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

Install the plugin:

claude install-skill github:brainbytes-dev/everything-claude-trading

Start using it immediately:

# Develop a mean-reversion strategy
claude /trading-strategy "pairs trading on SPY/QQQ with 2-sigma entry"

# Run a full backtest
claude /backtest "momentum factor strategy, 2015-2025, daily rebalance"

# Assess portfolio risk
claude /risk-report "current portfolio with 60/40 equity/bond split"

# Price an options structure
claude /price-derivative "iron condor on AAPL, 30 DTE, 1-sigma wings"

# Analyze crypto markets
claude /crypto-analysis "ETH on-chain metrics vs price action"

---

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

everything-claude-trading/
├── agents/
│   ├── quant-strategist.md
│   ├── risk-manager.md
│   ├── derivatives-analyst.md
│   ├── execution-specialist.md
│   ├── backtesting-engineer.md
│   ├── portfolio-optimizer.md
│   ├── data-engineer.md
│   ├── crypto-trader.md
│   ├── macro-strategist.md
│   ├── systematic-trader.md
│   ├── statistical-arbitrageur.md
│   ├── market-microstructure.md
│   ├── volatility-trader.md
│   ├── fixed-income-quant.md
│   ├── commodities-trader.md
│   ├── algorithmic-developer.md
│   ├── compliance-monitor.md
│   └── performance-analyst.md
├── skills/
│   ├── quant-methods/
│   ├── strategies/
│   ├── risk/
│   ├── derivatives/
│   ├── portfolio/
│   ├── execution/
│   ├── data/
│   ├── crypto/
│   ├── macro/
│   └── backtesting/
├── commands/
│   ├── trading-strategy.md
│   ├── backtest.md
│   ├── risk-report.md
│   └── ... (20 commands)
├── rules/
│   ├── risk-before-return.md
│   ├── backtest-before-deploy.md
│   ├── overfitting-awareness.md
│   ├── data-integrity.md
│   └── execution-realism.md
├── contexts/
│   ├── market-data.md
│   ├── portfolio-state.md
│   └── strategy-config.md
├── hooks/
│   ├── pre-trade-risk-check.md
│   └── post-backtest-validation.md
└── README.md

---

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}