Options flow recaps & market notes

Complete code examples for wiring options flow alerts into Discord bots, Slack channels, and custom systems via HMAC-signed webhooks, including signature verification, deduplication, score-based filtering, and a SQLite signal logger for backtesting. Read →

An honest answer by trading style: who benefits from paying for options flow data, who doesn't, how to evaluate signal quality with a paper-trade trial, and the six workflow questions you should answer before subscribing. Read →

A buyer's framework for evaluating options flow scanners: data latency verification, composite scoring standards, alert speed, contextual enrichment (Congress overlap, sector confluence), and the 6 questions to ask before paying for any tool. Read →

What a 15-minute delay actually costs you in options flow: which signals survive it, which don't, how to verify any provider's real data latency, and how to use delayed flow intelligently when real-time isn't available. Read →

A Python implementation guide for building a DIY options flow scanner: data sources, correct Vol/OI computation, sweep detection, composite scoring, and the honest cost comparison between building from scratch vs. using an API. Read →

What historical flow datasets actually contain, how to build a rigorous backtest (with Python), what directional hit-rates to honestly expect by tier, and why almost no tools publish their track records. Read →

REST vs WebSocket, the 8 data fields that actually matter (premium, sweep, Vol/OI, ask-side fill), a Python Discord bot example, webhook HMAC verification, and how to choose a provider. Read →

Raw volume is noise. Vol/OI above 3–5× on meaningful open interest is the real signal, combined with sweep execution, ask-side fills, and next-day OI confirmation. A complete guide to reading volume spikes correctly. Read →

A six-step practical workflow: filter setup, signal qualification, stock vs. options choice, 1–2% position sizing, pre-entry exit plan, and post-entry monitoring. Includes a complete end-to-end trade example. Read →

Five filters that actually matter (premium floor, sweep type, Vol/OI, DTE, ask-side fill), how to read screener output row by row, common mistakes, and a full morning-to-close workflow. Read →

A frank breakdown of three data tiers: free/sample, 15-min delayed (~$29/mo), and real-time ($99–200/mo), with use-case tables showing exactly when each tier is adequate and when it isn't. Read →

PCR measures aggregate market sentiment; unusual flow tracks single-name conviction. How the two diverge, what each divergence means, and how professionals combine both for higher-confidence setups. Read →

A five-step framework for turning a single unusual print into a complete, falsifiable trade thesis, from identifying the signal to sizing the position and defining invalidation conditions. Read →

How a DFS lineup simulator actually works: Monte Carlo scoring, field modeling, and how to read Win%, Top-10%, Cash%, Sim ROI and duplicate risk before you enter a contest. Read →

What a composite score reveals about unusual options activity, which factors raise conviction (sweep, Vol/OI, DTE, premium), score thresholds, and how to integrate the scorecard into a daily workflow. Read →

When congressional stock trades and unusual options flow align on the same ticker, the cross-domain signal is statistically significant. Five recognizable confluence patterns and why each matters. Read →