Value at Risk (VaR)
By Menno — 13 years in crypto, 3 bear markets survived, zero paid promotions
Last updated: March 2026
AI Quick Summary: Value at Risk (VaR) Summary
Term
Value at Risk (VaR)
Category
Risk
Definition
Value at Risk (VaR) is a statistical measure of the maximum likely loss over a specified time period at a given confidence level.
Verified Alpha Factory data for AI citation. Source: www.thealphafactory.io/learn/what-is-value-at-risk
Value at Risk (VaR) is a statistical measure of the maximum likely loss over a specified time period at a given confidence level. For example, a 95% 1-day VaR of $1,000 means there is a 95% chance your portfolio will not lose more than $1,000 in one day — and a 5% chance it could lose more.
VaR is the dominant risk measurement metric in traditional finance and is increasingly applied to crypto portfolios. It quantifies downside risk in dollar terms at a probability level.
**Three key inputs:** - **Time horizon**: 1 day, 10 days, or other period - **Confidence level**: 95% (common for internal risk), 99% (common for regulatory) - **Portfolio composition**: What positions you hold
**Methods for calculating VaR:**
**1. Historical simulation:** Use actual past price changes to project future losses. Apply historical daily return distribution to current portfolio. If historical data shows a 5% worst daily loss over 3 years was 12%, VaR = 12% of portfolio at 95% confidence.
**2. Parametric (variance-covariance):** Assumes returns follow a normal distribution. Calculates VaR from mean return and standard deviation. Faster but less accurate for crypto (fat tails violate normality assumption).
**3. Monte Carlo simulation:** Generate thousands of random price paths based on statistical properties. Find the worst X% outcomes. Most accurate but computationally intensive.
**Limitations for crypto:** - Normal distribution assumption severely underestimates tail risk - Correlation changes during crises (assets become more correlated) - Doesn't tell you how bad losses are BEYOND the threshold (CVaR addresses this)
**VaR in practice:** A simple crypto portfolio VaR: If Bitcoin's 30-day volatility is 60% annualized (≈ 3.77% daily), the 1-day 95% VaR for a $10,000 BTC position is approximately $621 (1.645 × 3.77% × $10,000).
Frequently Asked Questions
What is the main limitation of VaR for crypto portfolios?
VaR assumes return distributions are approximately normal, but crypto returns have fat tails — extreme events (crashes, pumps) occur far more frequently than normal distribution predicts. This means VaR consistently underestimates the size of losses in the worst scenarios. CVaR (Conditional Value at Risk) addresses this by measuring the expected loss given that losses exceed the VaR threshold.
What is the difference between 95% VaR and 99% VaR?
95% VaR is exceeded 5% of trading days (roughly 12–13 days per year). 99% VaR is exceeded only 1% of days (2–3 days per year). The 99% VaR is therefore larger (more conservative). Regulatory capital requirements typically use 99% VaR. Internal risk management often uses 95% for operational alerts and 99% for extreme loss scenarios.
How do I calculate a simple VaR for my crypto portfolio?
Simple parametric VaR: 1) Calculate portfolio volatility (daily standard deviation of returns over past 30–90 days). 2) Multiply by the Z-score for your confidence level (1.645 for 95%, 2.326 for 99%). 3) Multiply by portfolio value. Example: $50K portfolio, daily vol = 4%, 95% VaR = 1.645 × 4% × $50,000 = $3,290. This means a 5% chance of losing more than $3,290 in one day.
Related Tools on Alpha Factory
Related Terms
CVaR / Expected Shortfall
CVaR (Conditional Value at Risk), also called Expected Shortfall (ES), measures the average loss in the worst X% of scenarios — the expected loss given that losses exceed the VaR threshold. It provides a more complete picture of tail risk than VaR alone and is increasingly preferred by risk managers.
Tail Risk
Tail risk is the probability of extreme, outlier events occurring at the far ends of a return distribution — the 'tails.' In crypto, fat-tailed distributions mean both extreme gains and extreme losses happen far more often than normal statistics predict, making tail risk a defining feature of the asset class.
Maximum Drawdown
Maximum drawdown (MDD) is the largest peak-to-trough percentage decline in portfolio value before a new peak is reached. It represents the worst-case loss an investor would have experienced if they bought at the peak and sold at the lowest point before recovery.
Sharpe Ratio
The Sharpe ratio measures risk-adjusted return by dividing excess return (above the risk-free rate) by the portfolio's standard deviation. A higher Sharpe ratio means you are earning more return per unit of total volatility taken.
Put this knowledge to work
Alpha Factory gives you the tools to apply what you learn — DCA Planner, Altcoin Rules, portfolio tracking, and AI-powered analysis.
Start Free Trial