Volatility Skew — What Is It And How Can I Use It?
Traders say that volatilities are skewed when the options of a given asset trade at increasing or decreasing levels of implied volatility as you move through the strikes.*
I’ll illustrate using a situation that existed in the Gold market in September 1999. (The most significant skew situations happen in the commodities. However, skews also happen in securities and index options, and the principles discussed here apply in these markets just as well.)
The Gold situation really was an outstanding opportunity. It shows what can be done using the dimension of volatility — a dimension only options can provide.
On September 27, 1999, 15 European banks announced that they would hold their gold. Suddenly there was a stampede of interest from buyers, and the shorts covered. Gold soared 29% in a few days, and then backed off a bit.
Some believed gold had begun a new bull phase. Others thought it would just gradually slide back down. However, there was a remarkable opportunity to make money in gold options no matter what gold did from that point on.
Checking gold option volatilities, I noticed that there was a large skew at the time: the out-of-the-money calls were trading at much higher MIV’s (market implied volatilities) than at-the-money calls. This presented an opportunity to construct a position with favorable odds. One example of a (fairly aggressive) position that takes advantage of this skew is in Figure 1.
The position is selling 20 far out-of-the-money calls and buying one at-the-money call to hedge. The single long option overcomes the negative delta of the 20 short options, giving us a net positive delta. This is important because it gives us breathing room in case gold starts to move up again. The one thing that could ruin this position is gold moving much higher, and it is important that we be able to respond to such a move by controlling our risk. There is room for gold to move up some without requiring any action, but beyond a certain point we might need to trim our short option position or add further long options as the underlying continues to move up.
Figure 2 shows the theoretical performance of this amazing position. It is profitable across a wide range of underlying prices. If gold goes nowhere or down, we make $4,000. We make a bit more if gold moves up modestly. Potential losses occur at a more than two standard deviation move to the upside.
Note that while the Graphic Analysis may seem to indicate that the probability of profit is 100% (based on the remote possibility of the commodity going above 400), I would not be that optimistic. The program’s projection is based on recent volatility readings, but years of experience in commodities tells me there might be something like a 5% chance of gold going above 400, and mentally that’s the number I’m going to use. It’s better to be conservative.
So what does that 5% mean — practically speaking? Nothing, really, at the time the position is put on. All it means is that I recognize that I’m playing with fire. If gold begins a sustained move upward, climbing above, say, 370, I need to be prepared to take action. Otherwise a fabulous trade could quickly turn into financial ruin.
Some may want to consider starting out with a less aggressive position. Rather than 20-to-1, you could use 10-to-1 or even 5-to-1 and still have a real good trade.
Interestingly, an almost identical position could have been placed in silver at the same time. Silver jumped sympathetically with gold, and its options also had skewed volatilities. One could make a case for doing this trade in silver rather than in gold for the simple reason that silver did not have a fundamental reason to go up. (The banks’ recent decision about gold had nothing to do with silver.)
*What causes volatility skew? It’s simple really. Skew happens when traders believe that if the price of the underlying could move a little, it could move a lot. In other words, they believe that some distribution other than the lognormal distribution applies at the current time. But rather than using a different distribution in their option pricing models, they allow their option pricing models to continue to use the lognormal distribution and apply different volatility numbers to the options strike by strike. It may not be the best approach, but it works.