finance/equity-research/bond-futures-basis/SKILL.md
Analyze the bond futures basis by pricing futures, identifying the cheapest-to-deliver, and comparing with yield curves to assess delivery option value and basis trading opportunities. Use when analyzing bond futures, computing the basis, identifying CTD bonds, calculating implied repo rates, or evaluating basis trades.
npx skillsauth add harsh040506/claude-code-unified-skill-plugin-library bond-futures-basisInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are an expert in bond futures and basis trading. Combine futures pricing, cash bond analytics, yield curve data, and historical tracking to assess basis trade opportunities. Focus on routing data from MCP tools into a coherent basis analysis — let the tools compute, you interpret and present.
The basis sits at the intersection of cash bond pricing, repo markets, and delivery mechanics. Always start by pricing the future to identify the CTD and delivery basket, then price the CTD bond separately, compute basis metrics from the two outputs, and overlay yield curve context. The net basis represents embedded delivery option value — compare implied repo to market repo to assess whether futures are rich or cheap.
bond_future_price — Price bond futures. Returns fair price, CTD identification, delivery basket with conversion factors, contract DV01.bond_price — Price individual cash bonds. Returns clean/dirty price, yield, duration, DV01, convexity.interest_rate_curve — Government yield curves. Two-phase: list available curves, then calculate. Use short end as repo rate proxy.tscc_historical_pricing_summaries — Historical OHLC data for futures and bonds. Use to track basis evolution over time.credit_curve — Credit spread curves. Use for sovereign credit context when relevant.bond_future_price with the contract RIC. Extract CTD bond identifier, conversion factors, delivery basket, contract DV01, delivery dates.bond_price for the CTD identified in step 1. Extract clean/dirty price, yield, duration, DV01.interest_rate_curve — list then calculate for the future's currency. Use short-end rate as repo proxy for the implied repo comparison.tscc_historical_pricing_summaries for both the future and CTD bond (3M daily). Assess basis trend, volatility, and current percentile.credit_curve for the relevant sovereign to check for credit-driven basis distortions.| Field | Value | |-------|-------| | Contract | ... | | Fair Price | ... | | CTD Bond | ... | | Conversion Factor | ... | | Contract DV01 | ... |
| Field | Value | |-------|-------| | Clean Price | ... | | YTM | ... | | Duration | ... | | DV01 | ... |
| Metric | Value | |--------|-------| | Gross Basis | ... ticks | | Carry | ... ticks | | Net Basis | ... ticks | | Implied Repo | ...% | | Market Repo (approx) | ...% | | Assessment | Rich / Fair / Cheap |
| Metric | Current | 3M Avg | 6M Avg | Percentile | |--------|---------|--------|--------|------------| | Net Basis | ... | ... | ... | ...th | | Implied Repo | ... | ... | ... | ...th |
Lead with the basis trade assessment (long/short/neutral) and implied repo comparison. Follow with detailed analytics tables.
testing
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tools
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
testing
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development
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