Value-at-Risk (VaR) Calculator
Category: Risk ManagementEstimate potential losses in your portfolio with different confidence levels and time horizons
VaR Results
VaR Distribution
VaR by Confidence Level
VaR Comparison
| Time Horizon | 95% VaR | 99% VaR | 99.9% VaR |
|---|
Stress Testing
2008 Financial Crisis
Simulates portfolio losses based on 2008 market conditions
2020 COVID Crash
Models the rapid market decline seen in March 2020
2% Interest Rate Spike
Simulates impact of a sudden 2% rise in interest rates
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.
Risk Management Tools:
What this calculates
The loss a portfolio is not expected to exceed, at a given confidence level.
- Formula
VaR = portfolio value × z-score × volatility × √time. z is 1.645 at 95%, 2.326 at 99%- Worked example
- A 1,000,000 HKD portfolio with 1.2% daily volatility has a 1-day 95% VaR of 1,000,000 × 1.645 × 0.012 ≈ 19,740 HKD.
- When to use it
- To put a number on normal-case downside over a defined horizon.
- Common mistake
- VaR says nothing about the losses beyond the threshold. A 95% VaR is silent about the worst 5% of days, which is where the damage happens.