This section captures essential identification and technical metadata for the trading strategy. All fields marked mandatory must be completed before submission.
Strategy Name
Model Version Number
Primary Developer Name
Development Team Lead
Strategy Description & Core Logic
Strategy Classification
Market Making
Statistical Arbitrage
Momentum/Trend Following
Mean Reversion
Machine Learning Prediction
High-Frequency Arbitrage
Options Market Making
Event-Driven
Multi-Strategy
Other
Primary Asset Class
Expected Average Holding Period
Expected Daily Turnover Ratio (%)
Is this a significant model update from previously approved version?
Code Repository & Version Control Details
Git Repository URL
Commit Hash for Production Build
Has the code been peer-reviewed by at least two senior quants?
Peer Review Summary & Key Findings
Technology Stack & Infrastructure Requirements
Programming Languages Used
Python
C++
Java
Rust
C#
R
Julia
Other
Key Dependencies & Libraries (with versions)
Target Execution Environment
Expected Maximum Latency Tolerance (microseconds)
Does strategy require co-location or proximity hosting?
Has disaster recovery & failover been implemented?
Comprehensive performance validation and risk metric documentation. All performance claims must be supported by documented backtesting results over multiple market regimes.
Backtesting Period Start Date
Backtesting Period End Date
Total Backtesting Duration (months)
Does backtesting include out-of-sample validation?
Has walk-forward analysis been performed?
Core Performance Metrics Summary
Metric Name | In-Sample Value | Out-of-Sample Value | Benchmark Comparison | Meets Minimum Threshold? | |
|---|---|---|---|---|---|
Stress Testing & Scenario Analysis
Has strategy been tested against historical crash scenarios?
Describe performance during worst-case historical scenario
Synthetic Stress Test Results
Stress Scenario | Volatility Multiplier | Correlation Shock (%) | Simulated Loss ($) | Drawdown (%) | Within Risk Limits? | |
|---|---|---|---|---|---|---|
Has Monte Carlo simulation been performed with parameter randomization?
Has strategy been tested for overfitting using combinatorial purged cross-validation?
Overall Confidence Level in Backtesting Results
Very Low
Low
Moderate
High
Very High
Key Limitations & Assumptions in Backtesting Framework
Define explicit capital exposure limits and automated safety mechanisms. These controls are mandatory and cannot be bypassed in production.
Position & Exposure Limits Configuration
Limit Type | Maximum Value ($) | Maximum Percentage (%) | Hard Stop (Auto-Disable)? | Soft Warning Only? | Notification Recipients | |
|---|---|---|---|---|---|---|
Loss-Based Circuit Breaker Configuration
Daily Loss Limit (Hard Stop)
Intraday Loss Limit (Trading Halt)
Consecutive Loss Days Limit before Auto-Disable
Maximum Drawdown from Peak before Review (%)
Are trailing stop-loss mechanisms implemented per position?
Market Condition-Based Circuit Breakers
Auto-disable during extreme market volatility?
Auto-disable during liquidity crisis conditions?
Implement kill switch for correlation breakdown events?
Are manual override capabilities available to risk managers?
Margin & Leverage Controls
Maximum Leverage Ratio (Gross Notional/Capital)
Maintenance Margin Buffer Requirement ($)
Dynamic margin adjustment based on portfolio risk?
Operational Risk Controls
Has maximum order rate per second been configured?
Are fat-finger error checks implemented (price/size validation)?
Does system detect and prevent self-trading?
Has maximum order cancellation ratio been defined?
Overall Robustness of Risk Controls (1=Weak, 5=Exceptional)
Comprehensive assessment of regulatory compliance and market manipulation risks. This section must be completed with utmost diligence.
Primary Regulatory Framework
MiFID II (EU)
Reg NMS (US)
ASIC (Australia)
MAS (Singapore)
HKMA (Hong Kong)
FCA (UK)
Cross-Jurisdictional
Other
If Cross-Jurisdictional or Other, provide details
Is strategy classified as High-Frequency Trading (HFT) under relevant regulations?
Market Manipulation Risk Assessment
Assess manipulation risk for each behavior type (1=No Risk, 5=High Risk)
No Risk | Low Risk | Medium Risk | High Risk | Critical Risk | |
|---|---|---|---|---|---|
Spoofing/Layering risk | |||||
Quote stuffing risk | |||||
Momentum ignition risk | |||||
Cross-market manipulation risk | |||||
Marking the close risk | |||||
Wash trading risk |
Does strategy generate orders that may appear manipulative to surveillance systems?
Has independent compliance review been conducted?
Are real-time surveillance alerts configured for manipulation patterns?
Best Execution & Fair Pricing Compliance
Does strategy implement best execution monitoring?
Are pre-trade risk controls implemented at order gateway level?
Does strategy interact with dark pools or non-displayed liquidity?
Transparency & Reporting Readiness
Are all required regulatory reporting fields automatically captured?
Can strategy produce complete audit trail within 24 hours?
Does firm maintain algorithmic trading documentation per regulatory requirements?
Overall Market Integrity Risk Score (1=Minimal, 5=Critical)
Additional Compliance Notes or Regulatory Concerns
Final authorization section. All previous sections must be completed before executive sign-off. Approvals are binding and subject to regulatory scrutiny.
Chief Risk Officer Name
CRO Approval Date
CRO Risk Assessment - Rate each dimension (1=Poor, 5=Excellent)
Poor | Below Average | Average | Good | Excellent | |
|---|---|---|---|---|---|
Quality of backtesting methodology | |||||
Robustness of risk controls | |||||
Stress test adequacy | |||||
Compliance framework completeness | |||||
Operational readiness | |||||
Team expertise & experience |
CRO Approval - Does the strategy meet all risk management standards?
CRO: Additional Risk Conditions or Monitoring Requirements
Chief Risk Officer Signature
Head of Quantitative Trading Approval
Head of Quant Trading Name
Head of Quant Approval Date
Quantitative Quality Assessment - Rate each dimension (1=Poor, 5=Excellent)
Poor | Below Average | Average | Good | Excellent | |
|---|---|---|---|---|---|
Alpha signal robustness | |||||
Model innovation & edge sustainability | |||||
Technical implementation quality | |||||
Scalability potential | |||||
Competitive advantage analysis | |||||
Research documentation completeness |
Head of Quant Approval - Is the strategy ready for production deployment?
Head of Quant: Deployment Conditions & Post-Launch Review Schedule
Head of Quantitative Trading Signature
Emergency Protocol & Escalation
Has 24/7 on-call escalation list been established?
Are automated kill-switch procedures documented and tested?
Emergency Contact List (Name, Role, Phone, Email)
Name | Role | Phone | ||
|---|---|---|---|---|
Has legal counsel reviewed and approved the deployment?
Legal Approval Reference Number
I confirm that all information provided is accurate and complete to the best of my knowledge
I acknowledge that deployment authorization is conditional upon continuous compliance with risk limits and regulatory requirements
I understand that any material change to strategy parameters requires re-authorization
Final Authorization Timestamp