Value-at-Risk (VaR) Calculator

Category: Risk Management
- May 18, 2025
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Estimate potential losses in your portfolio with different confidence levels and time horizons

$
%
Standard deviation of annual returns
Probability that losses will not exceed the VaR value
Calculation Method:

VaR Results

Value-at-Risk (VaR) $0.00 Based on 95% confidence
Maximum Loss Percentage 0.00%
Expected Shortfall (CVaR) $0.00 Average loss when VaR is exceeded

VaR Distribution

VaR by Confidence Level

VaR Comparison

Time Horizon 95% VaR 99% VaR 99.9% VaR

Advanced Settings

Stress Testing

2008 Financial Crisis

Simulates portfolio losses based on 2008 market conditions

Potential Loss: $0.00

2020 COVID Crash

Models the rapid market decline seen in March 2020

Potential Loss: $0.00

2% Interest Rate Spike

Simulates impact of a sudden 2% rise in interest rates

Potential Loss: $0.00

About Value-at-Risk (VaR)

Value-at-Risk (VaR) is a statistical technique used to measure and quantify the level of financial risk within a portfolio over a specific time frame. It estimates how much a portfolio might lose in value over a defined period, with a given confidence level, under normal market conditions.

Parametric VaR

This approach assumes returns follow a normal distribution and uses volatility to estimate potential losses. It's simple and fast but may underestimate risks during extreme market conditions.

Historical VaR

Uses actual historical returns to estimate VaR. This approach doesn't assume a specific distribution but is limited by the historical data available and may not capture future risks.

Monte Carlo VaR

Generates thousands of random simulations based on statistical properties of returns. Offers flexibility in modeling different market conditions but is computationally intensive.

Conditional VaR (CVaR)

Also known as Expected Shortfall, CVaR measures the average loss exceeding the VaR threshold. It provides more insight into tail risk and is considered a more coherent risk measure than VaR.

Tips for Using VaR Effectively

  • VaR is not a maximum loss estimate; it can be exceeded with the probability specified (e.g., 5% for a 95% confidence VaR).
  • Consider using multiple confidence levels and time horizons to better understand your risk profile.
  • Supplement VaR with stress testing to assess potential losses during extreme market events.
  • Remember that all VaR models have limitations and should be part of a broader risk management strategy.
  • Regularly recalibrate your VaR model as market conditions and portfolio composition change.

VaR Results: Gauging Risk Exposure with Confidence

After running your portfolio numbers through the Value-at-Risk (VaR) calculator, you’re looking at a statistical snapshot of how much you might lose over a chosen timeframe, at a specific confidence level. This isn’t just a theoretical number—it’s a practical way to assess whether your current positions align with your risk tolerance, and whether adjustments are needed.

Whether your result shows a potential loss of $1,200 or $120,000, the key is understanding what it reflects: the maximum loss you’re not likely to exceed, given normal market conditions, for your selected horizon and confidence level.

What Your VaR Output Says About Your Portfolio

  • VaR Amount: This is your estimated potential loss. A 1-day 95% VaR of $5,000 means there's a 5% chance you could lose more than $5,000 in a single day.
  • Maximum Loss Percentage: Helpful for comparing risk across different portfolio sizes. A 4% VaR tells you you’re exposed to a relatively higher short-term swing than a portfolio with a 1.2% VaR.
  • Expected Shortfall (CVaR): This shows the average loss you might see if the VaR threshold is breached. If your CVaR is significantly larger than the VaR, you’re carrying heavier tail risk than it might appear at first glance.

Signals to Watch in Your VaR Output

  • VaR rises sharply with longer time horizons: This is natural, but if the increase seems too steep, it might signal higher exposure to compounding volatility.
  • High CVaR-to-VaR ratio: If your Expected Shortfall is 1.5x or more of your VaR, the distribution of losses may have a fat tail—especially relevant if you used the Student’s t-distribution or Monte Carlo method.
  • Stress test losses exceed VaR by a large margin: Scenarios like the 2008 crash or a 2% rate hike might show losses 3–5x greater than your VaR. This is a clear warning not to rely solely on historical volatility or Gaussian assumptions.

Comparing Calculation Methods: Why It Matters

The calculator offers different methods—each telling a slightly different story:

  • Parametric: Fast and clean but assumes normal distribution. Can understate losses in extreme markets.
  • Student’s t-distribution: Adjusts for fat tails. Useful if your assets have shown large swings or limited liquidity.
  • Monte Carlo: Offers flexibility by simulating thousands of outcomes. Great for complex portfolios but requires careful setup.
  • Historical simulation: Reflects past market behavior. However, it assumes history will repeat, which isn’t always the case.

Risk Factors to Keep in Mind

  • VaR does not measure worst-case scenarios. It simply tells you where 95% (or 99%) of your outcomes lie under assumed conditions.
  • Correlation assumptions can skew results. A 0.6 correlation with the market might be valid in normal times, but it could spike to 0.9 in a crisis.
  • Time decay and leverage matter. Short-term VaR might look small, but if you're holding leveraged positions, losses can escalate quickly.
  • Overfitting with advanced methods: Monte Carlo and t-distributions add flexibility, but more complexity doesn’t always mean more accuracy—especially if inputs aren't grounded in actual portfolio behavior.

Next Steps with Your VaR Analysis

Your VaR result isn’t the final word—it’s a starting point. Here’s how to take your analysis further:

  • Cross-check with real-world events. Use the built-in stress test results to see how your portfolio might fare in turbulent markets—not just calm ones.
  • Re-run with multiple timeframes. Compare 1-day, 1-week, and 1-month VaR results to understand how your exposure scales over time.
  • Adjust volatility inputs based on recent market behavior. If your asset class is spiking, the annualized volatility you’re using may be stale.
  • Pair with scenario planning. VaR works best when combined with forward-looking simulations—like modeling the impact of rate hikes, geopolitical shocks, or earnings misses.
  • Use CVaR to guide your stop-loss strategy. If CVaR suggests deeper losses than you're comfortable with, consider reducing position size or adding protective hedges.

At the end of the day, VaR is a valuable checkpoint—but not a seatbelt. Continue testing, adjusting, and monitoring your exposure regularly. Markets shift, and your risk profile should shift with them.