Building a Personal Watchlist of Tracked Markets

Choose a neutral universe: one category, date window, public-data availability, unambiguous resolution source, minimum observation frequency, and ethical exclusions. Exclude markets involving personal harm, nonpublic information, manipulation opportunity, unclear terms, or content you should not amplify.

Record the selection rule before choosing markets. This reduces cherry-picking and survivorship bias. Keep excluded items and reasons.

Store:

• event/market stable identifiers and canonical URL;
• question, outcomes, category, status, close/resolution dates;
• resolution source/rules and ambiguity note;
• observed bid, ask, midpoint, last trade, spread, depth, volume fields as defined;
• retrieval UTC time, API endpoint/schema version;
• source-desk state and next verification time;
• paper forecast, rationale source IDs, and immutable forecast timestamp;
• resolution/outcome and scoring fields after closure.

Do not overwrite observations. Append time-series rows. Separate raw API data from normalized analytics.

Use official read-only APIs and current rate-limit guidance. Cache responses, apply backoff, identify failures, and avoid aggressive polling. Refresh frequency should match the research question; a daily calibration study does not need millisecond data.

Detect schema/status changes and missing data. A failed request is not a zero price. Mark stale rows and prevent dashboards from displaying them as current.

Before viewing later outcomes, write a forecast/range and the reasons that could change it. Include a no-view/no-update period if constant price watching harms judgment. Do not send “urgent opportunity” alerts.

Use the watchlist to ask: which contracts are ambiguous, which sources need checking, how calibrated were frozen forecasts, and where did reasoning fail? Do not rank markets by hypothetical profit alone.