx band has been 0.74% of the index and 9.73% of the index. 0.74% was dec 9 2024. 9.73% was apr 7 2025. 13x the width, same product, same 5-point strike grid. 706 daily rows of it, one per session. every one is PUBLIC.

Alphanume · Oct 28, 2026 · 10:00 PM UTC

@alphanume_data15h

10 state changes. the entire 2025 history of the s&p risk regime flag. 250 sessions, one binary column a day: -> longest run: 110 sessions, may 12 to october 16 -> median run: 10 -> shortest: 1 44% of the year sat inside that one stretch.

data card: the s&p risk regime flag changed state 10 times across 250 sessions of calendar 2025, with one unbroken run of 110 sessions from may 12 to october 16

ALT data card: the s&p risk regime flag changed state 10 times across 250 sessions of calendar 2025, with one unbroken run of 110 sessions from may 12 to october 16

Alphanume · Oct 28, 2026 · 7:01 PM UTC

@alphanume_data18h

the momentum index publishes 10 names. the cross-section behind it, september 1 2026: 519. every optionable name scored and ranked. beta, sharpe, vol, liquidity, sector. 12 columns. this is PUBLIC. filter the whole field server-side. 11 sectors to group by.

Dark terminal card: a curl call to the expanded momentum endpoint returning one row for SNDK on 2026-09-01, technology sector, beta 4.31, sharpe 23.70, rank 1, with a footer noting 12 columns per row and a september 1 2026 field of 519 names across 11 sectors.

ALT Dark terminal card: a curl call to the expanded momentum endpoint returning one row for SNDK on 2026-09-01, technology sector, beta 4.31, sharpe 23.70, rank 1, with a footer noting 12 columns per row and a september 1 2026 field of 519 names across 11 sectors.

Alphanume · Oct 28, 2026 · 4:02 PM UTC

@alphanume_data20h

ask your agent "what did the model's five picks for september 18 2026 actually do" -> get_next_day_movers -> one row per pick: ticker, return, absolute move -> backfilled after the close asked september 24: AXTI 14.18, CIFR 3.10, PURR -3.85, RZLV 1.10, SLS -1.04

Dark composed exchange: asking an agent what the model's five next-day picks for september 18 2026 actually did runs get_next_day_movers and returns AXTI at 14.18, CIFR at 3.10, PURR at -3.85, RZLV at 1.10 and SLS at -1.04, with the absolute move beside each return.

ALT Dark composed exchange: asking an agent what the model's five next-day picks for september 18 2026 actually did runs get_next_day_movers and returns AXTI at 14.18, CIFR at 3.10, PURR at -3.85, RZLV at 1.10 and SLS at -1.04, with the absolute move beside each return.

Alphanume · Oct 28, 2026 · 1:02 PM UTC

@alphanume_data23h

121,068 vol-of-vol readings across 599 optionable names, full-year 2025. only 250 showed a name's implied vol swinging as hard as its own level. -> all 250 came from 18 tickers -> 514 of 599 never got halfway -> median reading: 0.14 peak: ACI, january 16 that year, 1.4

Data card: 250 in large type, the vol-of-vol readings in full-year 2025 where a name's implied vol swung as hard as its own level, out of 121,068 readings across 599 names, from just 18 tickers, with 514 of 599 never getting halfway.

ALT Data card: 250 in large type, the vol-of-vol readings in full-year 2025 where a name's implied vol swung as hard as its own level, out of 121,068 readings across 599 names, from just 18 tickers, with 514 of 599 never getting halfway.

Alphanume · Oct 28, 2026 · 10:00 AM UTC

every completed SPAC merger since january 2021 read out of the super 8-K and the proxy trail into one structured row redemptions, trust remaining, PIPE, sponsor. the numbers nobody else bothers to structure the graveyard has a schema this is PUBLIC

Terminal card: curl api.alphanume.com/v1/de-spac-events returns one completed de-SPAC record for FAC with 23,051,313 shares redeemed, 11,200,000 of trust remaining and a 100,900,000 PIPE.

ALT Terminal card: curl api.alphanume.com/v1/de-spac-events returns one completed de-SPAC record for FAC with 23,051,313 shares redeemed, 11,200,000 of trust remaining and a 100,900,000 PIPE.

Alphanume · Oct 28, 2026 · 7:00 AM UTC

ask your agent "is AAPL's implied vol expensive next to its own year" -> get_iv_rank -> the 52-week high, low and median ride the row with the reading asked september 3 2026: AAPL iv rank 43, sitting at 20% inside a 52-week range of 14% to 28%.

composed exchange: asking whether AAPL's implied vol is expensive next to its own year returns iv rank 43 with the 52-week range 0.14 to 0.28 around a 0.20 reading

ALT composed exchange: asking whether AAPL's implied vol is expensive next to its own year returns iv rank 43 with the 52-week range 0.14 to 0.28 around a 0.20 reading

Alphanume · Oct 28, 2026 · 4:00 AM UTC

86 Item 2.04 corporate default records in full-year 2025, machine-read off EDGAR into 15 columns. 76 of them carry the verbatim sentence they were read from. all 86 carry the filing link and a confidence score. the extraction shows its work. that is the whole methodology.

data card: 76 of the 86 Item 2.04 corporate default records from full-year 2025 carry the verbatim sentence they were read from, and all 86 carry the filing link

ALT data card: 76 of the 86 Item 2.04 corporate default records from full-year 2025 carry the verbatim sentence they were read from, and all 86 carry the filing link

Alphanume · Oct 28, 2026 · 1:00 AM UTC

the sector map is a closed vocabulary. 11 sectors, 25 industries, both validated server-side: send a value that isn't on the list and the endpoint hands you the whole list back. no date column, so nothing to clamp. it's FREE.

Dark terminal card: a GET /v1/ticker-classification call with an invalid sector returning INVALID_SECTOR and the whole valid_values list, over a footer reading sectors 11, industries 25, date columns 0.

ALT Dark terminal card: a GET /v1/ticker-classification call with an invalid sector returning INVALID_SECTOR and the whole valid_values list, over a footer reading sectors 11, industries 25, date columns 0.

Alphanume · Oct 27, 2026 · 10:00 PM UTC

550 S-1 stock offerings hit EDGAR in 2025. 462 went effective median time from filing to effectiveness: 13 days that is the median runway between the paperwork and the share flood. calendar 2025, every filing in the dataset

ALT Data card: the median 2025 S-1 went from filing to effectiveness in 13 days; 550 filings, 462 effective.

Alphanume · Oct 27, 2026 · 7:01 PM UTC

every US ex-dividend event, resolved. declaration through pay date. the cum-day close, the ex-day drop, the ratio between them. then whether the stock got back to breakeven in 1, 3, 5, 10 or 20 sessions. 32 columns. the forward calendar ships in the same file. this is PUBLIC

Terminal card: the dividend-capture endpoint called with upcoming=true and future_days=120, listing the columns date, cum_close, drop_ratio_close and recovered_within_5d with plain-English descriptions.

ALT Terminal card: the dividend-capture endpoint called with upcoming=true and future_days=120, listing the columns date, cum_close, drop_ratio_close and recovered_within_5d with plain-English descriptions.

Ethan Kho · Oct 27, 2026 · 12:43 PM UTC

Alphanume retweeted

Ethan Kho

@ethanrkhoOct 27

$480M Hedge Fund Manager David Orr (@orrdavid) on why big firms underallocate to their best PMs: "In a single year I'm getting more reps than a lot of hedge fund managers get in a decade." "What you're looking for in a portfolio manager, there's just a guy who consistently wins. And these people are out there. You just have to go find them." "But what the bigger firms seem to do is just still give them only a small allocation." "One of the guys, he's short only, and he's won 40% a year short only for years now. I mean, the guy's a killer." "Somehow he gets a tiny allocation at the fund he's at. If you do that at my fund, man, we're gonna give you a lot of money." "The thing is, I heard it doesn't scale super well, so maybe that's why they don't upsize him."

Ethan Kho

@ethanrkhoOct 23

Hedge Fund Manager David Orr (@orrdavid) on why he’ll back a delivery guy over a Harvard grad, as long as the track record is real. David Orr runs Militia Capital, a ~$480M hedge fund. ~50% annualized, Sharpe 2. “If you didn’t go to Harvard, they’re not going to give you money. They’re gonna lead you on for years.” We cover: - Edge is just reps. He's placed a few hundred independent bets every year since 2019, more in one year than a lot of hedge fund managers get in a decade. - The two-hour rule: if he can't decide on a stock in an hour or two, he skips it. When a trade goes against him, he quits. "The market said I'm wrong, I'm wrong." - 500 positions in his partition and zero notes. Some of his best shorts are down 40% and he's forgotten what the company does. - The Gogo lesson: he spent 100 hours on a short and was right on the fundamentals (it's now $2), but it ripped to $20 first. All that research made him stubborn on the way up. - The AI risk system: it groups the book into custom baskets like "Banks Done Right" and "yield traps," recalculated daily. A 25% bet can quietly become 45% in two weeks. - How Militia recruits PMs: 95% of track records are junk, and one cherry-picker ran 30 accounts and sent the best one. The PMs who make it include a game show winner, a Spanish government worker and a programmer, with 0.15 cross-correlation. - The best short seller in the world, quietly: 40% a year short only for years, and he still gets a tiny allocation at his fund. - Why multi-managers' real business is marketing. Collect $2B a year in fees on $100B and it's "mission accomplished," whatever the returns. - The long/short tax trick: harvest losses on losing shorts, and never cover one that's down 90%. No tax is due until it's delisted, which can take 10 years. - $150M raised from one email asking LPs for $100M. He says he could raise a billion but won't, and admits they "must have gotten at least somewhat lucky." - His AI stock map: hyperscalers locked customers into take-or-pay deals at ~35% return on capital. If compute prices crash 80%, the end customers get wiped out, not the hyperscalers. - Is investing 99% talent? For big alpha, almost entirely. Pod shop alpha is teachable, maybe for 1 in 50 people rather than 1 in 10,000. Highlights: 00:00 Intro 00:44 How AI custom factor baskets track dynamic correlation in levered portfolios 03:24 Sourcing non-consensus PM talent and verifying live Sharpe track records 07:24 Structuring carry and tax deferral to attract elite proprietary traders 12:50 Why institutional multi-manager platforms fail to back pure alpha 20:22 The two-hour research limit: Avoiding sunk-cost bias in short selling 27:58 Momentum screening vs deep value: Why top longs hit new highs 29:40 Why traditional finance books fail and what operator biographies teach 37:16 Why rapid technological adaptation beats traditional economic moats 39:26 Analyzing the AI trade: Why hyperscalers offer superior downside protection 44:57 Internalizing stock borrow desks to maximize net-of-fee fund compounding 55:25 Avoiding confirmation bias and why shorting revenue growth fails 01:01:42 Pod shop leverage factories vs raw discretionary alpha generation 01:07:12 Unplugging from market narrative feeds to preserve independent conviction

11,141

Alphanume · Oct 27, 2026 · 4:02 PM UTC

your agent can answer "which stocks are getting unusual wikipedia attention" in one call -> get_wikipedia_views, one z-score filter -> the 2026-08-11 pull: 18 names above z=3, the loudest 8.6 sigma over its own average the question is the whole interface

Composed agent exchange: asking which stocks are getting unusual wikipedia attention runs get_wikipedia_views and returns ONON, PFE and HSY with views, 30-day averages and z-scores from 2026-08-11.

ALT Composed agent exchange: asking which stocks are getting unusual wikipedia attention runs get_wikipedia_views and returns ONON, PFE and HSY with views, 30-day averages and z-scores from 2026-08-11.

Alphanume · Oct 27, 2026 · 1:02 PM UTC

most expected-move models want a vol surface, a term structure, and a prayer the SPX 0-DTE band wants one number the market already priced the day. the band just reads it back out

ALT Data card: the SPX 0-DTE expected-move band needs one input; no vol surface, no term structure.

Alphanume · Oct 27, 2026 · 10:00 AM UTC

every us ticker's market cap, stamped on the session that made it. four columns: date, ticker, market_cap, shares_outstanding. the panel opens 2015-09-30, 3,513 names on day one. ask for one ticker, get its whole history. this is PUBLIC

Dark terminal card: a curl to /v1/historical-market-cap for AAPL returning one row with date, ticker, market_cap and shares_outstanding. Footer: four columns, one row per ticker per session, coverage opens 2015-09-30.

ALT Dark terminal card: a curl to /v1/historical-market-cap for AAPL returning one row with date, ticker, market_cap and shares_outstanding. Footer: four columns, one row per ticker per session, coverage opens 2015-09-30.

Alphanume · Oct 27, 2026 · 7:00 AM UTC