Referential Labs Blog
Learn from the best. Our blog is full of tips and tricks to help you deliver your software. When you need a little more help, we're here for you.
Market Data Hygiene Part 3: Reference Data and Historical Integrity
Your price data is clean—but are your corporate actions applied correctly? Is your historical data truly point-in-time? Reference data errors and historical revisionism corrupt backtests in ways that statistical checks can't catch.
Market Data Hygiene Part 2: Cross-Validation and Contextual Analysis
Statistical methods catch obvious errors, but context catches the subtle ones. Learn how cross-asset validation, time-based patterns, venue awareness, and multi-source triangulation reveal data problems that outlier detection misses.
Market Data Hygiene Part 1: Statistical Methods for Detecting Bad Data
Bad data doesn't announce itself. Learn the statistical methods and domain-specific heuristics that separate clean market data from the noise that corrupts your strategies.
Avoiding Common Backtesting Pitfalls: A Practical Guide
Your backtest shows 40% annual returns. But will it hold up in live trading? Learn to identify and fix the most common backtesting errors that inflate expectations and destroy live performance.
Backtesting vs Paper Trading: What Really Matters
Should you trust your backtest or run paper trading first? Neither fully prepares you for live trading—but each has specific use cases. Learn when to use each and how to bridge the gap.
Order Execution Slippage Analysis: Measuring and Mitigating
Your strategy makes money in backtests but loses in live trading. The difference is often execution slippage. Learn how to measure, analyze, and reduce the hidden cost of trading.
Real-Time Data Pipeline Architecture for Trading Systems
Your trading system needs market data with sub-second latency. Learn how to architect data pipelines that reliably deliver real-time market data from exchange to strategy.
