For Investors & Quant Researchers · Investment Banking Brokerage
Investment Banking & Brokerage Data for Investors & Quant Researchers
Investment Banking Brokerage data for investors: 13 datasets on one shelf. Every one delivered as API, files, or warehouse rows.
best alternative data sources for investing · satellite imagery data for hedge funds · point-in-time fundamentals database · how do quants use investment banking brokerage data
API, files, or your warehouse. Daily, weekly, or hourly.
Which investment banking & brokerage datasets should investors and quant researchers pull first?
Ranking runs on signal value rather than brand familiarity: the 7 datasets scored relevance 3 lead, the 4 at relevance 2 follow and the 2 scored relevance 1 close, ordered inside each band by quality score and refresh speed.
How do quants actually use investment banking & brokerage data?
Curve and funding work comes first. U.S. Treasury Interest Rate Data discounts cash flows off the official tenor-by-tenor daily series, and the Federal Reserve Bank of New York Markets Datasets add repo, SOMA and primary-dealer history with inception dates, so funding-stress factors can be built on full samples rather than trimmed windows. BIS Total Credit & Debt Securities Statistics backs the leverage side with quarterly series reaching back to 1940-Q2.
Microstructure and positioning follow: the FINRA API Developer Center serves bond-trade prints, OTC volumes and short interest, MSRB EMMA carries official statements, continuing disclosures and trade activity as the SEC-designated primary municipal source, and WhaleWisdom tracks hedge-fund 13F position changes quarter over quarter for crowding screens.
Two evidence-first caveats. None of these records documents vintages or revision history, so treat every pull as restated history rather than first-print data. And this slice's only static record - Kaggle NYSE S&P 500 Historical Prices & Fundamentals - stops at its 2016 cutoff, which disqualifies it from anything live.
How fresh is each source, and does cadence limit the signal?
That is 46% of the slice at daily cadence against 22.6% daily and 27.8% weekly-plus across the full catalog.
Frequency and signal largely align: Treasury's daily curve is the slice's only quality-10 record, and the New York Fed and FINRA both publish daily at quality 9. The slow records are slow by design - 13F holdings exist only quarterly, IPO and fact-book statistics compile annually - so run event-driven work off the daily prints and structural work off the annual drops.
Does this slice include satellite imagery or card-panel signals?
No. Nothing here observes parking lots, tanker counts, store traffic or card spend - these records measure rates, trades, filings and disclosures. The nearest activity proxies are market-shaped rather than physical: FINRA's OTC volumes and short interest, MSRB EMMA's municipal trade activity and WhaleWisdom's quarter-over-quarter 13F repositioning. None prices a dealer intraday. The gap is structural: 781 of the 1,744 datasets Datadory catalogs (44.8%) are public data, and regulators and central banks set this industry's reporting rhythm.
Straight answers
What are the best alternative data sources for investing in investment banking & brokerage?
For signal value: Treasury's tenor-by-tenor daily yield curve, the New York Fed's repo, SOMA and primary-dealer series, FINRA's bond-trade prints and short interest, BIS credit statistics back to 1940-Q2 and MSRB EMMA's municipal disclosures. Those lead the 7 relevance-3 records, and mean quality across all 13 is 8.2 of 10.
Where can hedge funds get satellite imagery data on investment banks and brokers?
Not in this slice - it holds no satellite, card-panel or transaction-tape feed. Closest substitutes are market-shaped: FINRA's OTC volumes and short interest, MSRB EMMA's municipal trade activity and WhaleWisdom's 13F crowding screens, none of which photographs a parking lot. Public sources dominate: 44.8% of the 1,744-dataset catalog is public data.
Can I build a point-in-time fundamentals database from these sources?
None documents vintages, so nothing here qualifies as point-in-time. BIS Total Credit & Debt Securities Statistics is the closest structural analogue: quarterly credit and debt-securities series back to 1940-Q2, deep enough to rebuild history but published as revised levels. Archive pulls with timestamps and size trades off release calendars, not first prints.
How do quants use investment banking & brokerage data?
Four working patterns: discounting and curve-regime tagging off Treasury's daily tenors, funding-stress factors off New York Fed repo and primary-dealer series, microstructure research off FINRA prints and short interest, and crowding screens off WhaleWisdom's quarterly 13F deltas. Jay Ritter's IPO tables add 55-country issuance benchmarks.
Rows before rollout
Sample rows from any shelf entry — the field dictionary and coverage notes ride along. If the shelf misses what you need, say so; sourcing requests are half our job.
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