About Linear Derivative VaR
Linear derivative VaR measures possible loss for positions with near linear payoff behavior. It fits swaps, forwards, futures, and delta based option approximations. The method uses sensitivities, volatilities, correlations, and a chosen confidence level. It converts them into a single tail loss estimate for a selected holding period.
Why This Method Helps
Many derivative desks need a quick risk view before deeper simulation. A linear model is transparent. Each exposure shows how one risk factor affects portfolio value. The covariance matrix then combines single factor risk and diversification. This makes the result useful for review, limits, and scenario planning.
Key Inputs
Exposure is the value change for a one unit return in a factor. Volatility measures factor uncertainty. Correlation describes how factors move together. Horizon scales risk through time. Confidence selects the statistical tail. A higher confidence level gives a larger VaR. Mean return can adjust the estimate when a drift assumption matters.
Reading The Output
Portfolio variance is the core matrix result. Standard deviation is its square root. VaR is the selected tail multiple of that deviation. Expected shortfall estimates average loss beyond the VaR point. Risk contribution shows which factor drives the total number. Negative contribution can appear when hedges reduce risk.
Practical Notes
This calculator assumes normally distributed linear changes. Real markets can have jumps, skew, liquidity gaps, and basis risk. Nonlinear options may need gamma, vega, or full revaluation. Stress testing is still important. Use VaR as one risk lens, not a complete decision rule.
Good Workflow
Start with clean exposure mapping. Use consistent daily or annual volatility inputs. Check every correlation value. Compare the example table with your own portfolio. Review risk contribution before accepting the total. Large concentrations may hide inside a small diversified result. Save the CSV for audit notes. Use the PDF when sharing summary results with a team.
Validation Checks
Review signs before trusting results. A long asset exposure and a short hedge should offset. If correlation is one, combined risk may rise. If correlation is negative, risk may fall. A zero volatility factor adds no variance. A negative variance means inputs are inconsistent, so the calculator floors it at zero for display. Check inputs once more.