Earnings Spike Potential Algorithm v1.1

First there was the VWSI, now it seems like I am going to try to get ESPA (Earnings Spike Potential Algorithm) off the ground. This immediately raises the question: just how many ugly acronyms should I try to prop up in this space? Maybe I should just do it the way the rest of the world does and start with the acronym I want, then reverse engineer the full text.

Never one to leave well enough alone, I have taken my CNBC Million Dollar Portfolio Challenge (remember that disaster?) cardboard and duct tape version of the ESPA and tweaked it a little for the current earnings season. The changes are not that major and consist largely of beefing up some TA inputs having to do with support and resistance. The resulting ESPA v1.1 seems to do a better job of predicting the magnitude of the post-earnings move and a noticeably better job of picking the direction of that move (which was previously just a little above 50%.)

Armed with a better mousetrap, I will be more active in earnings plays this quarter than usual, using the model to be both long and short straddles and strangles, as well as playing some instances where I have directional bias with straight calls/puts or call/put backspreads.

I do not intend to clutter up with space with a flood of predictions or comments on individual stocks, though I may highlight one or two from time to time. Still, looking at some of the earnings spiker candidates for AMC today through BMO tomorrow, I was struck by the sheer number of stocks with a very high short squeeze potential and a high implied volatility, two ingredients that can help turn a couple of sparks into a widespread conflagration.

Stepping back a little, my thinking is that most of the recent market action has been of the healthy correction variety – the controlled burn that renews instead of destroys. I also think that much of the bearish sentiment we find rolled into an 18ish VIX is of the bullish contrarian variety. As far as I can tell, the big fears are on the table and in the headlines. I suspect that it will require something new and unanticipated to give us the type of conflagration where we could see something like the VIX of 25-30 referenced by Jim Kingsland.

How to Find the Spiker Before the Earnings Announcement

Several readers have expressed interest in how I came up with my earnings spike potential algorithm. Essentially, this is something that has evolved over the past three weeks as a result of my desire to find companies with a high probability of making a substantial near-term move and give my CNBC Million Dollar Portfolio Challenge portfolio a chance to make a run at the finals. To make a long story short, I got the volatility I wanted, but I didn’t always get the direction right.

I would not call this a battle-tested formula. It is more like a hypothesis that continues to evolve as I get more data and continue to test and tune some of the elements. Think of it as just-in-time sausage making.

I am not an arsonist (I even missed out on youthful pyromania), but I liken this task to understanding how to get a fire started and make sure it quickly builds in intensity and spreads as rapidly as possible. For a fire, you need a starter and an accelerant; for an earnings spike, it’s essentially the same thing.

In the links below, wherever possible I have provided a favorite deep link to a free public source that includes the relevant data, calculation, graphic, etc.

Some of the more important factors I look at are:

• Implied volatility, a great initial screening tool (higher is better) – free data at iVolatility.com; if you have an account at optionsXpress, they have excellent options screens available to all
  
  
• Beta (higher is better) is another good accelerant barometer, though not as good as IV – available many places, including Google Finance
  
  
• Number of analysts (lower is better) and degree of analyst consensus (lower is usually better) – Marketwatch.com has a page that not only summarizes the analyst estimates, but also provides a “coefficient variance” number that gives you a sense of the dispersion of opinion. In many cases, the earnings and/or revenue surprise is the fire starter.
  
  
• Short ratio: days to cover (higher is better) – a classic accelerant indicator, with free data available at ShortSqueeze.com

Some secondary factors to consider:

• Price to earnings ratio (negative or n/a is best, higher is better) – available many places, including Google Finance
  
  
• Earnings history data – there is a higher probability of a surprise if there is an erratic earnings history; there is also greater potential for a high magnitude surprise if there is a consistent pattern of beating (or missing) expectations – assuming the pattern can be broken. One fun source that has earnings dates baked in to charts and post-earnings performance data available is WhisperNumber.com (more complete data for larger companies.)
  
  
• Recent analyst ranking and/or price estimate changes (none is best) – these can work both ways, but most often they reduce the probability of a surprise. Again, Marketwatch.com is a good source.
  
  
• News flow – this is a highly subjective/qualitative assessment, but there are certain types of pre-earnings news that I believe can indicate in increased or decreased likelihood of an earnings surprise. Be particularly wary of binary events, such as the pending FDA approval for a drug and the like. The best place to find the relevant information is probably by looking at company news at Yahoo Finance. I am not ready to expand upon this one at this stage, except for…
  
  
• Recent company guidance (none is best) – as with recent changes in analyst opinion, these usually dampen the surprise potential. Again, try Yahoo Finance.
  
  
• Insider transactions – these are sometimes difficult to evaluate in the context of earnings, but if an apparent transactional pattern is confirmed or contradicted by earnings, there could be an accelerant. I favor Form4Oracle as a free public source of insider transaction data.
  
  
• Technical analysis – this is good for identifying the heightened possibility of breakouts, violation of important support and resistance levels, and other factors that may act as technical accelerants. The gallery view at StockCharts.com is always a good place to start.
  
  
• Put to call ratio (higher is better) – somewhat analogous to the short data is the individual stock open interest put to call ratio, data for which is available at SchaeffersResearch.com
  
  
• Recent options activity – another subjective and difficult to assess measure, but if significant changes in open interest favor either puts or calls, this may be a tell. Not much in the way of great public data, but you may get some valuable information from Yahoo Finance.
  
  
• Company size (lower is better) – this includes revenues and market capitalization. Available many places, including Google Finance.
  
  
• Recent IPO or lack of relevant operating history (less history is better) – In general, the shorter the track record, the bigger the chance for an earnings surprise. This means that the first quarterly report or two with new management, new products, a new acquisition, etc. increases uncertainty about the result – and the potential for a surprise.

As a footnote, if you are looking for a good source for who reports when that is sortable by time of day (BMO, AMC, etc.), I like TheStreet.com’s Earnings Release calendar, where you can click on the Date/Time column to sort accordingly. If you are not familiar with a lot of the tickers/companies, then I suggest that a first pass be limited to those companies with four letter tickers whose EPS estimate and/or previous year actual EPS is negative or close to zero.

Finally, I feel obliged to remind everyone that this is a method for finding the high potential post-earnings movers, *not* the winners. I continue to play with the weightings of the various factors and ultimately your weightings should reflect your research and beliefs about the market. If you keep track of the pre-earnings data and the outcomes, you should be able to develop and tweak your own model – or at least flag some potential high fliers.

CNBC Million Dollar Portfolio Challenge: Top 0.2%

This seems to be as good a time as any to provide an update on my dalliances in the CNBC Million Dollar Portfolio Challenge. At the moment, I stand as #2091 out of 1,246,562 contestants – my best showing to date. While I am delighted to be sporting a 57% return and have so many contestants in my rear view mirror, I decided a week ago that each day I would put all my chips on a particularly volatile stock in hopes of maximizing my chances for reeling in those who are ahead of me.

As you can see from the trades outlined below, my goal is to maximize volatility in my portfolio more than it is to pick winners. In the process, I have developed a system for picking potential earnings spikers that I will be glad to provide some more details on when the contest is over. In the meantime, I will be the first to acknowledge that skill is not a significant element in this contest, unless you consider it a skill to be able to develop a portfolio that will have a week to week volatility of at least 25%.

Here is a recap of what has transpired in the past seven trading days.

I started my single stock approach by tempting fate with an ‘all in’ bet on Vertex Pharmaceuticals (VRTX) on Friday the 13^th. It looked like a disastrous move when VRTX traded down 6% before the market opened on Monday and opened off more than 5%. Fortunately, VRTX rallied slowly over the course of the day, finishing down only 0.8%. I was impressed by the reversal, held on for another day, and was rewarded with a 5.9% gain. I made the mistake of holding one more day, however, watched VRTX drift sideways, and dumped it at the end of the third day.

In my worst move and only losing trade of the contest so far, I rolled the dice on earnings AMC Wednesday. EBAY looked like the obvious high flier trade, so I went against the crowd and went all in on NVLS, losing 5.8% of my portfolio and negating the gains from VRTX.

Thursday night I sold NVLS and hopped on the OO express. Oakley turned in a great quarter in terms of both revenues and earnings, raised full-year guidance, and saw their stock jump 11.7% the next day.

By Monday morning, I was back at the earnings roulette wheel, with all my chips riding on Arch Coal (ACI) – and they handily beat expectations, trading up over 7% at one point during the day and finishing the day up 4.4%.

Today looks to be an even better day for my single stock ‘portfolio,’ as AK Steel (AKS) turned in another strong earnings report, pushing the stock up 5.8% as of this writing.

I still think it will take a portfolio of at least $3 million to make it to the top ten and get a pass into the finals. Assuming I can hold on to today’s gains in AKS, that means it will take a minimum return of 22% per week (compounded) over the last three weeks to put me in the ballpark. That type of performance is not impossible, but time is becoming a a more significant obstacle each day.

If my good fortune continues, I will provide more frequent updates…