Brady vs. Manning and Exxon Mobil (XOM)

“I don’t look at a problem and put variables in there that don’t affect it.” – Bill Parcells

All of last week, heading into Sunday’s big NFL showdown between the Broncos and Patriots, most of the rhetoric was about who the greatest quarterback of this generation is.  Tom Brady or Peyton Manning.

Ardent supporters of Brady talked about his Super Bowl rings, doing more with less offensive weapons over his career and his 10-5 record in games against Manning led teams.  Manning supporters noted his better career stats and passing records, better command of the offense and his win against Brady in the playoffs last year.

When it came down to prognostications for the game Sunday, there was usually one key stat to support either side, again focused on the quarterbacks.  Manning is having the better season.  Brady is better in cold weather games.  Manning has better weapons.  Brady is great at home.  Here were some interesting stats when it came to actual performance:

     ·  Manning has a 2-7 record all-time in games at New England

     ·  Manning has an 8-11 record in games played below 40 degrees (it was 37 degrees and windy at kickoff Sunday)

     ·  Brady is 33-4 in games played in temperatures below 40 degrees

     ·  Brady has won 41 straight regular season home games against AFC opponents

When you start looking at some of these historical statistics in aggregate they begin to look meaningful.  One of them alone, on their own, is interesting but at least the first two above lack statistical significance.  Most people, to achieve a better level of confidence, look at multiple data points or factors to shape their opinion going into any decision and particularly investment decisions.

This week we took a look at Exxon Mobil (XOM).  Our predictive analytics technology utilizes financial time series data to find relationships in historical data to provide probabilities on forward outcomes.  We’ve validated the predictive nature of using price trends alone, which is now being utilized by some of the largest Asset Managers and Hedge Funds to support fundamental investment decisions, as a signal for multi-factor quant models and as a more accurate forecast for price and volatility for risk management.

For many of our clients, they like the ability to adjust the parameters of their research and look at multiple factors to get an objective gauge for what is likely to happen next.  For example, as opposed to just looking at price as a factor, you can use multiple data sets to narrow in on similar environments to today.  For this week, we decided to look at Exxon Mobil’s current 3 month price trend AND the 3 month daily volume trend for Exxon Mobil (XOM) to find instances where both the price trend and volume trend are statistically similar to today and to see if there’s consistency in the market reaction to this environment historically.  There is.

The projection is also consistently negative just looking at similar instances of the current price trend alone.

Have a great week.