When I traded iron condors, I tended to enter about the same number of days before expiration each cycle. Because I had traded iron condors on the same vehicles so long, I tended to know about how much credit I could expect to take in when I sold them, depending on the implied volatilities. I didn't need a spreadsheet. Because I was so familiar with my vehicle and my underlying, I knew when I was earning a good fee for the risk I was taking, and when I wasn't and should pass up the trade.
I don't know that about the butterflies I'm trading now. Not yet. For the August cycle, I entered 8 contracts of butterflies. I had watched the price and the fills over a couple of days. I entered my first order below the mid-price or mark, between the bid and ask. Then I gradually worked the price higher, trying the two exchanges at which I usually get the best fills on complex orders on the RUT, the ISE and the CBOE. I was patient, letting orders sit for a while as I worked my offer higher. My trade journal notes tell me that I worked the order from 8:48:48 am until 9:22:48 until I finally got a fill. I was filled at $12.45. I knew it to be the best fill I could get at the time because I'd worked the order so patiently.
About thirty minutes later, trading compatriots got filled on the same butterfly. They both got filled at $12.25. In the interim between my fill and theirs, there was enough of a shift in the price/implied volatilities combination to let them in at a lower price. Since I had an eight-lot butterfly order that meant that I had paid 8($12.45 - $12.25 x 100) = $160 more than I might have been able to pay for that butterfly position if I'd been plying my trade thirty minutes later.
I know for sure that I got the best price that I personally was able to get at the time that I entered my butterfly. However, I hadn't yet developed the same level knowledge of what constituted a good price for the butterflies on that day at the implied volatility level that I was seeing. If I'd had that knowledge, I could have elected not to enter the butterfly trade if I didn't get filled at the price I wanted and to wait until pricing was more favorable.
As I first roughed out this article, that butterfly position's theoretical profit was up 5.69 percent of the maximum profit in the trade after round-trip commissions. I would have been making 6.41 percent profit if I'd had that extra $200. As it turned out, that butterfly trade is forgiving enough to overcome my entry, and I have since closed it out for a bigger profit of 8.53 percent of the maximum margin ever used by the trade at any point.
However, my experience entering the trade illustrates the importance of familiarizing yourself with options prices for your strategy on your preferred vehicle. You might be able to tell that I'm not a fan of switching strategies or underlyings for your main trades. I occasionally trade debit spreads on underlyings that have seen unusual volume, setting up the trade so that I have about a 1:1 risk-to-reward ratio, but that's with speculative lotto money. I trade those trades in a separate account from my income trades.
For those income trades, a butterfly trade, I'm still trading much smaller than I used to trade. I'll size up gradually as I gain that same instinctive and experience-honed knowledge of correct pricing. Learning from your own experiences and those of others is something that all options traders can do as a first tool to improve their trading successes.
The easiest and lowest tech method is to jot down the price of your simulated trade, the days to expiration, implied volatilities, the price of option position and perhaps the time of day, and to do this over a period of time. Of course, some organization on a spreadsheet allows for comparing and contrasting prices or at least searching for prices under certain conditions. How were RUT butterflies priced when the RVX was between 22-25 with 56-58 days to expiration, I might want to know.
Even without organizing the collected data in this matter, the act of writing down the prices and other parameters reinforces observations and helps retain the information.
Those with Excel skills can import prices from some brokerages. Some traders work with DDE feed on think-or-swim to produce spreadsheets that update prices. They may watch prices for several days before opening a new trade, for example, and will have a good understanding of where current prices range. Savvy techies can export delayed quotes for all options and LEAPS for an underlying in comma delimited text format from the CBOE, although the CBOE points to a possible limitation to manipulating data once its in the spreadsheet format. The CBOE offers a possible workaround, but that's beyond my technological skills.
The CBOE offers another possibility for price discovery. It's both more interesting and more hit-and-miss. The CBOE'S "COBWeb" allows registrants to look at "price and size of CBOE top-of-the-book resting complex spread orders in real-time." It's free to registrants and can be found at under the "Tools" tab on the CBOE site. It is available only during market hours, of course.
Snapshot of a Portion of CBOE's COBWeb on July 24:
This snapshot shows that someone or some institution was bidding 5.38 for a 10-contract calendar trade on the RUT, selling AUG12 830 puts and buying SEP12 830 puts. At the time this was snapped, the RUT hovered near 770, which made the trade a bit curious. You won't always find the trade you're interested in trading listed on the complex order book. I doubt the trader trying to buy this calendar found too many orders like this one to follow over the preceding days or hours. Still, it's a free tool available to all traders who want to learn something about order flow and typical prices. It is not, however, a tool that I utilize with regularity, but I am attempting to watch it with the goal of learning something about the trend of traders' beliefs about the next market direction.
As many of you know, brokerage platform think-or-swim has some of the best analytics for traders, although that doesn't mean that the platform is the best platform for all traders. Pricing structure, the stability of the platform, vehicles available for trading, accessibility of support staff, and many other such factors go into any decision when choosing a trading platform. However, one of the tools that TOS has that will help me get up to speed quicker on learning my strategy on my underlying includes the ability to graph the price of a strategy over time. I'm not talking about the expiration profit-and-loss graph of a strategy such as the butterfly, which is the kind of graph we're usually viewing after we've entered a trade and are managing it. I'm talking about a graph of actual fill prices on the trade over a period of time.
In the graph below, I've chosen the "area" view of an IBM JUL12 195 call over a 30-day period so that I can illustrate how the price of that call has changed. To illustrate this type of graph, I chose a simple strategy employing a liquid enough option that there would be many price points to view. Volume shows beneath the area graph. I've displayed the price compared to the VIX, but of course I could also have displayed it compared to IBM's price.
30-Day Chart of IBM JUL12 195 Call Compared to VIX, Snapped July 19, 2012:
Such a chart would provide a quick method of gaining some insight into the price of a strategy at a certain point before expiration or a certain price point of the underlying or, in this case, with respect to the VIX. Such charts are available for complex strategies, too. I can and sometimes do chart butterfly prices and watch how they move over time.
While I don't know of other platforms that allow this kind of charting on an option strategy, that doesn't mean that it's not available. Ask your support staff at your platform if it's possible to do this or otherwise gain insight into the prices fluctuations over time or versus implied volatilities or other such measures.
Tracking prices by hand and good old experience are still two of the best tools, no matter what impressive charting capabilities your brokerage might provide.