Risk Management

Comprehensive risk management framework combining real-time monitoring, stress testing, and advanced controls to protect and optimize portfolio performance.

Parallax's comprehensive risk management framework protects client portfolios while optimizing for superior risk-adjusted returns. Our multi-dimensional approach combines real-time monitoring, predictive analytics, and systematic controls to manage both known and emerging risks.

Multi-Dimensional Risk Framework

Beyond Traditional Risk Metrics

While most platforms focus on simple volatility measures, Parallax monitors risk across multiple dimensions:

Factor Risk

• Concentration Monitoring: Prevent overexposure to any single factor

• Interaction Effects: Track how factors correlate during stress periods

• Style Drift: Ensure portfolios maintain intended factor exposures

Market Risk

• Volatility Tracking: Real-time portfolio volatility measurement

• Beta Management: Control systematic market risk exposure

• Correlation Analysis: Monitor changing relationship patterns

Concentration Risk

• Position Limits: Maximum exposure to individual securities

• Sector Concentration: Industry and geographic exposure controls

• Factor Concentration: Prevent over-reliance on single factors

Liquidity Risk

• Trading Volume: Ensure adequate liquidity for position changes

• Market Impact: Estimate costs of portfolio adjustments

• Stress Liquidity: Model liquidity during market stress periods

Real-Time Risk Monitoring

Continuous Assessment

Real-Time Metrics:

  • Portfolio volatility and Value-at-Risk (VaR) updated every 15 minutes
  • Factor exposures tracked against targets throughout the day
  • Concentration measures monitored across all dimensions
  • Correlation matrices updated with each market close

Dynamic Risk Budgeting:

  • Risk allocation across factors, sectors, and individual positions
  • Active share measurement against benchmarks
  • Tracking error decomposition and analysis
  • Expected shortfall and tail risk measurement

Market Regime Detection:

  • Automatic identification of changing market conditions
  • Volatility regime classification (low, normal, high)
  • Factor correlation regime monitoring
  • Crisis period detection and preparation

Stress Testing and Scenario Analysis

Comprehensive Stress Testing

Historical Scenario Analysis:

  • Performance simulation during major market events (2008, 2020, etc.)
  • Factor behavior during different crisis types
  • Correlation breakdown analysis during stress periods
  • Recovery pattern analysis and timing

Forward-Looking Stress Tests:

  • Monte Carlo simulations with 10,000+ scenarios
  • Economic recession and expansion scenarios
  • Interest rate shock and inflation scenarios
  • Geopolitical and black swan event modeling

Factor-Specific Stress Tests:

  • Individual factor breakdown scenarios
  • Factor correlation stress testing
  • Momentum crash and value trap scenarios
  • Quality deterioration and defensive failure tests

Advanced Risk Controls

Systematic Risk Management

Position-Level Controls

Maximum Position Sizes: Typically 3-5% per individual security Liquidity Requirements: Minimum daily volume thresholds Quality Screens: Fundamental filters to avoid deteriorating companies Correlation Limits: Prevent highly correlated position clustering

Portfolio-Level Controls

Volatility Targets: Client-specific maximum volatility limits Factor Bounds: Tolerance bands around target factor exposures Sector Limits: Maximum exposure to individual sectors/industries Geographic Limits: Concentration controls for regional exposure

Dynamic Controls

Regime-Aware Limits: Tighter controls during high volatility periods Correlation-Based Sizing: Position sizes adjust for correlation changes Momentum Controls: Reduced momentum exposure during reversal risks Liquidity-Based Limits: Position sizes reflect current market liquidity

Implementation Risk Management

Transaction Cost Control:

  • Pre-trade cost analysis and optimization
  • Market impact modeling and minimization
  • Optimal execution timing and sizing
  • Post-trade cost analysis and model improvement

Rebalancing Risk Management:

  • Intelligent rebalancing considering multiple factors
  • Tax-aware rebalancing for taxable accounts
  • Market timing considerations for major changes
  • Gradual implementation for large portfolio shifts

Client-Specific Risk Management

Tailored Risk Approaches

High Net Worth (over 1M AUM):

  • Sophisticated risk budgeting and allocation
  • Custom risk constraints and preferences
  • Advanced hedging strategies and derivatives
  • Direct coordination with external risk managers

Affluent (150K-1M AUM):

  • Balanced risk approach with moderate customization
  • Clear risk communication and education
  • Automated risk controls with override capabilities
  • Regular risk review and adjustment opportunities

Emerging Wealth (under 150K AUM):

  • Age-appropriate risk tolerance (typically higher)
  • Educational risk content and market context
  • Simplified risk metrics and clear explanations
  • Long-term perspective on risk and volatility

Risk-Return Optimization

Continuous Improvement

Performance Attribution:

  • Decomposition of returns by risk source
  • Factor contribution vs. security selection
  • Risk-adjusted performance measurement
  • Benchmark comparison and active share analysis

Risk Efficiency Analysis:

  • Identification of unrewarded risks
  • Optimization opportunities for better risk-adjusted returns
  • Factor efficiency measurement and improvement
  • Cost-benefit analysis of risk reduction strategies

Dynamic Risk Budgeting:

  • Optimal allocation of risk across different sources
  • Factor risk vs. specific risk trade-offs
  • Active risk vs. tracking error management
  • Risk capacity utilization and optimization

Technology and Integration

Advanced Risk Systems

Real-Time Processing:

  • Sub-second risk calculation updates
  • Integration with market data feeds
  • Automated model recalibration
  • Cloud-based scalability and reliability

Machine Learning Enhancement:

  • Pattern recognition for risk factor identification
  • Predictive modeling for risk regime changes
  • Anomaly detection for unusual risk patterns
  • Continuous model improvement and adaptation

Integration Capabilities:

  • API access for real-time risk data
  • Integration with external risk systems
  • Custom reporting and analytics
  • Third-party data source integration

Note:

Understanding Risk Metrics: For detailed explanations of volatility, beta, correlation, tracking error, drawdown, and other risk metrics including mathematical formulas, data requirements, and interpretation guidelines, see our Investment Terms Glossary.

See how our risk management integrates with Portfolio Construction and Portfolio Analyzer to provide comprehensive portfolio protection.