Stock data analysis with
summary
A Java SQL client called Q Studio loads a 6GB NYSE CSV and runs analysis locally by embedding DuckDB, ingesting about 68 million rows and returning pivots and time-bucketed aggregates in sub-second to low‑hundreds‑millisecond queries. The demo builds candlestick and a naive trading signal using a moving average window plus lag/lead to compute per-trade profit, and it reports a small profitable sum on that toy strategy.
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chapters (6)
- 0:00Introduction to speaker
- 1:11Bank data architecture
- 4:04Data analysis in qStudio
- 9:48Advanced financial modeling
- 15:30Why DuckDB excels in finance
- 16:36Q&A session
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