Calculator
Value at Risk (VaR) Calculator
Value at Risk (VaR) Calculator
Value at Risk (95% Confidence)
$1,522.54
90% VaR
$1,179.25
99% VaR
$2,166.4
Risk Analysis
A 95% confidence VaR of $1,522.54 over 1 trading day means that on roughly 1 day in 20 (about 12 days a year), you can expect to lose at least that much. On the worst days of a typical year, actual losses often exceed the 99% VaR — which is why professionals pair VaR with stress tests and position limits.
*Parametric VaR assumes returns follow a normal distribution. Real markets have fat tails - extreme losses occur more often than the model predicts, and VaR says nothing about the size of losses beyond the confidence threshold. Educational only, not financial advice.
Value at Risk: Putting a Number on Your Worst Usual Day
Value at Risk answers the question every investor dreads but rarely quantifies: how much could I lose on a bad day? Expressed as a dollar figure at a given confidence level, VaR says that on 95% of days the portfolio's loss will not exceed that amount - which also means on roughly one day in twenty, it will. Banks, funds and APRA-regulated institutions have used the measure since the 1990s, and the same mathematics runs inside free tools for retail investors who want to size risk before it sizes them. For Australian investors the practical applications are immediate. A 95% daily VaR of $2,000 on a $150,000 ETF portfolio tells you whether your stomach and your liquidity can survive a routine drawdown; a one-month VaR on a concentrated BHP or tech holding tells you whether a single name is dominating your risk budget inside or outside super. VaR also forces honesty about volatility - the difference between a 9% volatility balanced super option and a 32% volatility single miner shows up as a dramatically different potential loss at the same dollar size. The danger of VaR is complacency: it describes the usual bad days, not the extreme ones, which is why every serious risk framework pairs it with stress testing.
Behind the Formula: Volatility, Time and the Z-Score
The parametric VaR formula is VaR = Portfolio Value x (z x sigma_horizon - mu_horizon), where sigma is volatility and mu is expected drift. Annual volatility is first converted to daily volatility by dividing by the square root of 252 trading days - volatility scales with the square root of time because daily moves are approximately independent. For multi-day horizons, daily volatility is then scaled up by the square root of the holding period. The z-score is the multiplier that encodes confidence: 1.28 for 90%, 1.64 for 95% and 2.33 for 99%. Each says how many standard deviations into the loss tail the threshold sits. Expected return over the horizon is subtracted because positive drift offsets part of the volatility-driven loss; over one day the drift is tiny, but over 21 trading days it visibly shrinks the VaR. The whole model assumes normally distributed returns, which understates the probability of extreme losses - real markets have fat tails, as March 2020 demonstrated on the ASX within weeks. That is precisely why this tool pairs the normal-model figure with commentary about tail risk and why a 99% VaR should be treated as a floor on the worst days, not a ceiling.
Expert Insights
VaR Is the Beginning of Risk Management, Not the End
The famous failure mode: in calm markets VaR looks reassuring, then a fat-tail event dwarfs it. The GFC and March 2020 both produced multi-VaR events inside days, and the ASX 200's fall from late February 2020 was faster than any normal-model VaR anticipated. The discipline VaR imposes - measuring risk, setting position limits against it and re-checking regularly - is exactly right. The failure is believing the number when the distribution assumption breaks. Use VaR to size normal risk and stress-test scenarios to bound the extreme ones.
Match the Horizon to Your Decision
A one-day VaR matters if you might need to sell tomorrow; a one-month VaR matters if you are judging money you cannot touch until preservation age anyway. Traders in ASX-listed securities run daily VaR; super accumulators should think monthly or quarterly. The holding-period slider exists because the same portfolio has a very different risk profile at different horizons - volatility compounds with the square root of time, so a month-long VaR is roughly 4.6 times the daily number.
Use VaR to Price Position Concentration
Individual ASX stocks often carry 25-40% volatility - resources names during China-driven swings can exceed it - while a broad index ETF carries around 13-15%. A $10,000 single-stock position contributes more to portfolio VaR than a $25,000 index position. Before adding a concentrated holding, compute its standalone VaR here and ask whether that loss on the worst usual day is acceptable. It converts the abstract anxiety of 'too much in one name' into a concrete dollar test.
Actionable Tips
- 1
Run Your Portfolio's VaR Against Your Cash Buffer
Compare the 95% monthly VaR of your equity holdings against your emergency fund and any offset-account buffer you might raid. If the VaR exceeds the buffer, a single bad month could force you to sell into weakness to cover expenses. The fix is either more cash or less volatility - the number tells you which gap to close first.
- 2
Stress the Volatility Input
Your portfolio's recent realised volatility may understate what a crisis does. Re-run the tool at 1.5 times your volatility input - if the resulting VaR is a number you cannot stomach, your present sizing is not crisis-proof regardless of what today's calmer figure suggests. Australian banks during 2020 moved from mid-teens to 50%-plus annualised volatility within weeks.
- 3
Set a VaR Budget per Holding
Cap each individual position's daily VaR contribution at a fixed dollar amount - say 0.5% of total portfolio value. When a winner grows past the cap, trim it. This mechanical rule keeps single-stock risk from quietly accumulating through inattention, which is the most common way self-managed portfolios become concentrated without anyone deciding to.
Real-World Examples
Marcus Sizes His Employer Stock Concentration
Marcus, an engineer in Perth, had $90,000 of vested employer shares inside a $320,000 portfolio. Running the tool at the stock's 36% volatility showed a 95% monthly VaR near $16,000 for the single position - far beyond his cash buffer. He sold down to $45,000, diversifying into index ETFs, and brought the position's monthly VaR down to under $8,000 without abandoning his equity exposure.
Dana Learns Her Bond Fund Wasn't Risk-Free
Dana, 61 and recently retired in Adelaide, parked her rollover in a long-duration bond fund expecting stability. At 9% volatility the tool showed a 95% one-month VaR of roughly $11,000 on her $300,000 balance - real money in the same months rate volatility spiked. She shifted half into shorter-duration holdings and cash, cutting the fund's contribution to portfolio VaR roughly in half.
The Chen Family Sets a Rule for Crypto
The Chens allowed themselves a 5% crypto sleeve beside their ASX ETFs, but at 70% volatility the tool showed that slice alone carried a 95% monthly VaR of nearly $6,000 on just $8,500 of holdings - roughly fifteen times the VaR of the same dollars in an index fund. They capped the position at 2.5%, a decision they could defend with a number rather than a feeling.
Glossary of Terms
- Value at Risk (VaR)
- The maximum expected loss over a given horizon at a specified confidence level - a 95% 1-day VaR of $2,000 means worse losses are expected on fewer than 5% of days.
- Confidence Level
- The probability threshold the VaR statement covers - 95% means the loss threshold is breached about one day in twenty.
- Square-Root-of-Time Rule
- The convention that volatility scales with the square root of the time horizon, used to convert annual volatility to daily or multi-day figures.
Frequently Asked Questions
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Ivy Sinclair-Wren
Financial Chaos Analyst
Ivy Sinclair-Wren is a Financial Chaos Analyst covering investing, AI, wealth psychology, and the emotional consequences of opening finance apps during market crashes. Based in Melbourne, she specializes in demystifying the Australian tax code and helping users navigate the intersection of spreadsheet logic and human irrationality.