ValueAtRisk Function for Portfolio Risk Assessment
The ValueAtRisk function in MarketXLS provides a streamlined way to estimate how much a portfolio could lose under normal or extreme market conditions. By simply specifying your holdings, time period, confidence level, and calculation method, you can quickly evaluate both short-term and long-term risks without leaving Excel. This function supports multiple VaR methods—historical, conditional, Gaussian (parametric), and Cornish-Fischer—to help you make informed decisions under various modeling assumptions.
Why Use This Function?
- Identify Potential Losses: Quickly assess the worst-case loss your portfolio might face within a given time frame.
- Multiple Methods: Switch between historical, conditional, Gaussian, or Cornish-Fischer VaR depending on your risk modeling preferences.
- Flexible Input Parameters: Adjust the lookback period, confidence level, and more to suit your analysis.
- Informed Risk Management: Incorporate VaR estimates into your overall portfolio optimization, hedging strategies, and drawdown assessments.
- Real-World Applicability: Useful for traders, fund managers, and individual investors managing portfolios of publicly traded US stocks or ETFs.
How to Use in Excel
=ValueAtRisk(portfolio, [period], [levelOfSignificance], [variation])
- Enter your portfolio data (e.g., ticker symbols with their weights) into Excel.
- In a cell, type the function name "ValueAtRisk", followed by the necessary parameters.
- Press Enter to calculate various types of VaR.
- If you omit “variation,” a historical VaR is computed by default.
Parameters Explained
Parameter | Description | Example Values | Notes |
---|---|---|---|
portfolio | The composition of your portfolio, typically a range of tickers and weights (e.g., cells A2:B5). | A2:B5 with tickers and weights | Ensure the total weights sum to 1. The add-in automatically normalizes weights if they do not sum to 1. |
period (optional) | Number of months (by default 12) used for historical lookback or data sampling. | 12, 24, 36 | Must be numeric or convertible to a number. If left blank, defaults to “12”. |
levelOfSignificance | The VaR confidence level as a decimal (e.g. 0.05 equals 5% significance). | 0.05 (5%), 0.01 (1%) | If left at 0, this can result in 0% significance, which is typically not practical; specify a proper value like 0.05. |
variation (optional) | Selects the VaR calculation methodology. Blank or “historical” uses the historical approach. Other valid options: “conditional”, “gaussian”, or “cf” (Cornish-Fischer). | “historical”, “conditional”, “gaussian”, “cf” | Different methods yield different VaR estimates. If parameter is excluded, the function defaults to “historical” VaR. |
Example Usage
Basic Examples
-
Historical VaR with defaults (12 months, 5% significance): • Assuming your portfolio data is in cells A2:B5, and each ticker’s weight is in that range:
=ValueAtRisk(A2:B5, 12, 0.05, "historical")
Explanation: This calculates a Historical VaR at a 95% confidence level (5% significance) based on 12 months of returns. -
Conditional VaR (also known as Expected Shortfall) over 24 months at 5%: • =ValueAtRisk(A2:B5, 24, 0.05, "conditional")
Explanation: If the portfolio experiences extreme losses (beyond the 5% VaR threshold), this method measures the average loss in those tail events. -
Gaussian VaR for a smaller alpha level of 1%: • =ValueAtRisk(A2:B5, 12, 0.01, "gaussian")
Explanation: Uses a parametric approach assuming normally distributed returns to estimate losses at the 99% confidence level. -
Cornish-Fischer (CF) VaR for 12 months, 5%: • =ValueAtRisk(A2:B5, 12, 0.05, "cf")
Explanation: Adjusts the normal VaR by accounting for skewness and kurtosis in the returns distribution.
Advanced Scenarios
• VaR at multiple confidence levels:
- You might want to compare a moderate 5% VaR against an extreme 1% VaR to see how your risk profile changes. Simply change the levelOfSignificance parameter and observe the outcomes.
• Mixed-asset portfolio: - If your workbook contains a mix of large-cap stocks and sector ETFs, you can group them into different sets of cells and switch references to see how each allocation impacts VaR.
• Integration with other portfolio analytics: - Combine ValueAtRisk with measures like Sharpe ratio or Drawdowns to keep track of both risk and performance in one sheet.
Common Questions and Troubleshooting
- “Why do I get ‘NA’ as a result?”
- This often occurs if the portfolio range is invalid, the data is missing, or an unexpected error occurred. Make sure your portfolio’s tickers and weights are valid and publicly traded US securities.
- “How do I fix a portfolio with NaN errors?”
- If you have unrecognized or delisted tickers, the function may drop them or return an error. Check that each ticker in your range is valid.
- “Can I use more than 500 tickers?”
- The function does not support portfolios larger than 500 tickers. If you exceed this limit, you may receive an error message.
- “My portfolio doesn’t sum to 1. Will the function fail?”
- The function automatically normalizes weights if they do not sum to 1. Verify the results carefully to ensure they match your expectations.
- “Which VaR method should I use?”
- “historical” reflects actual past return distributions, “gaussian” assumes normal distributions, “conditional” calculates expected shortfall in the worst cases, and “cf” modifies the normal approximation for skewness and kurtosis.
By using the ValueAtRisk function in MarketXLS, you can efficiently measure and compare your portfolio’s potential losses under multiple risk models—empowering you to maintain better control over your trading and investment decisions.