In yesterday’s post, I wrote a little bit about what I’ve learned while researching an options strategy of trading long puts against high volatility equities. Today, I’m providing a concrete example of the strategy and my thought processes along the way.
The underlying for this example is AIG. I’ve continued to look for them as the underlying because this strategy is predicated on using an underlying with high volatility and the 30-day historic volatility for AIG has been above 90% since I started thinking about this strategy. About Tuesday of last week, I did an analysis of where AIG’s price was, what Nov09 puts were trading for, and decided to set a limit buy order for IKG WR at $4.30 as my entry point into the strategy. Let’s discuss a few of those phrases.
First, why Nov09 puts? Mostly because I had little confidence AIG would have the price swings I was aiming for prior to October expiration which was last Friday. But also because I didn’t want to add the additional risk of having to overcome the effects of rapidly decaying time premium. Much simpler to give myself a longer time period as a safety valve should I need to own the puts for longer than I was hoping.
Second, how did I arrive at a $4.30 limit order? This came about by doing calculations using the “greeks” delta and gamma. As a refresher, delta is the rate of change in an option’s price as a function of the underlying’s price change. And gamma is the rate of change in an option’s delta as a function of the underlying’s price change. To put these to use, I started by picking an underlying price that I thought would represent an achievable local high due to volatility. Which meant picking a probability level, I used 75%, a time period, I used 2 days, and then figuring out the price as a function of historic volatility. My equations told me to aim for a price of about $45.50. Now the greeks come into play. Using the difference between the current price and that price, I could figure out how much a given put option’s price would likely change as a result of changes in the underlying’s price.
This calculation generated a table where one column is the underlying’s price, another is the probability of hitting that price given the historic volatility of the underlying, and the others are the prices of various puts that I was considering. Now I simply scanned the table looking for a put who’s entry price fit within my capital requirements and where profit was maximized given a decent probability of hitting a low in the underlying. Because the delta and gamma will vary for each possible put, they have different responses to the same changes in the underlying’s price, and thus differences in how much profit can be earned given an equal drop in the underlying’s share price. Think of this as where you’re balancing risk vs. reward vs. capital requirements.
In the end, I decided to use the Nov09 $44 put on AIG. My calculations told me I had a 75% chance of entering if I set a BTO limit order at $4.30, and a roughly similar chance of exiting if I aimed for about $100 in profit before taking commissions into account. This meant using capital of little more than $430 on entry, and using a limit order to sell if the puts hit $5.30. Here’s the overall summary of the trades as actually completed. As usual, I’m including all commissions and fees and thus my numbers go out to fractions of a cent when shown as prices per share.
IKG WR Long Put: Critical dates and Summary
2009.10.14: Place limit order to BTO 1 IKG WR (Nov09 $44) @ $4.30
2009.10.15: BTO 1 IKG WR (Nov09 $44) @ $4.356
2009.10.15: Place contingent order STC 1 IKG WR (if IKG WR bid >= $5.30)
2009.10.15: Place contingent order STC 1 IKG WR (if IKG WR bid <= $3.30)
2009.10.19: STC 1 IKG WR (Nov09 $44) @ $5.2438
Days position held: 4
Capital investment: $435.60
Net Profit: $88.78
Percent return: 20.38%
Annualized yield: >>1000.00%