Value-at-Risk (VaR)
Definition
Value-at-Risk (VaR) estimates the potential loss in value of a portfolio over a defined time period for a given confidence level. For example, a 1-day 95% VaR of –1.5% means there is a 95% chance the portfolio will not lose more than 1.5% in a single day.
Why It Matters to Investors
- Quantifies the worst expected loss over a specific time horizon
- Helps compare risk between portfolios or strategies
- Supports risk management and position sizing
- Often used by institutions and regulators to monitor downside exposure
- Adds context to volatility and drawdown metrics
The TiltFolio View
At TiltFolio, both systems use 1-day 95% historical VaR to provide a consistent risk metric across our strategies, the S&P 500, and TiltFolio Balanced. Our backtests show that TiltFolio Adaptive's VaR tends to be lower than that of the S&P 500, meaning smaller typical daily losses even during volatile periods. This reflects the system's ability to rotate into defensive assets when market conditions deteriorate.
TiltFolio Balanced also demonstrates strong VaR characteristics through its diversified allocation (50% bonds, 30% stocks, 20% gold), which provides natural risk reduction compared to equity-only strategies. The system's consistent diversification helps manage downside risk across different market environments.
VaR helps both systems translate abstract volatility into more tangible expectations. While no risk measure is perfect, we find VaR useful as part of a broader toolkit, especially when evaluating downside risk in turbulent markets. Both systems prioritize risk management, with TiltFolio Adaptive doing so through dynamic rotation and TiltFolio Balanced through strategic diversification.
Real-World Application
• A 1-day 95% VaR of –2% means there is a 5% chance of losing more than 2% in one day
• TiltFolio's backtested VaR is around –1.52% versus –1.75% for the S&P 500
• Portfolios with similar returns but lower VaR offer more efficient risk-reward
• Traders and risk managers use VaR to assess potential losses under normal conditions