Stocks Likely to Move Tomorrow (Next-Day Movers)
Where SPX Is Likely to Close Today (0-DTE Strike Band)
De-SPAC Short Signals (De-SPAC Events)
When to Take Risk (Market Regimes)
How Dilution Impacts Stock Prices (Dilution)
Early Signals of Corporate Distress (Defaults)
The Momentum Basket (Quant Galore Momentum Index)
Which Stocks Actually Have Options (Optionable Tickers)
How Stocks Are Grouped (Ticker Classification)
Market Cap, As It Actually Was (Historical Market Cap)
Corporate Default Events: A Practical Guide
When a Company Starts to Break
Defaults don't happen overnight. They unfold through SEC filings, covenant violations, missed payments, and restructuring disclosures — all of which leave a paper trail long before the stock hits zero.
But for equity traders, accessing this information systematically has always been hard. Credit default data lives in the bond and CDS world, locked behind expensive terminals and opaque dealer markets. If you trade equities, you've historically had to rely on news headlines or screen for accounting red flags as a proxy.
The Corporate Default Events dataset changes this. It provides a clean, historical event feed of public-company default events, extracted directly from SEC filing text. Each event is a date-stamped record: this company, on this date, was flagged as being in default status, with a link to the source filing as evidence.
What Counts as a Default Event
The dataset captures events where a company is identified as being in default status based on the text of its SEC filings. This includes situations like debt covenant violations, missed interest or principal payments, cross-default triggers, and formal default notices.
Each record represents a point-in-time event: the company was in default on this date, according to this filing. The filing URL is included so you can verify the source and understand the context.
This is important because defaults are not binary in practice. A company might enter technical default on one covenant while continuing to operate normally. Or it might cure a default weeks later. The dataset gives you the raw events so you can build your own definition of "distressed" based on the level of severity that matters to your strategy.
Why Equity Traders Should Care About Credit Events
In credit markets, defaults are the core risk. But they have powerful implications for equities too, and those implications are systematically underexploited.
Post-event drift. Stocks that enter default tend to continue declining, often for weeks or months. The initial event is just the beginning of a longer repricing. This creates opportunity for short-biased strategies or for timing exits from long positions.
Volatility expansion. Default events are associated with sharp increases in realized and implied volatility. If you trade options, knowing when a name enters default status helps you understand the volatility environment you're stepping into.
Liquidity deterioration. Defaulted companies see bid-ask spreads widen and volume patterns shift. Understanding when a company entered default helps explain otherwise puzzling changes in trading dynamics.
Contagion signals. Defaults rarely happen in isolation. A default in one name can signal stress in a sector, supply chain, or financing structure. Tracking defaults across the universe gives you an early read on systemic stress.
How Traders Use This
Distress watchlists. Monitor the event feed for new defaults and build a running watchlist of distressed names. This is your starting point for short candidates or names to avoid on the long side.
Event studies. Measure the average return path before and after a default event across hundreds of observations. How much does the stock typically fall in the 5, 10, 30 days after the event? Is there predictive signal in the pre-event drift? The dataset gives you the clean event dates to anchor this analysis.
Avoid lists for long portfolios. If you run a long equity strategy, you probably don't want to be holding a name that just entered default. The event feed acts as a real-time filter: any name that appears gets flagged for review or automatic exclusion.
ML labels. For machine learning practitioners, default events make excellent training labels. You can build models that predict the probability of a default event within N days, using financial, price, and alternative data features. The dataset gives you the target variable.
What the Data Looks Like
Three fields per event. The date, the ticker, and the source. Everything you need to identify the event and verify it, nothing you don't.
Key Details
Property | Detail |
Data source | SEC filing text, labeled for default status |
Event type | Default events only (is_default = 1) |
Evidence | Direct link to SEC filing for each event |
History | Point-in-time, never retroactively altered |
The Bottom Line
Default events are one of the most powerful signals in credit markets, but equity traders have historically lacked clean, systematic access to them. This dataset bridges that gap: a structured event feed of corporate defaults, sourced from SEC filings, stored historically, and ready to use in screens, backtests, and production systems.
Whether you're building a distress-driven short strategy, protecting a long portfolio, or generating labels for a predictive model, the starting point is the same: knowing which companies entered default, when, and having the evidence to prove it.
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