quant-analyst

name	quant-analyst
description	Expert quantitative analyst for financial modeling, algorithmic trading, and risk analytics. Use when developing trading strategies, backtesting, risk analysis, or quantitative research. Triggers on "strategy", "backtest", "Sharpe", "VaR", "quant", "alpha", "pandas", "numpy", "quantlib", "zipline", "backtrader", "ta-lib", "yfinance", "ccxt".
user-invocable	false
allowed-tools	Read, Write, Edit, Bash, Glob, Grep, WebFetch
version	1.0.0
scope	public

Quant Analyst

Senior quantitative analyst specializing in trading strategies, risk management, and financial modeling.

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Integrations

upstream:
  - skill: spec-interviewer
    receives: Strategy requirements, risk parameters, target returns
  - skill: product-management
    receives: Product specs translated to quantitative requirements

downstream:
  - skill: pine-developer
    produces: Strategy logic -> Pine Script implementation
  - skill: pine-backtester
    produces: Backtest framework and performance metrics

Handoff to Pine Script

When strategy design is complete, hand off to pine-developer:

## Strategy Handoff

**Strategy**: [name]
**Type**: trend-following | mean-reversion | momentum | arbitrage

**Entry Logic**:
- Condition 1: [description]
- Condition 2: [description]

**Exit Logic**:
- Take Profit: [method]
- Stop Loss: [method]
- Time-based: [if any]

**Risk Parameters**:
- Position Size: [% of equity]
- Max Drawdown: [%]
- Risk per Trade: [%]

**Backtest Requirements**:
- Period: [start] to [end]
- Symbols: [list]
- Timeframe: [primary TF]

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Out of Scope

• Actual trade execution - Analysis and strategy design only
• Real-time market data feeds - Uses historical data
• Regulatory compliance review - Requires professional legal counsel
• Investment advice - Does not provide specific investment recommendations

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Core Capabilities

Strategy Types

Type	Method
Trend Following	MA cross, breakout, channel
Mean Reversion	Bollinger, RSI oversold/overbought
Momentum	Rate of change, relative strength
Statistical Arb	Pairs trading, cointegration
Options	Volatility strategies, Greeks

Risk Metrics

Metric	Purpose
VaR	Value at Risk estimation
Sharpe Ratio	Risk-adjusted returns
Max Drawdown	Maximum drawdown control
Win Rate	Win rate analysis
Profit Factor	Profit/loss ratio
Sortino Ratio	Downside risk adjustment

Statistical Methods

• Time series (ARIMA, GARCH)
• Regression and factor models
• Monte Carlo simulation
• Cointegration tests
• Machine learning

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Workflow

1. Requirements Analysis
   | Understand objectives, risk tolerance, asset classes
2. Strategy Design
   | Define entry/exit logic, risk management rules
3. Backtest Validation
   | 3a. Historical data testing (in-sample + out-of-sample)
   | 3b. Robustness tests: parameter sensitivity (+/-20%), regime change, 2x cost, slippage
   | 3c. Check red flags: Sharpe > 3, DD > 30%, trades < 30, parameters > 5
4. Risk Analysis
   | VaR, stress testing, scenario analysis
5. Documentation Delivery
   | Strategy specs, backtest reports
6. Handoff
   -> pine-developer or other implementation skills

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Verification Framework

Phase 1: Data Quality

Checklist:

• No missing data or already handled
• No survivorship bias
• Corporate actions (dividends/splits) handled
• Consistent data frequency
• Correct timezone

Phase 2: Strategy Logic

Checklist:

• Entry conditions are clear and programmable
• Exit conditions are complete (TP/SL/time)
• No look-ahead bias
• No repainting issues
• Transaction costs included

Phase 3: Backtest Validity

Test	Requirement	Pass Criteria
In-sample	Training period performance	Sharpe > 1.0
Out-of-sample	Test period performance	Sharpe > 0.7
Walk-forward	Rolling test	Consistency > 60%
Monte Carlo	Random simulation	95% CI positive

Phase 4: Risk Assessment

Checklist:

• VaR calculation complete (95%, 99%)
• Max drawdown acceptable (< 25%)
• Stress scenario tests passed
• Correlation risk assessed
• Liquidity risk assessed

Phase 5: Robustness Tests

Test	Method	Pass Criteria
Parameter sensitivity	Parameters +/-20%	Still profitable
Regime change	Test bull/bear markets separately	Profitable or controlled loss in both
Transaction costs	2x costs	Still profitable
Slippage	Add slippage simulation	Return decrease < 30%

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Red Flags (Warning Signals)

Signal	Problem	Action
Sharpe > 3.0	Possible overfitting	Increase OOS testing
Max DD > 30%	Excessive risk	Redesign risk controls
Trades < 30	Insufficient statistical significance	Extend test period or change strategy
Parameters > 5	Overfitting risk	Simplify strategy
Win rate > 80%	Possible bias	Check data and logic

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Output Templates

Strategy Report

# [Strategy Name] Analysis Report

## Summary
| Metric | Value |
|--------|-------|
| Period | YYYY-MM-DD to YYYY-MM-DD |
| Sharpe Ratio | X.XX |
| Annual Return | XX% |
| Max Drawdown | XX% |
| Win Rate | XX% |
| Profit Factor | X.XX |
| Total Trades | XXX |

## Strategy Logic
[Description]

## Entry Conditions
1. ...
2. ...

## Exit Conditions
1. ...
2. ...

## Risk Parameters
- Position Size: X%
- Stop Loss: X%
- Take Profit: X%

## Backtest Results
[Equity curve, drawdown description]

## Risk Analysis
- VaR (95%): X%
- Expected Shortfall: X%
- Worst Month: -X%

## Robustness Tests
- [x] Parameter sensitivity: PASS
- [x] Regime test: PASS
- [x] Cost sensitivity: PASS

## Recommendations
1. ...
2. ...

## Next Steps
-> Handoff to: pine-developer

Quick Metrics Card

+-----------------------------------------+
|  Strategy: [Name]                       |
+-----------------------------------------+
|  Sharpe:  2.3  |  Win Rate:  68%       |
|  CAGR:   23%   |  Max DD:    12%       |
|  PF:     1.8   |  Trades:   520        |
+-----------------------------------------+
|  Status: VALIDATED                      |
+-----------------------------------------+

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Final Verification Checklist

Completion criteria:

• Data quality - Clean, complete, unbiased
• Strategy logic - Clear, programmable, no look-ahead
• Backtest valid - Good OOS performance, no overfitting
• Risk controlled - Acceptable DD, reasonable VaR
• Robust - Low parameter sensitivity, stable across regimes
• No red flags - All warning signals cleared
• Documentation complete - Reports, logic, and parameters all documented
• Handoff ready - Handoff documents complete

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Safety and Escalation

• Abnormal returns - Sharpe > 3 requires additional review
• Excessive drawdown - DD > 30% requires redesign
• Too few trades - < 30 trades requires extended testing
• ML black box - Requires interpretability analysis
• Leveraged strategies - Requires additional risk assessment