StockQL blog https://stockql.ai/feed.xml 2026-10-22T00:00:00Z StockQL How to backtest earnings-call signals https://stockql.ai/blog/how-to-backtest-earnings-call-signals.html 2026-10-22T00:00:00Z Build a leakage-controlled earnings transcript NLP pipeline with audited sections, post-reaction returns, and issuer-aware uncertainty. A ticker is not an earnings transcript's identity https://stockql.ai/blog/ticker-is-not-transcript-identity.html 2026-10-16T00:00:00Z Verify transcript issuer lineage across acquisitions, ticker reuse, fiscal labels, and provider timestamp differences. Today's bulk market-data file may not be final https://stockql.ai/blog/todays-bulk-file-may-not-be-final.html 2026-10-11T00:00:00Z Design daily ingestion for mutable bulk snapshots, late rows, placeholder data, and explicit-date completeness checks. Two matching fundamentals feeds can still be wrong https://stockql.ai/blog/matching-fundamentals-can-still-be-wrong.html 2026-10-06T00:00:00Z Test statement freshness, restatements, field semantics, and source independence with an SEC XBRL verification layer. Market-data coverage is not one number https://stockql.ai/blog/market-data-coverage-is-not-one-number.html 2026-09-30T00:00:00Z Compare market-data coverage by instrument, venue, history, freshness, and field depth instead of one provider-wide score. Split-adjusted prices can change after ingestion https://stockql.ai/blog/split-adjusted-prices-can-change.html 2026-09-24T00:00:00Z Map raw and adjusted price semantics, detect stale split restatements, and use a second provider as an arithmetic arbiter. Dead ETFs and survivorship bias in backtests https://stockql.ai/blog/dead-etfs-and-survivorship-bias.html 2026-09-18T00:00:00Z Why erased fund history is a separate defect from inaccurate delisting data, and how to preserve a point-in-time universe. When is a stock really delisted? https://stockql.ai/blog/when-is-a-stock-really-delisted.html 2026-09-13T00:00:00Z Separate missing prices, provider availability, ticker reuse, and formal delisting evidence without creating zombie securities. How to screen Japanese net-net stocks with SQL https://stockql.ai/blog/how-to-screen-japanese-net-net-stocks.html 2026-09-12T00:00:00Z Screen Japan-listed stocks for NCAV, Graham-style, double-net, and triple-net thresholds with reproducible SQL and filing checks. How to categorize earnings call transcripts with an LLM https://stockql.ai/blog/how-to-categorize-earnings-transcripts-with-an-llm.html 2026-09-12T00:00:00Z Export earnings calls from StockQL, classify demand, pricing, margins, and capital spending with quoted evidence, then screen the labels in PostgreSQL. How to backtest a trading strategy with SQL https://stockql.ai/blog/how-to-backtest-with-stockql.html 2026-09-11T00:00:00Z Build and evaluate a 200-day moving-average backtest in PostgreSQL with StockQL, including runnable SQL, costs, drawdowns, and live results.