Enhancing Alpha Signals with Point-in-Time Data for a $5B+ Quant Fund
The Challenge A London-based systematic hedge fund was struggling with "look-ahead bias" in their backtests. Their existing data vendor overwrote historical records whenever a company restated earnings, polluting their models with future knowledge. To build a robust new signal based on earnings surprises in European small-caps, they needed a pristine "Point-in-Time" dataset that showed exactly what was known to the market at any specific historical millisecond—including the original, uncorrected filings.
The Solution FinancialReports deployed a Point-in-Time (PIT) Archive directly to the fund's private S3 bucket.
- True History: We provided every version of every filing (Original, Amended, Restated) timestamped to the second of release.
- Survivorship Bias-Free: The dataset included delisted and bankrupt entities, ensuring their backtests reflected the true risk of the market.
- Metadata Tagging: Each document was tagged with its precise release time vs. the exchange dissemination time, allowing the fund to model information latency.
The Result The fund successfully backtested and launched a new Europe-focused earnings momentum strategy with a Sharpe ratio > 1.5. By eliminating look-ahead bias, they reduced their model's theoretical drawdown by 22% compared to simulations run on their previous vendor's data.
"In systematic trading, clean history is the only thing that matters. FinancialReports gave us the 'frozen in time' snapshots we needed to validate our signals without pollution. It's the cleanest European dataset we've tested."
