Estimating Crypto Portfolio VaR with Normal Minute Returns

Summary

The document introduces Value at Risk (VaR) as an estimate of portfolio or position losses over a chosen horizon and confidence level. Its worked example uses minute BTC/USDT closing prices from a stated historical week. It calculates minute log returns, estimates their mean and standard deviation, then uses a normal distribution to estimate loss thresholds at two confidence levels. The example translates those percentage thresholds into dollar losses for a hypothetical investment, illustrating how a trader can express risk in both relative and monetary terms.

The method depends on a strong assumption: returns are normally distributed. The resulting VaR summarizes a quantile threshold, not the largest possible loss, and it does not describe how severe losses may be beyond that threshold. Estimates also depend on the selected sample, time horizon, and market conditions; historical minute returns may not represent future crypto behavior, especially during jumps or stressed liquidity. The article offers a basic illustration rather than a full portfolio model or validation of the distributional assumption.

Key ideas

• VaR combines a time horizon, confidence level, and estimated loss threshold.
• The example estimates minute log-return mean and standard deviation from BTC/USDT data.
• A normal-return assumption is used to derive loss thresholds at two confidence levels.
• VaR does not bound losses beyond its selected quantile or establish future outcomes.
• The estimate depends on sample choice and may understate risks from non-normal market moves.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.