Analyze CFTC COT data to compute net positions and open interest.
npx skills add https://github.com/EternisAI/agent-sandbox --skill cftc
Please help me install this Agent Skill. Skill: cftc Source: https://github.com/EternisAI/agent-sandbox/tree/main/skills/cftc Command: npx skills add https://github.com/EternisAI/agent-sandbox --skill cftc
Provides weekly CFTC Commitments of Traders data to reveal who holds and changes position in futures markets, helping users assess crowding and potential market sentiment.
Query TFF or Disaggregated data with get_cot_tff or get_cot_disaggregated and summarize results with summarize_cot_tff or summarize_cot_disaggregated.
High-intent search queries and answers about installing and using this skill.
Use the summarize_cot_tff or summarize_cot_disaggregated functions to compute net positions, deltas, and open-interest shares, producing concise sentiment signals from weekly CFTC COT datasets across various sectors and contracts.
TFF datasets separate leveraged funds from real money, while Disaggregated datasets provide a broader breakdown of trader categories. Both allow you to compare speculative positioning and open interest across equities, rates, currencies, energy, and metals.
Yes, you can filter CFTC COT data by sector or contract when querying TFF or Disaggregated datasets, allowing targeted analysis of speculative positioning and open interest in specific futures markets.
No, this CFTC COT analysis tool has zero external dependencies. It uses built-in Python functions to query CFTC proxy endpoints and compute net positions, deltas, and percentage of open interest directly.
CFTC COT data analysis supports equities, rates, currencies, energy, and metals markets. It evaluates crowding, hedging pressure, and speculative positioning across these futures sectors using weekly TFF and Disaggregated reports.
Calculate net positioning deltas by applying dedicated summarize functions to weekly CFTC reports. These functions compute the changes in long and short positions and output the percentage of open interest for sentiment analysis.
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