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Value at Risk VaR

⬢ LIVELLO 2Tecniche
Alto
Impatto sullo stipendio
10 mesi
Tempo di apprendimento
Difficile
Difficoltà
2
Carriere
In sintesi

Value at Risk (VaR) is a statistical measure of portfolio risk: the maximum loss under normal market conditions at a given confidence level (95%, 99%). Used by risk managers, traders, and financial institutions quantifying portfolio risk, setting risk limits, and stress-testing strategies. Salary: $120–180k. Learn in 10–14 weeks. Sits alongside Risk Management, Portfolio Theory, and Statistical Modeling.

Cos'è Value at Risk VaR

Value at Risk (VaR) is a statistical measure of portfolio risk: the maximum loss a portfolio is likely to suffer under normal market conditions at a given confidence level (e.g., 95%). If a portfolio has a 95% VaR of $1M, there's a 95% chance it won't lose more than $1M tomorrow (or chosen period). VaR quantifies risk; it helps risk managers set capital reserves and risk limits. You calculate VaR using market data, returns distributions, and statistical models. Common methods: historical simulation (use past returns), parametric (assume normal distribution), Monte Carlo (simulate thousands of scenarios).

🔧 STRUMENTI ED ECOSISTEMA
Python for VaR modeling (NumPy, SciPy, pandas)Statistical software (R, STATA)Risk systems (RiskMetrics, Axioma, Numerix)Market data APIsExcel for modelingTime series analysis

💰 Stipendio per regione

RegioneLivello baseMidLivello esperto
USA$100k$160k$250k
UK£60k£95k£160k
EU€68k€105k€175k
CANADAC$95kC$150kC$240k

🎯 Carriere che usano Value at Risk VaR

Product Manager
Risk Analyst

❓ Domande frequenti

What does '95% VaR of $1M' mean?
There's a 95% chance the portfolio won't lose more than $1M over the next day (or period). Conversely, 5% chance of losing MORE than $1M. Used to set capital reserves.
What are VaR methods: historical, parametric, Monte Carlo?
Historical: use past returns to estimate future losses. Parametric (variance-covariance): assume normal distribution; calculate based on mean/std dev. Monte Carlo: simulate thousands of scenarios. Each has pros/cons.
What's the difference between VaR and expected shortfall (CVaR)?
VaR = max loss at 95% confidence. Expected shortfall (CVaR) = average loss in worst 5% of cases. CVaR is more conservative, better for extreme risks.
Does VaR prevent losses?
No. VaR measures risk; it doesn't prevent losses. It helps set risk limits and capital reserves. Risk limits prevent exceeding your VaR threshold.
Can VaR models be wrong?
Yes. VaR assumes normal market conditions. Tail events (crashes, black swans) break assumptions. Stress testing and scenario analysis complement VaR.

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