In an options trade, both sides of the transaction make a bet on the volatility of the underlying security. While there are several methods for measuring volatility, options traders generally work with two metrics: Historical volatility measures past trading ranges of underlying securities and indexes, while implied volatility gauges expectations for future volatility, which are expressed in options premiums. The combination of these metrics has a direct influence on options' prices, specifically the component of premiums referred to as time value, which often fluctuates with the degree of volatility. Generally speaking, periods when these measurements indicate high volatility tend to benefit options sellers, while low volatility readings benefit buyers.

Historical Volatility

Also referred to as statistical volatility, historical volatility gauges the fluctuations of underlying securities by measuring price changes over predetermined periods of time. This calculation may be based on intraday changes but most often measures movements based on the change from one closing price to the next. Depending on the intended duration of the options trade, historical volatility can be measured in increments ranging from 10 to 180 trading days.

By comparing the percentage changes over longer periods of time, investors can gain insights on relative values for the intended time frames of their options trades. For example, if the average historical volatility is 25% over 180 days and the reading for the preceding 10 days is 45%, a stock is trading with higher-than-normal volatility. Because historical volatility measures past metrics, options traders tend to combine the data with implied volatility, which takes forward-looking readings on options premiums at the time of the trade.

Implied Volatility

By gauging significant imbalances in supply and demand, implied volatility represents the expected fluctuations of an underlying stock or index over a specific time frame. Options premiums are directly correlated with these expectations, rising in price when either excess demand or supply is evident and declining in periods of equilibrium.

The level of supply and demand, which drives implied volatility metrics, can be affected by a variety of factors ranging from market-wide events to news related directly to a single company. For example, if several Wall Street analysts make forecasts three days prior to a quarterly earnings report that a company is going to soundly beat expected earnings, implied volatility and options premiums could increase substantially in the few days preceding the report. Once the earnings are reported, implied volatility is likely to decline in the absence of a subsequent event to drive demand and volatility.

Using Historical and Implied Volatility

In the relationship between these metrics, the historical volatility reading serves as the baseline, while fluctuations in implied volatility define the relative values of options premiums. When the two measures represent similar values, options premiums are generally considered to be fairly valued based on historical norms. Options traders seek the deviations from this state of equilibrium to take advantage of overvalued or undervalued options premiums.

For example, when implied volatility is significantly higher than the average historical levels, options premiums are assumed to be overvalued. Higher-than-average premiums shift the advantage to options writers, who can sell to open positions at inflated premiums indicative of high implied volatility levels. Under these circumstances, the objective is to close positions at a profit as volatility regresses back to average levels and the value of options premiums declines. Using this strategy, traders intend to sell high and buy low.

Options buyers, on the other hand, have an advantage when implied volatility is substantially lower than historical volatility levels, indicating undervalued premiums. In this situation, a return of volatility levels to the baseline average can result in higher premiums when options owners sell to close positions, following the standard trading objective of buying low and selling high.