VaR Analysis gives you the same risk math that institutional desks use to size their portfolios (Historical VaR, Parametric VaR, and Monte Carlo VaR) running live against your real positions. Daily VaR. Stress VaR. Conditional VaR. The dollar amount you could realistically lose, with three independent methods that agree (or don't, and that's interesting too).
Most retail traders manage risk by gut. "I think I'm taking maybe 2% risk." "This feels like a normal day." "I should be okay if BTC drops 5%." Gut is fine until the day it isn't. Usually the day everything you hold correlates and the position you thought was 2% turns out to have been 8%.
If you can't put a dollar number on your downside, you don't have risk management. You have hope.
VaR Analysis answers the math question, three different ways, with each method's assumptions visible so you can argue with them. Historical VaR looks at the worst N days in your actual trading history and asks: how often, and how much. Parametric VaR assumes the world follows a normal distribution and gives you the clean textbook number. Monte Carlo VaR simulates 10,000+ possible tomorrows and shows you the full distribution, fat tails included. When the three agree, you know your number. When they disagree, you know which assumption is failing.
Each VaR method has known strengths and known blind spots. We run all three live on your book, side-by-side, so the limitations of each are visible. When they agree, you have a confident estimate. When they disagree, you've found the question worth asking.
Takes your portfolio composition today, walks it backward through every day of price history, and asks: how often has this lost more than $X? The 5th percentile is your 95% historical VaR.
Assumes returns are normally distributed (or fitted to t-distribution), uses your portfolio's variance-covariance matrix to compute the theoretical 5th percentile loss in closed form. Fast, clean, textbook.
Simulates 10,000+ possible future paths for every instrument in your book, accounting for correlation, drift, volatility regime, and jump risk. The 5th percentile of simulated outcomes is your 95% Monte Carlo VaR.
Historical, parametric, Monte Carlo. All three computed continuously on your live book. Side-by-side. When they disagree, you know which assumption is breaking.
Run your current book through 2008, 2010 Flash Crash, 2015 SNB, COVID, 2022 yen intervention. See the dollar P&L that would result. Stress VaR is the number most retail traders never see.
"If we exceed VaR, how bad does it get on average?" CVaR (also called Expected Shortfall) answers this. It's the number prop firms and funds use because it captures tail severity.
VaR isn't just a single number. It's decomposable. See exactly which position is contributing the most to total portfolio risk. Often surprising, almost always actionable.
How often has your actual P&L breached your VaR estimate? A 95% VaR should be breached ~1 day in 20. If you're getting breached 1 day in 5, your model is broken.
Call atrader.var(book, method, horizon) from any strategy. Use VaR as a sizing constraint in backtests. Build risk-aware execution. Same engine, programmatic.
Every position change flows into the VaR engine within a second. Historical VaR recomputes instantly; Monte Carlo runs against precomputed paths refreshed nightly; parametric is closed-form fast.
Daily VaR (95% and 99%), Stress VaR (against picked scenarios), and Conditional VaR. Three independent estimates show the range of plausible answers. Disagreement is signal.
When your VaR jumps materially without a position change (usually because volatility expanded or correlation regime shifted) you get notified. The math is doing the noticing you'd otherwise miss.
Risk Exposure tells you what you have. VaR tells you what it could lose. Together they form the full risk dashboard, and combine into the Risk Pack bundle.
See Risk Exposure →VaR Analysis gives you statistical risk; Scenario Testing gives you historical-event risk. Different lenses on the same question. Use both.
See Scenario Testing →Build a strategy that auto-sizes to maintain a fixed VaR budget. The position size shrinks when volatility expands, grows when it compresses. Discipline by code.
See Strategy Lab →Hedge funds pay six figures a year for VaR systems. We built ours on the same foundations, exposed it through a simple interface, and charge what fits a working trader's monthly budget.
Three VaR methods live. Stress VaR against five historical crises. Conditional VaR. Per-position contribution. Backtest mode. Full API access. Strategy Lab integration.
14 days free. No card. Full app from day one.