Volatility Explained

Historical and implied, and the gap between them

Historical volatility is calculated from prices that have already happened. Implied volatility is extracted from option prices and represents what the market is currently charging to insure against movement, so it is forward-looking.

The gap between them is informative. Implied volatility usually sits above realised volatility, because option sellers charge a premium for taking on uncertainty. When implied rises sharply above historical, the market is pricing an event: an earnings date, a regulatory decision, a court ruling. When it collapses back afterwards, positions that were expensive to hold lose value even if the stock does exactly what you expected, which is the mechanism that catches people buying options around earnings.

Volatility clusters, which is why yesterday matters

Volatility is not randomly distributed through time. Large moves are followed by large moves, and quiet periods are followed by quiet periods. This clustering is one of the most robust statistical features of financial markets and it has two practical consequences.

First, a volatility measurement taken today is a reasonable estimate for the next few days and a poor one for next quarter. Second, a stop distance set during a calm period is inside the noise once volatility expands, so a system that worked for months starts getting stopped out on entries that would previously have survived. The fix is to measure volatility continuously and let the stop distance float with it, which is what average true range based stops do.

The drag volatility puts on a compounding account

Dispersion has an arithmetic cost independent of direction. Gain 20% then lose 20% and you are not flat: 1.20 × 0.80 is 0.96, a 4% loss. Repeat that pair five times and the account is at 0.96 to the power of five, which is 0.815, down 18.5%, while the average of the returns reads as zero.

The higher the volatility, the larger this drag. That is why two strategies with the same average return and different volatility do not produce the same account balance, and why reducing swings improves compounding even when it lowers the average return. Run the sequence through the drawdown calculator to see how quickly the recovery requirement grows.

Where volatility becomes a reason to stand aside

High volatility widens spreads, thins depth, and makes slippage on stops worse, so the cost of trading rises at exactly the moment the price range looks most attractive. It also compresses decision time, which is the condition under which most discretionary errors happen.

The practical rule used by many is to cut size rather than to avoid volatile instruments entirely, and to have a threshold beyond which no new position is opened at all. Both belong in a written plan, since the whole point is to decide before the day arrives rather than during it. The risk management guide sets out how those limits fit together at account level.