Readers of my blog know that I often refer to my friend Bob Seawright’s blog as a source for good information and content. This week, Bob touched me in a different way as he tapped into my secret “Star Trek” fanaticism and made a good point at the same time. After reading his article I had to share it with you all. Enjoy.
Kobayashi Maru and The Forecasting Follies
posted December, 2, 2014 by Bob Seawright
In the Star Trek universe, the Kobayashi Maru is a Starfleet Academy training exercise for future officers in the command track. It takes place on a replica of a starship bridge with the test-taker as captain. In the exercise, the cadet and crew receive a distress signal advising that the freighter Kobayashi Maru has stranded in the Klingon Neutral Zone and is rapidly losing power, hull integrity and life support.
The cadet is seemingly faced with a decision (a) to attempt to rescue the freighter’s crew and passengers, which involves violating the Neutral Zone and potentially provoking the Klingons into an all-out war; or (b) to abandon the ship, potentially preventing war but leaving the freighter’s crew and passengers to die. As the simulation is played out, both possibilities are set up to end badly. Either both the starship and the freighter are destroyed by the Klingons or the starship is forced to wait and watch as everyone on the Kobayashi Maru dies an agonizing death.
The objective of the test is not for the cadet to outsmart or outfight the Klingons but rather to examine the cadet’s reaction to a no-win situation. It is ultimately designed as a test of discipline and character under stress.
However, before his third attempt at the test while a student, James T. Kirk surreptitiously reprograms the simulator so that it was possible to rescue the freighter. When questioned later about his ploy, Kirk asserts that he doesn’t believe in no-win scenarios. And he doesn’t like to lose. So he changed the game. Thus for Trekkies, the test’s name is used to describe a no-win scenario as well as a solution that requires that one change the game in order to jerry-rig a solution to the proffered problem.
For would-be market experts, their Kobayashi Maru is a public market target, most often included in an annual market preview publication. It’s an expected part of the gig. Similarly, when a Wall Street strategist, economist or even a run-of-the-mill investment manager or analyst gets a crack at financial television, he or she is routinely asked, often as almost an afterthought, to give a specific target forecast for the market. Instead of thinking like Captain Kirk and wisely objecting to the premise of the question, the poor schlemiel answers and, once matters play out, is shown to have been less than prescient. Indeed, as I often say, one forecast that is almost certain to be correct is that market forecasts are almost certain to be wrong.
Every December I take a look at these predictions for the year that’s ending and they are almost always uniformly lousy. Moreover, when somebody does get one right or almost right, that performance quality is not repeated in subsequent years. That’s because, at best, complex systems – from the weather to the markets – allow only for probabilistic forecasts with very significant margins for error and often seemingly outlandish and hugely divergent potential outcomes. Chaos theory establishes as much. Traditional market analysis has generally failed to grasp the inherent complexity and dynamic nature of the financial markets, which chaotic reality goes a long way towards explaining highly remarkable and volatile outcomes that seem inevitable in retrospect but were predicted by almost nobody.
This year hasn’t been any different. As year-end approaches, let’s once again take a look at how badly various Wall Street market forecasts missed it with their prognostications for the S&P 500 in 2014. What follows is a table of my survey of the 2014 year-end target forecasts for the S&P 500 from 50 investment strategists and money managers. It tracks their “achievements,” using forecasts from the beginning of 2014.
Strategist (Firm) Year-End 2014 S&P 500 Target
Brad McMillan (Commonwealth) 1,800
David Joy (Ameriprise) 1,845
David Bianco (Deutsche Bank): 1,850
Gina Martin Adams (Wells Fargo) 1,850
Barry Bannister (Stifel Nicolaus) 1,850
Craig Callahan (ICON) 1,850
Gary Thayer (Tradition Capital Management) 1,875
Brian Belski (BMO) 1,900
Barry Knapp (Barclays) 1,900
Tobias Levkovich (Citigroup) 1,900
David Kostil (Goldman Sachs) 1,900
Kim Forest (Fort Pitt) 1,900
Jack Ablin (BMO) 1,915
Mark Luschini (Janney Montgomery Scott) 1,920
Michael Kurtz (Nomura) 1,925
Matt King (Bell) 1,925
Peter Cardillo (Rockwell) 1,935
Derek Hoyt (KDV) 1,940
Sean Darby (Jefferies) 1,950
Jonathan Golub (RBC) 1,950
Julian Emanuel (UBS) 1,950
Jeff Weniger (BMO) 1,950
Fred Dickson (D.A. Davidson) 1,950
Ben Halliburton (Tradition Capital Management) 1,950
Cam Albright (Wilmington Trust) 1,950
Bob Doll (Nuveen) 1,950
Andrew Garthwaite (Credit Suisse) 1,960
Jim Kee (South Texas Money Management) 1,970
Joe Tatusko (Westport Resources) 1,975
Mike McGarr (Becker) 1,980
Donald Selkin (National Securities) 1,980
Dan Greenhaus (BTIG) 1,980
Frank Fantozzi (Planned Financial Services) 1,995
Savita Subramanian (Bank of America) 2,000
Craig Johnson (Piper Jaffray) 2,000
Rob Stein (Astor) 2,000
John Burke (Raymond James) 2,000
Peter Tuz (Chase) 2,000
Thomas Nyheim (Christiana) 2,000
Oliver Pursche (Gary Goldberg Financial) 2,000
Brian Jacrobsen (Wells Fargo) 2,000
Adam Parker (Morgan Stanley) 2,014
John Stoltzfus (Oppenheimer) 2,014
Doug Cote (ING) 2.020
Steven Goldman (Goldman Mgmt) 2,025
Brian Peery (Hennessey Funds) 2,050
Tom Lee (JP Morgan) 2,075
Philip Orlando (Federated Investors) 2,100
Ryan Detrick (Schaeffer’s Investment Research) 2,100
Byron Wein (Blackstone) 2,200
Median Forecast 1,950 (up 6.44 percent)
S&P 500 Actual (through November, 2014) 2067.56 (up 11.86 percent)
I had a cork wall in my office at NYSE firm Morgan Keegan, and every year end we would throw darts at the pages of the WSJ for a portfolio…it always beat the indexes and often our own research recommendations. What fun.