In a recent post I was discussing the question of whether it is generally better to be a buyer or seller of options. My conclusion was that theoretically there is no inherent advantage in either buying or selling, if options are priced correctly; it depends on the situation.
The oft repeated mantra out there in options land is to sell when options are overpriced and to buy when underpriced. Wise advice, but of course the sixty four thousand dollar question is - when is an option overpriced and when is it underpriced?
Of course if you know your option theory, you'll know the great variable in option pricing is volatility, all other inputs being known definitively.
We can measure the volatility of the underlying by looking back over a set number of days and applying a formula to determine the statistical volatility over that time frame. This is also definitive, but unfortunately may bear no relation to the volatility realized over the same number of days henceforth.
This is the volatility option traders want to know, future volatility. As it lies in the future, it cannot be known. Therefore the market collectively makes a forecast of future volatility and prices options accordingly, hence the measure derived by a little bit of algebra, 'implied volatility'.
Some folks suggest comparing implied volatility to statistical volatility to determine over or under valuation. I say that's naive. As discussed, statistical volatility looks backward, but implied volatility looks forward and as I've already pointed out, the volatility realized going forward can be markedly different to the preceding period.
What the individual trader must therefore do, is to make a call on future volatility and decide whether options are fairly valued or not, according to his or her own projections. Statistical volatility may be a tool that can be used in this analysis, but ultimately he who guesses best, wins.
Of course there are other dynamics at play depending on the specific strategy which may sink or save any one position, but good forecasters of volatility have a huge edge.
In the next post, I want to have a look at how accurately 'the market' forecasts volatility.