'Volatility' and 'risk' are the same thing in financial jargon. We measure volatility in the form of standard deviation (NYSE:SD) in annual returns. Volatility is always measured in terms of standard deviation in return. Standard deviation in return is a measure of risk--the size of 'normal' deviations in return from the mean. If SD in return is low, the volatility in that asset is low, and vice versa. It is important to manage total portfolio standard deviation if you want to limit potential loss. The value of at-the-money options is mostly determined by estimates of future volatility / risk. The markets in options can be used as the basis for figuring out a consensus estimate of the future risks in an asset. This is one of the great things about ETF's in portfolio management---many have options markets that trade on them.
So a reasonable way to determine an estimate for future volatility in a stock or fund is to look at options prices and back out the implied volatility. If you have a portfolio simulation tool, you can run the simulation, price options from the simulation, and (if levels agree), you can look at the projected market volatility in the portfolio model. This is a good way to sanity check a Monte Carlo model, as well as providing insight. We have compared put and call option prices on SPY and QQQQ in the market to simulated prices from Quantext’s Retirement Planner (QRP), a Monte Carlo (NYSE:MC) portfolio simulation. Results are for SPY are shown below:
The same analysis has been performed for QQQQ (with full results in our paper). The agreement between options prices simulated within the Monte Carlo portfolio simulation and the market prices of the options are quite close, but there are also some interesting differences.
Both QQQQ and SPY options are consistent with market prices. The projected future volatility in the MC model is substantially higher than the volatility that we have seen in the markets for the last several years. The options markets clearly are pricing in expectations that the next two to three years will be substantially more volatile than the most recent three years. That said, the projected volatility is closer to long-term historical levels in these markets.
[This is a summary of a full paper that is available here.]