Everything Claude Trading
The complete trading & quant finance system for Claude Code
18 specialized agents | 82 domain skills | 20 commands | Every trading discipline covered
From strategy ideation to live execution -- 82 skills, 18 agents, and 20 slash commands that turn Claude Code into your quant trading co-pilot. Backtest, optimize, risk-check, and deploy -- all from your terminal.
Quick Start
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Agents
18 specialized agents, each an expert in a distinct trading discipline:
| # |
Agent |
Role |
Model |
| 1 |
Quant Strategist |
Quantitative strategy design and alpha research |
Opus |
| 2 |
Risk Manager |
Portfolio risk assessment, VaR, stress testing |
Opus |
| 3 |
Derivatives Analyst |
Options/futures pricing, Greeks, vol surfaces |
Opus |
| 4 |
Execution Specialist |
Order routing, slippage modeling, TCA |
Sonnet |
| 5 |
Backtesting Engineer |
Historical simulation, walk-forward analysis |
Sonnet |
| 6 |
Portfolio Optimizer |
Asset allocation, factor models, rebalancing |
Opus |
| 7 |
Data Engineer |
Market data pipelines, alternative data ingestion |
Sonnet |
| 8 |
Crypto Trader |
Digital asset strategies, DeFi, on-chain analytics |
Sonnet |
| 9 |
Macro Strategist |
Global macro, rates, FX, cross-asset flows |
Opus |
| 10 |
Systematic Trader |
Rule-based systems, signal generation, automation |
Sonnet |
| 11 |
Statistical Arbitrageur |
Stat arb, pairs trading, cointegration |
Opus |
| 12 |
Market Microstructure |
Order book dynamics, HFT patterns, tick data |
Opus |
| 13 |
Volatility Trader |
Vol strategies, dispersion, variance swaps |
Opus |
| 14 |
Fixed Income Quant |
Rates modeling, curve fitting, duration management |
Opus |
| 15 |
Commodities Trader |
Commodity futures, seasonality, term structure |
Sonnet |
| 16 |
Algorithmic Developer |
Trading algorithm design, latency optimization |
Sonnet |
| 17 |
Compliance Monitor |
Trading rule compliance, position limits, reporting |
Sonnet |
| 18 |
Performance Analyst |
Attribution, benchmarking, Sharpe/Sortino analysis |
Sonnet |
Skills (82)
Quant Methods (10)
| Skill |
Description |
factor-model-design |
Multi-factor model construction and validation |
alpha-signal-research |
Alpha signal discovery, decay analysis, IC testing |
time-series-analysis |
ARIMA, GARCH, regime detection, stationarity tests |
machine-learning-signals |
ML-based signal generation: random forests, XGBoost, neural nets |
statistical-testing |
Hypothesis testing, multiple comparison correction, p-hacking prevention |
cointegration-analysis |
Engle-Granger, Johansen tests, half-life estimation |
dimensionality-reduction |
PCA, autoencoders for factor extraction |
bayesian-inference |
Bayesian parameter estimation, posterior analysis |
regime-detection |
Hidden Markov models, change-point detection |
feature-engineering |
Trading feature construction, normalization, selection |
Strategies (10)
| Skill |
Description |
momentum-strategy |
Cross-sectional and time-series momentum |
mean-reversion-strategy |
Statistical mean reversion, Ornstein-Uhlenbeck |
pairs-trading |
Pair selection, spread modeling, entry/exit rules |
trend-following |
Breakout detection, moving average systems, turtle rules |
market-making |
Bid-ask quoting, inventory management, adverse selection |
event-driven-strategy |
Earnings, M&A, macro event trading |
carry-trade |
Interest rate carry, roll yield, funding cost analysis |
relative-value |
Cross-asset relative value, rich/cheap analysis |
multi-strategy-portfolio |
Strategy combination, capital allocation across strategies |
alternative-data-strategy |
Sentiment, satellite, web scraping signal strategies |
Risk Management (10)
| Skill |
Description |
var-calculation |
Parametric, historical, Monte Carlo VaR |
stress-testing |
Scenario analysis, historical stress events |
position-sizing |
Kelly criterion, risk parity, volatility targeting |
correlation-analysis |
Dynamic correlations, tail dependence, copulas |
drawdown-analysis |
Max drawdown, drawdown duration, recovery analysis |
tail-risk-management |
CVaR, extreme value theory, tail hedging |
liquidity-risk |
Market impact modeling, liquidity-adjusted VaR |
counterparty-risk |
Credit exposure, netting, collateral management |
margin-optimization |
Initial/variation margin, cross-margining |
risk-budgeting |
Risk allocation, contribution analysis, limits |
Derivatives (10)
| Skill |
Description |
options-pricing |
Black-Scholes, binomial trees, Monte Carlo |
greeks-analysis |
Delta, gamma, vega, theta, rho computation |
volatility-surface |
Implied vol surface construction, SABR, SVI |
exotic-options |
Barrier, Asian, lookback, digital options |
structured-products |
Autocallables, CLNs, reverse convertibles |
futures-pricing |
Cost of carry, convenience yield, calendar spreads |
interest-rate-derivatives |
Swaps, swaptions, caps/floors pricing |
credit-derivatives |
CDS pricing, CDO tranching, default correlation |
options-strategies |
Spreads, straddles, condors, butterflies |
hedging-optimization |
Delta-hedging, cross-hedging, hedge ratio optimization |
Portfolio Management (8)
| Skill |
Description |
mean-variance-optimization |
Markowitz, Black-Litterman, robust optimization |
risk-parity |
Equal risk contribution, hierarchical risk parity |
factor-investing |
Smart beta, factor tilts, factor timing |
rebalancing-strategy |
Calendar vs threshold rebalancing, tax-aware |
performance-attribution |
Brinson, factor-based, risk-adjusted attribution |
benchmark-construction |
Custom benchmark design, tracking error budgeting |
asset-allocation |
Strategic and tactical asset allocation |
portfolio-construction |
Constraint handling, turnover management, ESG integration |
Execution (8)
| Skill |
Description |
order-management |
Order types, routing logic, smart order routing |
transaction-cost-analysis |
Implementation shortfall, VWAP/TWAP analysis |
market-impact-model |
Almgren-Chriss, temporary/permanent impact |
execution-algorithm |
VWAP, TWAP, POV, IS algorithm design |
dark-pool-strategy |
Dark pool routing, information leakage prevention |
latency-optimization |
Execution latency measurement and reduction |
fill-analysis |
Fill rate, partial fill handling, queue position |
best-execution-compliance |
MiFID II / Reg NMS best execution reporting |
Market Data (6)
| Skill |
Description |
data-pipeline-design |
Real-time and historical data pipeline architecture |
alternative-data-ingestion |
NLP sentiment, satellite imagery, web data |
tick-data-processing |
Tick-by-tick cleaning, aggregation, bar construction |
reference-data-management |
Symbology, corporate actions, universe maintenance |
data-quality-monitoring |
Anomaly detection, gap filling, data validation |
api-integration |
Broker API, exchange feed, vendor data integration |
Crypto & Digital Assets (8)
| Skill |
Description |
defi-analytics |
DEX volume, TVL, yield farming analysis |
on-chain-analysis |
Wallet tracking, whale alerts, network metrics |
crypto-derivatives |
Perpetual swaps, funding rates, basis trading |
tokenomics-analysis |
Token supply dynamics, vesting schedules, inflation |
mev-analysis |
MEV extraction, sandwich attacks, flashbots |
cross-chain-arbitrage |
Bridge arbitrage, cross-DEX opportunities |
stablecoin-monitoring |
Peg stability, reserve analysis, de-peg risk |
nft-market-analysis |
Floor price models, wash trading detection, rarity |
Macro & Global (6)
| Skill |
Description |
economic-indicator-analysis |
GDP, CPI, NFP, PMI interpretation and trading |
central-bank-analysis |
Fed/ECB/BOJ policy analysis, rate path modeling |
fx-strategy |
Currency pair analysis, carry, PPP models |
rates-strategy |
Yield curve trades, duration, convexity |
geopolitical-risk |
Political risk scoring, event impact modeling |
cross-asset-flows |
Fund flow analysis, risk-on/risk-off indicators |
Backtesting & Research (6)
| Skill |
Description |
backtest-engine |
Event-driven and vectorized backtesting frameworks |
walk-forward-analysis |
Rolling window optimization, out-of-sample testing |
monte-carlo-simulation |
Portfolio simulation, confidence intervals |
overfitting-detection |
Deflated Sharpe, CSCV, combinatorial purging |
paper-trading-setup |
Paper trading configuration, live signal monitoring |
research-notebook |
Jupyter-based research workflow, reproducibility |
Commands (20)
| Command |
Description |
/trading-strategy |
Design and document a complete trading strategy |
/backtest |
Run historical backtest with full performance report |
/risk-report |
Generate comprehensive portfolio risk analysis |
/price-derivative |
Price options, futures, and structured products |
/portfolio-optimize |
Run mean-variance or risk parity optimization |
/execution-plan |
Design execution algorithm with cost estimates |
/crypto-analysis |
Analyze crypto markets, on-chain data, DeFi |
/macro-outlook |
Generate macro economic outlook and trade ideas |
/factor-analysis |
Analyze factor exposures and construct factor models |
/vol-surface |
Build and analyze implied volatility surfaces |
/pairs-scan |
Scan universe for cointegrated pairs |
/stress-test |
Run portfolio stress tests against historical scenarios |
/signal-research |
Research and validate new alpha signals |
/tca-report |
Transaction cost analysis on recent executions |
/position-sizer |
Calculate optimal position sizes given risk budget |
/regime-detect |
Identify current market regime |
/correlation-monitor |
Monitor dynamic correlations across assets |
/performance-review |
Generate performance attribution and analytics |
/data-pipeline |
Design or debug market data pipeline |
/compliance-check |
Verify trading compliance with rules and limits |
Rules (5)
| # |
Rule |
Description |
| 1 |
Risk Before Return |
Always quantify risk before evaluating return potential |
| 2 |
Backtest Before Deploy |
No strategy goes live without rigorous historical testing |
| 3 |
Overfitting Awareness |
Apply deflated Sharpe, cross-validation, and out-of-sample checks |
| 4 |
Data Integrity First |
Validate all data inputs; never trust raw feeds blindly |
| 5 |
Execution Realism |
Include transaction costs, slippage, and market impact in all analysis |
Architecture
Core Principles
| Principle |
What It Means |
| Risk-First |
Every analysis starts with risk quantification. No blind return-chasing. |
| Data-Driven |
Decisions grounded in data, not narratives. Statistical significance required. |
| Backtest Before Deploy |
Rigorous historical validation before any live deployment. |
| Overfitting-Aware |
Multiple testing corrections, out-of-sample validation, deflated Sharpe ratios. |
| Execution-Conscious |
Transaction costs, slippage, and market impact are never ignored. |
| Regulatory-Compliant |
Adherence to MiFID II, Reg NMS, Dodd-Frank, and relevant trading regulations. |
Multi-Agent Workflows
Complex trading tasks orchestrate multiple agents working together:
| Workflow |
Agents Involved |
Description |
| Strategy Development |
Quant Strategist -> Backtesting Engineer -> Risk Manager -> Performance Analyst |
End-to-end strategy creation, validation, and analysis |
| Risk Assessment |
Risk Manager -> Portfolio Optimizer -> Compliance Monitor |
Comprehensive portfolio risk review with compliance checks |
| Live Deployment |
Systematic Trader -> Execution Specialist -> Compliance Monitor -> Performance Analyst |
Strategy deployment with execution optimization |
| Derivatives Pricing |
Derivatives Analyst -> Volatility Trader -> Risk Manager |
Complex derivatives pricing with vol and risk analysis |
| Crypto Research |
Crypto Trader -> Data Engineer -> Quant Strategist |
Digital asset research with on-chain data integration |
| Macro Analysis |
Macro Strategist -> Fixed Income Quant -> Portfolio Optimizer |
Global macro view with rates analysis and positioning |
Contexts
| Context |
Purpose |
market-data |
Current market state, asset prices, volumes, and spreads |
portfolio-state |
Active positions, P&L, exposure breakdown |
strategy-config |
Strategy parameters, universe definitions, signal thresholds |
risk-limits |
Position limits, drawdown limits, concentration constraints |
execution-config |
Broker connections, order routing preferences, cost models |
Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines on adding new strategy skills, asset-class agents, and indicator skills.
License
MIT License -- see LICENSE for details.
Acknowledgments
- The quantitative finance open-source community
- Contributors who keep pushing the boundaries of AI-assisted trading
- Every quant who shared a paper, a backtest, or a hard-won lesson
Built for traders who build with AI.
Made with conviction by Brain Bytes
