Y-Nexus Stress

Crash-test your portfolios against historical market crises under dynamic quality-based limits

Performance & Risk Analysis

The Overview tab monitors rolling risk indicators calculated from your transaction history:

  • Sharpe Ratio: Measures risk-adjusted performance. A ratio > 1.0 is considered good.
  • Volatility (Std Dev): Measures annual price fluctuations. Lower values indicate stability.
  • Beta: Measures systematic risk sensitivity compared to the market benchmark (e.g. SPY). A beta of 1.0 matches market moves; < 1.0 indicates lower sensitivity; > 1.0 indicates higher volatility.
  • Benchmark Comparison: Compare your cumulative Time-Weighted Returns (TWR) directly against indices like the S&P 500 (SPY), Nasdaq (QQQ), or commodity rates.

Y-Nexus Stress (Solvency Crash Testing)

How will your portfolio survive a major market shock? The Y-Nexus Stress tool simulates historical crash scenarios on your active Y-Active holdings. It helps you understand tail risk, downside volatility, and capital preservation during systemic market failures.

Historical Crisis Scenarios

The simulator shock-tests your active holdings across four major macroeconomic distress regimes:

  1. Dot-com Bubble (2000): Simulates the collapse of speculative technology stocks and the ensuing multi-year market correction (Mar 2000 - Oct 2002).
  2. Great Financial Crisis (2008): Simulates the subprime mortgage meltdown and banking liquidity freeze (Oct 2007 - Mar 2009).
  3. COVID-19 Crash (2020): Simulates the high-volatility, panic-selling event triggered by global pandemic lockdowns (Feb 2020 - Mar 2020).
  4. Inflation Bear Market (2022): Simulates the impact of aggressive central bank interest rate hikes and rising inflation, which caused both equities and bonds to decline simultaneously (Jan 2022 - Oct 2022).

Methodology

1. Bayesian Beta Shrinkage

To model assets that did not exist during earlier crises, the engine calculates asset-specific systematic risk sensitivities (betas). If historical data is missing for a particular crisis, the engine automatically retrieves the asset’s current 3-year baseline beta and blends it with GICS sector-specific default crash parameters using Bayesian shrinkage to improve stability and reliability.

2. Systematic Shock & Diversification Decay

During severe panic regimes, historical correlation patterns tend to break down, and assets often drop in unison. To reflect this, the engine spikes systematic correlation: all non-cash holdings converge to a minimum beta shock of 0.25, even if their historical beta was zero. Cash holdings (e.g., USD, EUR) are treated as perfect safe-havens and maintain a beta of 0.00.

Out-of-Sample MPT Benchmarking

To help you evaluate whether your allocation is resilient, the stress engine compares your current portfolio against two optimized benchmarks:

  • Safest Allocation (Y-Nexus Bounds): The simulated minimum variance portfolio.
  • Efficient Allocation (Y-Nexus Bounds): The simulated maximum Sharpe ratio portfolio.

[!IMPORTANT]
Pre-Crisis Out-of-Sample Optimization: To prevent look-ahead bias, these benchmarks are optimized over a 7-year historical window preceding each crisis scenario. Furthermore, the simulation applies Y-Nexus Bounds (Y-VQS limits) to ensure that the compared benchmarks follow the same fundamental quality rules and safety bounds you have active today.

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