Credit data from the big terminals is licensed and can't be shown or shared. Palanor builds the same picture from sources that are public by law or licensed for reuse, and says where each number comes from.
New bond deals, from the filings
When a company sells bonds publicly in the U.S., it files a pricing term sheet with the SEC. Palanor reads every one it can find with EDGAR full-text search, splits it into tranches and records the amount, coupon, maturity, price, yield, spread to Treasuries and ratings. Each tranche is checked by adding the spread to the benchmark Treasury yield and comparing the result with the yield printed on the sheet.
From those tranches come weekly investment-grade issuance, the median spread new borrowers pay (by week, by rating band and by sector), and the borrowing of the five biggest cloud and AI spenders: Microsoft, Alphabet, Amazon, Meta and Oracle.
Deals sold under Rule 144A (most high-yield bonds, many foreign issuers and private placements) file no term sheet, so they are missing. The high-yield series counts only SEC-registered deals and says so.
Distance to default
For each non-financial S&P 500 company, plus CoreWeave, Palanor computes a Merton distance to default every trading day: how many standard deviations the company's asset value sits above the point where it could not cover its debt. It uses the company's share price and volatility over the last year, the debt on its latest 10-Q or 10-K (short-term debt plus half of long-term debt, finance leases included) and the 1-year Treasury yield.
- The S&P 500 median, the distance of the weakest tenth of companies (the 10th percentile), and a median for each sector are public signals.
- A single company's reading moves with its own share price, which comes from a licensed market data provider, so it appears only inside Palanor: on the company's Dossier when you are signed in, never in the API, embeds or data files. The same goes for the median of the five hyperscalers.
- It is a model reading, not a rating. The probability it implies is not calibrated to real default rates; use the distance to rank companies and to watch change.
- Banks and other financial companies are left out: their deposits are not debt in this model's sense.
Market and survey series
- NY Fed Corporate Bond Market Distress Index (CMDI): whether the corporate bond market is functioning, for the whole market, investment grade and high yield. Weekly, published monthly.
- Commercial paper: rates for top-rated and lower-rated issuers, the gap between them, and amounts outstanding (Federal Reserve Board).
- Bank lending: the Fed's weekly H.8 balance sheet of U.S. commercial banks (loans by type, securities, deposits) and every Senior Loan Officer Survey series on standards and demand.
- Repo and money funds: overnight repo rates and volumes and money market fund holdings from the OFR Short-term Funding Monitor, plus the credit and funding parts of the OFR Financial Stress Index.
- Credit index swaps: weekly trades, volume and outstanding notional for CDX, iTraxx and related products, investment grade and high yield, from the CFTC Weekly Swaps Report.
Prediction markets
The expected number of U.S. corporate bankruptcies this year implied by Kalshi's contract prices, and Kalshi contracts on recession, an emergency Fed meeting and a U.S. downgrade. These are shown in Palanor only and never redistributed.
What is not here, and why
Trade-by-trade credit default swap prices are published by the swap data repositories (DTCC, ICE) under U.S. reporting rules, but their website terms forbid copying the data into a database or republishing it without written permission. Palanor does not collect or show them until it has that permission. The ICE BofA index spreads already in the Library are shown in the product only and never redistributed.
How fresh it is
Distance to default updates after each market close, repo daily, bond deals daily, the CFTC report weekly (about two and a half weeks after the week it covers), and the CMDI once a month. A daily health check flags any of these that fall behind.