Last week I talked about the Bull Call Spread. The way our sample trade worked out deserved another article.
This is usually thought of as a bullish strategy, meaning one that needs a rising stock price to profit. That is generally true if one or both options are out of the money. We looked at using the Bull Call Spread as more of a neutral strategy. Instead of a trade that relies on price going up, I showed how by selecting different strikes, it could be transformed into an income-generating strategy that is based on time decay. These two strategies have the same name, but in function they are as different as ice cream and ice hockey.
Last week’s example was Gannett Corp (GCI). The stock was at $19.90 and our outlook was neutral to bullish. We felt that it was very unlikely to drop below $18.50 – it would have had to break through multiple levels of demand to do so. We put on a bullish debit vertical spread using the 16 and 18 strikes, (Buying the July 16 calls for $4.00 and selling the July 18 calls for $2.30). Both options were in the money, and we expected both to remain in the money until expiration. The spread cost $1.70, and had a maximum payoff of $.30. For us to collect our maximum payoff, all that GCI had to do was not drop below the $18 short call strike. This would have been a $2 drop through strong demand. As long as that didn’t happen, we’d make $.30 on $1.70, or about a 17.6% profit in 37 days (174% annualized).
There was a small, but non-zero, chance that we could sustain a relatively very large loss, though – the entire $1.70 cost of the spread. This would occur if GCI were to be below $16 at the July expiration, and we were still in the position. To avoid this, we planned to exit long before that happened – unwinding the position if GCI dropped below our $18 strike. We were still exposed, though, to a sudden overnight gap opening at a price far below $18. In that (unlikely) case we could lose all or nearly all of the $1.70 cost.
Weighing the probabilities of such a large and violent drop, we decided that the trade was worthwhile, and we entered it.
As it turned out, the trade worked out quicker than we could have imagined, giving us almost all our profit in a single day! But In doing so, it provides a lesson about probabilities that we need to take to heart.
We took the trade on June 12. The next morning Gannett announced that it was acquiring another company. The acquisition would not only drastically expand Gannett’s market, but it was expected to significantly increase reported earnings immediately. In response, GCI’s stock shot up from $19.95 to $26.75, closing out the day at $26.60. This caused both the $16 and the $18 calls to be so far in the money, that both lost all their time value and were trading just pennies away from their very large intrinsic values. With GCI at $26.60, the 16 call had $10.60 worth of intrinsic value and the 18 call had $8.60. Their actual prices were very close to these amounts, and the spread could have been closed out almost any time during that day or the following day for a net credit of $1.95, just $.05 short of its maximum profit. The position had gained 25 cents out of its 30-cent maximum.
At that point we were in the position of deciding whether to take our 25-cent profit and redeploy our capital elsewhere, or to wait an additional 36 days to collect that last 5 cents. Taking the money was the obvious decision. It resulted in a ridiculously high rate of return of 14.7% ($.25 / $1.70) in a single day, and an annualized rate too big to bother calculating.
This quick win was partly because we were on the right side of the trade. I wish I could say it was all due to skill and laser-sharp analysis, but the fact that it happened so fast was pure luck. (Now if we had been really lucky, we would have just bought calls, and had a profit that was not only fast, but big!) The fact that GCI came up on a scan of stocks with much higher than average implied volatility provided a clue that something was up, but we didn’t know what. We had no reason to expect GCI to move by 35% in one day. This was a 4-standard-deviation move. Statistically that should happen only about 7 times in a million trading days, or about once every 62 years – literally, once in a lifetime.
But remember what that “statistical” probability estimate is based on. It takes into account the historical rate of change in the price of the stock, and based on that, calculates how unlikely any future rate of change is. The farther away from the past observed rate, the less likely. In other words, this type of probability calculation assumes a linear world where things change smoothly. The vast majority of the time, that model of the world is close enough to reality to be useful. That’s a good thing, or there would not be an option market at all.
That linear-thinking model, however, breaks down when there are discontinuities. By definition, probability estimates based on past observations can not comprehend an event of a magnitude that has never happened before. In fact, they’re stumped by a change that‘s bigger than whatever has happened in just the last 30 days, or whatever their look-back period is (conventionally for stock volatility, it’s 30 days).
Here, that once-in-a lifetime event happened. In this case, we were the winners. But what if it had gone the other way? A once-in-a-lifetime event that’s bad can certainly happen too. A similar move downward would have taken GCI down to about $13.10. At that price, our $16/18 call spread would have been worth about a nickel more than zero, instead of a nickel less than its maximum. We would have lost $1.65 out of $1.70, instead of making $.25 on the same $1.70. Instead of a one-day 14.7% gain, we would have had a one-day 97% loss.
The lesson is: things that statistically “just can’t happen,” do happen in financial markets. Betting a large amount on any single unlikely event’s not happening can be costly.
This sobering thought is one that we have to keep in mind when doing trades of this nature. That is, trades with a high probability of profit, but a low reward-to-risk ratio. Those trades rely on the unlikelihood of a big adverse move, to make their low reward-to-risk worthwhile. That describes many popular credit options trades, as well as in-the-money debit verticals like this one. Most of the time, they work out fine. Occasionally, they will lose big.
The best defenses against the big losses with these trades are:
Most important, be on the right side of the trade in the first place, by accurately gauging the underlying’s Supply and Demand zones. If your trade depends on price not dropping or rising too far, make sure there is a quality Supply or Demand level that will keep it from doing that, no matter how low the probability estimate is.
Don’t bet the farm on any one trade. If its maximum loss, no matter how unlikely, would significantly hurt your account, you can’t afford it. Scale back or pass.
So, we had a nice win that was good in itself. It also gave us the opportunity to explore some aspects of probability that are important to remember, and also to reinforce the idea that even with “neutral” trades, accurately identifying Supply and Demand zones is the key.
For comments or questions on this article, contact me at firstname.lastname@example.org.