{"uid":"cap_qs5L60JdrjE4UxiJ2Onwc","slug":"trading-journal-iqr-outlier-flags-two-measure-correlation-8e346126","name":"Trading Journal IQR Outlier Flags + Two-Measure Correlation","description":"Trading journal observations — IQR outlier flags + Two-measure correlation: IQR outlier flags + Two-measure correlation for supplied trading journal observations records (entry_price, exit_price). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-finance-09-176?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","instrument_group","date","entry_price","exit_price"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"exit_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"entry_price":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"instrument_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","exit_price":1,"entry_price":10,"instrument_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","exit_price":2,"entry_price":20,"instrument_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","exit_price":3,"entry_price":15,"instrument_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","exit_price":4,"entry_price":30,"instrument_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["entry_price","exit_price"],"type":"string","default":"entry_price"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_IZtsNUJcomTmiJMk-DhTC","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes trading journal entry/exit price records to flag IQR-based outliers and compute two-measure correlation, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you run IQR outlier detection and correlation analysis on my trading journal? Here are my records — each row has a row_id, instrument_group, date, entry_price, and exit_price — I want to check the entry_price field for outliers and see how entry and exit prices correlate across up to 50 trades.","exampleUseCases":[{"title":"Flag outlier trades in equity journal","prompt":"I have a list of about 80 equity trades with entry and exit prices — can you run IQR outlier flagging on the entry_price field and also compute the two-measure correlation between entry and exit prices? Here are the rows with date, row_id, instrument_group, entry_price, and exit_price."},{"title":"Spot anomalous forex entries","prompt":"I want to check my forex trading journal for weird outlier trades — use IQR to flag anything abnormal in exit_price and also give me a correlation report between entry and exit prices across these 120 records grouped by instrument_group."},{"title":"Audit crypto trading records statistically","prompt":"Can you analyze these 200 crypto trading records for statistical outliers using IQR on the entry_price field, and also run a two-measure correlation between entry_price and exit_price? The data includes date, row_id, instrument_group, and both price fields."}],"resultDescription":"Returns two reports: (1) IQR outlier flags identifying which rows have entry_price or exit_price values outside interquartile range thresholds, and (2) a two-measure correlation analysis between entry_price and exit_price across the supplied rows. All computation is performed locally using analytical engines with no external data lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds max row limit","Missing required fields (row_id, instrument_group, date, entry_price, exit_price) — validation error","Invalid date format not matching YYYY-MM-DD pattern — schema error","Price values outside allowed numeric range — validation failure","Insufficient data variance for meaningful correlation — may return degenerate results"],"whenToPreferThis":"Choose this endpoint when you need local, deterministic statistical analysis of trading journal records without any external data fetching, live market lookups, or ML prediction. It is ideal for post-trade analysis workflows where you want IQR-based outlier detection and a correlation check between entry and exit prices in a single low-cost API call covering up to 200 rows. Prefer it over general-purpose analytics tools when you specifically need these two paired reports on structured trade records with instrument_group segmentation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T13:16:06.909Z","isFirstParty":false,"canonicalSlug":"trading-journal-iqr-outlier-flags-two-measure-correlation-8e346126"}