everything-claude-trading

Analyze signal half-life, alpha decay curves, and strategy capacity

Backtest a trading strategy with rigorous validation and overfitting checks

Analyze portfolio correlations, detect regime breaks, and identify hidden exposures

Analyze crypto assets, DeFi protocols, on-chain metrics, and yield opportunities

Design and validate financial data ingestion, cleaning, and transformation pipelines

Plan trade execution with optimal scheduling, venue selection, and TCA targets

Decompose portfolio returns by factor exposures and identify unintended bets

Design hedging strategies for portfolio risk or single-name exposure

Assess macroeconomic outlook and cross-asset market impact

Detect and classify the current market regime for strategy selection

Analyze options strategies including pricing, Greeks, vol surfaces, and trade structuring

Scan for pairs trading opportunities using cointegration and mean-reversion analysis

Optimize portfolio allocation using mean-variance, risk parity, or factor-based methods

Calculate optimal position sizes using Kelly criterion, volatility targeting, or risk budgeting

Generate a comprehensive portfolio risk report with VaR, stress tests, and exposure analysis

Research and validate alpha signals with statistical rigor

Design a systematic trading strategy from concept to implementation

Run historical and hypothetical stress test scenarios on a portfolio

Review trading performance with execution quality analysis and lessons learned

Analyze volatility surfaces, term structure, and skew for trading opportunities

Algorithmic trading strategist for systematic strategy design, rule-based systems, and execution algorithm development. Use for strategy design or systematic trading approaches.

Backtesting and simulation specialist for strategy validation, walk-forward optimization, Monte Carlo simulation, and overfitting prevention. Use when validating any trading strategy.

Commodities analyst for futures curve analysis, seasonality patterns, supply/demand fundamentals, and commodity trading strategies. Use for commodity market analysis.

Crypto and DeFi analyst for on-chain analytics, protocol analysis, tokenomics evaluation, and yield strategy assessment. Use for cryptocurrency or DeFi analysis.

Derivatives specialist for options pricing, volatility surface construction, exotic option analysis, and structured product evaluation. Use for any derivatives-related analysis.

Trade execution specialist for order management, execution algorithm selection, transaction cost analysis, and smart order routing. Use for execution planning or TCA.

Financial data science specialist for feature engineering, ML model development, alternative data analysis, and quantitative research infrastructure. Use for ML-based trading research or data pipeline design.

Fixed income specialist for bond analysis, yield curve modeling, duration/convexity management, and credit spread analysis. Use for bond portfolio or fixed income strategy work.

FX strategy specialist for currency analysis, carry trade design, macro-driven FX strategies, and hedging. Use for foreign exchange strategy or currency risk management.

Market microstructure specialist for order flow analysis, liquidity assessment, market making, and price discovery research. Use for execution optimization or market structure analysis.

Options strategy specialist for spread design, volatility trading, hedging strategies, and options portfolio management. Use for options trade structuring or vol trading.

Portfolio construction specialist for asset allocation, optimization, rebalancing, and performance attribution. Use for portfolio design or optimization tasks.

Quantitative researcher for alpha signal discovery, factor model construction, and systematic strategy research. Use PROACTIVELY for signal research, factor analysis, or alpha generation.

Trading compliance specialist for MiFID II, Dodd-Frank, position limits, best execution, and regulatory reporting. Use for compliance questions or regulatory risk assessment.

Market risk manager for VaR calculation, stress testing, exposure analysis, and risk limit monitoring. Use PROACTIVELY when any trading strategy or position is being evaluated.

Statistical arbitrage specialist for pairs trading, mean reversion strategies, cointegration analysis, and market-neutral portfolio construction. Use for stat-arb strategy development.

Technical analysis specialist for chart patterns, indicators, price action analysis, and support/resistance identification. Use for technical market analysis.

Volatility trading specialist for vol surface analysis, variance swaps, dispersion trading, and VIX strategies. Use for volatility-focused analysis or trading.

name: live-trading-monitoring

- Estimating confidence intervals for strategy performance metrics (Sharpe, drawdown, CAGR)

- Evaluating whether a backtest result reflects genuine alpha or data mining artifacts

- Setting up Jupyter/research notebook workflows for quantitative research

- Conducting comprehensive evaluation of a trading strategy before deployment

- Validating trading strategy parameters using robust out-of-sample testing

- Identifying and evaluating arbitrage opportunities between centralized and decentralized exchanges

- Analyzing perpetual swap mechanics, funding rates, and basis trading opportunities

- Analyzing DeFi protocol mechanics for trading or yield opportunities

- Analyzing Maximal Extractable Value (MEV) opportunities or risks in DeFi transactions

- Analyzing blockchain data for trading signals (whale movements, exchange flows, network health)

- Evaluating stablecoin peg mechanisms, reserve compositions, and risk profiles

- Evaluating a token's supply dynamics, emission schedule, and value accrual mechanisms

- Evaluating DeFi yield opportunities across protocols and chains

name: alternative-data

name: data-quality

name: data-vendors

name: feature-engineering

name: sentiment-analysis

name: web-scraping-finance

> CRR model, multi-step trees, American options, early exercise boundary, calibration, and convergence to BSM.

> BSM derivation intuition, formula, put-call parity, Greeks, limitations, and extensions for dividends, American options, and implied volatility.

name: credit-derivatives

> Barriers, Asians, lookbacks, digitals, cliquets, autocallables, and quanto options. Pricing, hedging, and risk management.

name: hedging-strategies

> Swaps, swaptions, caps/floors, curve construction, OIS discounting, and multi-curve framework.

> Random number generation, GBM simulation, path-dependent options, variance reduction, Longstaff-Schwartz for Americans, and convergence analysis.

name: structured-products

> Implied vol surface, smile/skew, SVI parameterization, SABR model, sticky strike vs sticky delta, surface dynamics, and arbitrage constraints.

name: vol-trading

> Execution algorithms — TWAP, VWAP, IS, POV, Iceberg for optimal trade execution.

> Low-latency trading infrastructure — co-location, FPGA, kernel bypass, network optimization.

> Market microstructure theory — limit order books, price discovery, bid-ask spread economics.

> Order flow analysis — volume profile, footprint charts, delta for short-term price prediction.

> Sharpe, Sortino, Calmar, Information Ratio, and comprehensive performance measurement.

> Smart order routing — dark pools, lit markets, internalization, and best execution.

> Tick data processing — cleaning, aggregation, bar construction from raw market data.

> Transaction cost analysis (TCA) — slippage, market impact, benchmarks for measuring execution quality.

- Parsing central bank communications (statements, minutes, press conferences, speeches)

- Analyzing commodity futures term structure (contango, backwardation) and roll yield

- Interpreting economic data releases and their market implications

- Analyzing currency valuation using fundamental models (PPP, interest rate parity, balance of payments)

- Assessing the market impact of geopolitical events (conflicts, sanctions, elections)

- Analyzing term structure of interest rates for trading signals or macro assessment

> Alternative investment allocation — PE, VC, hedge funds, real assets in portfolio context.

> Index tracking and replication strategies — full replication, sampling, and optimization.

> Black-Litterman model for portfolio allocation — combining equilibrium returns with investor views.

> Factor investing and smart beta strategies — systematic exposure to return drivers.

> Mean-variance optimization and efficient frontier construction for portfolio allocation.

> Decomposing portfolio returns into allocation, selection, and factor contributions.

> Portfolio rebalancing methodologies — when, how, and how much to trade.

> Risk parity and equal risk contribution portfolios — balancing risk, not capital.

name: alpha-research

name: bayesian-methods

name: deep-learning-trading

name: factor-models

name: kalman-filters

name: ml-for-finance

name: regime-detection

name: reinforcement-learning-trading

name: signal-processing

name: time-series-analysis

> Regime-dependent correlation, diversification failure, dynamic correlation models, and correlation trading strategies.

> Margin, collateral, CVA/DVA/FVA, central clearing, netting, wrong-way risk, and credit support framework.

> Max drawdown, recovery analysis, conditional drawdown at risk, stop-loss design, de-leveraging rules, and drawdown-based position sizing.

> Expected Shortfall calculation, advantages over VaR, regulatory adoption under FRTB, extreme value theory, and tail dependence modeling.

> Delta, gamma, vega, theta hedging and higher-order Greeks. Portfolio-level risk management, dynamic hedging, and rebalancing strategies.

> Bid-ask spreads, market impact, Amihud illiquidity, liquidity-adjusted VaR, and the illiquidity premium.

> Kelly criterion, optimal-f, fixed fractional, volatility targeting, risk parity position sizing, and practical implementation.

> Historical, hypothetical, and reverse stress testing. Scenario design, regulatory frameworks, crisis replay, and integration with risk management.

> Put spreads, VIX calls, tail risk parity, cost-effective crash protection, and systematic tail hedging programs.

> Parametric, historical simulation, and Monte Carlo VaR. Confidence levels, holding periods, backtesting, regulatory requirements, and known limitations.

name: carry-strategies

name: event-driven

name: market-making

name: mean-reversion

name: momentum-strategies

name: multi-asset-strategies

name: pairs-trading

name: relative-value

name: stat-arb

name: trend-following

4 hooks across 2 events