Skip to main content

Two Earnings Plays for Tomorrow...

We're officially in earnings season and here are two opportunities that stick out to me for tomorrow...

Both of these names are large caps so I don't like super aggressive strategies like ratio backspreads.

  1. Bearish Biogen (BIIB):
    • Long 41 shares at $265.81
    • Long 1 November $265 put at $14.90
    • Long 1 November $255 put at $10.60
    • Long 1 November $245 put at $7.20
Anytime you're trading options with elevated levels of implied volatility it will be difficult to get a lot of convexity and this trade maxes out at 5.72x with a 23% move.  However, the structure manages to get the downside breakeven price up to about $240 which is only about 2.5 ATRs away.  The expected value on this trade is anywhere between $600 and $1,000 using projected vol and $1,400 to $2,100 using implied vol.


      2. Long Vol Kinder Morgan (KMI):
    • Short shares 290 at $31.88
    • Long 6 November $32 calls at $0.78
There's something very interesting going on with Kinder Morgan options ahead of tomorrow's earnings report.  The put options are reflecting the typical spike in implied vol (the November ATM put has an implied vol of 36% vs. a projected period vol of roughly 21%) but the call options are showing as being insanely cheap (the November ATM call has an implied vol of 21.5%).  Put/call parity is supposed to prevent this type of pricing anomaly from arising but for whatever reason it doesn't seem to hold here.  This position has a straddle type of payout structure (straddles are usually a terrible trading strategy) but the breakeven prices are only 1.7x ATR on either side of the current price.  Even if the company reports bad earnings, a layoff announcement (which is expected) could prompt a recovery rally and those cheap call options could really pay off.

Here's what the payoff vs. price projection looks like:

Comments

Popular posts from this blog

Modeling Credit Risk...

     Here's a link to a presentation I gave back in August on modeling credit risk.  If anyone would like a copy of the slides, go ahead and drop me a line... https://www.gotostage.com/channel/39b3bd2dd467480a8200e7468c765143/recording/37684fe4e655449f9b473ec796241567/watch      Timeline of the presentation: Presentation Begins:                                                                0:58:00 Logistic Regression:                                     ...

Variable Types for Principal Component & Factor Modeling

TRANSFORMING RAW DATA INTO INSIGHT & ACTIONABLE INFORMATION After reading the book Moneyball for the first time, I built a factor model in hopes of finding a way to finally be competitive in my fantasy baseball league - which I had consistently been terrible at.  It worked immediately.  By taking raw data and turning it into actionable information, I was able to solve a problem that had long perplexed me.  It was like discovering a new power.  What else could I do with this? Today, I build models for everything and have come a long way since that first simple spreadsheet but still use a lot of the same concepts. To build a traditional factor model, you would regress a dependent variable against a series of independent variables and use the resulting beta coefficients as the factor weights... assuming your resulting r-squared and t-test showed a meaningful relationship of course. Variables typically fall into one of two categories... continuous or dichotomous....

Convexity as a Technical Indicator - Applications of the Second Derivative...

WHAT'S IN A NAME? In investment parlance, the term 'convexity' is typically reserved for the topic of fixed income risk; especially in regards to debt with embedded optionality where negative convexity is a prominent pricing factor.  However, it is important to recall that 'convexity' (or 'concavity', for that matter) is a mathematical measurement used to describe the second derivative of a continuous, nonlinear function on an interval. The issue with confining the term to a single connotation is that - for better or worse - investment tools have become increasingly nonlinear since the days of the 60/40 model and convexity is present in a number of applications.  The extent to which it has been circumscribed to a single asset class is evident in equity option jargon where the second derivative of the pricing function is called 'gamma' instead of convexity.  Of course, the argument could be made that the principle purpose of option vernacular is to c...