Value at Risk (VaR) Singapore: A Guide for Retail Investors
Value at Risk (VaR) is a statistical measure that estimates the maximum loss a portfolio could suffer over a given time period at a specific confidence level. While traditionally used by financial institutions, VaR concepts are increasingly relevant to sophisticated Singapore retail investors managing significant portfolios. This is educational content only.
How VaR Is Calculated: Three Methods
VaR is expressed as: “With X% confidence, the portfolio will not lose more than $Y over N days.” Example: “95% 1-day VaR = SGD $15,000” means there is a 5% probability of losing more than $15,000 in a single day. Three methods: (1) Historical VaR — uses actual historical returns; simple but backward-looking. (2) Parametric VaR — assumes normal distribution; fast but underestimates tail risk. (3) Monte Carlo VaR — simulates thousands of random scenarios; most flexible but computationally intensive.
VaR for Singapore Retail Investors: Practical Applications
Position sizing: if a single S-REIT is 20% of your portfolio and has 40% historical maximum drawdown, you’re exposed to an 8% portfolio loss from one position — VaR-style thinking helps size positions more conservatively. Portfolio stress testing: “What happens if S-REITs drop 30% like in COVID-19?” is informal VaR analysis. Risk communication: when discussing risk with your advisor at Endowus or Syfe, ask how they measure downside risk — VaR or CVaR are standard institutional metrics. Related: Singapore REIT ETF Guide.
Limitations of Value at Risk
VaR does not capture tail risk beyond the confidence level — 95% VaR tells you nothing about how bad losses can be in the 5% tail (CVaR/Expected Shortfall is more informative). Parametric VaR significantly underestimates losses during market dislocations when distributions become fat-tailed (GFC, COVID-19). VaR assumes you can sell at market prices — for less liquid S-REITs or small-cap stocks, actual losses during forced liquidation can exceed VaR estimates. Correlations are assumed stable but spike during crises.