Recently I read an article somewhere describing a study showing that stocks with novel tickers outperformed those with humdrum tickers. One thinks, for example, of Southwest Airlines, with ticker "LUV." This is based on the name of Love Field, which was the first airport from which they ever flew. Southwest, of course, has done very, very well over the past few decades (I'm finding that it appreciated by 2900% since 1982, which corresponds to 14% compounded. This is actually less than I expected, but it is still nothing to sneeze at). This may lead someone to ask if stocks with clever tickers in general tend to do well. Unfortunately I've forgotten where I saw the original article on this topic, so I have decided to try a homemade version.

A difficulty arises in assessing without bias which tickers are "clever," but I did the best I could.

I took the members of the Russell 1000 as of 1997 and listed their names and tickers as of that date. A good starting point for finding clever tickers is to look for tickers which have a first character that does not match that of the company name. For example, the "L" in "LUV" doesn't match the "S" in "Southwest Airlines," and the "X" in "XRAY" doesn't match the "D" in "Dentsply." There were, however, some tickers that were obviously clever but didn't obey this rule. For example, the ticker for "Outback Steakhouse" is "OSSI," and I definitely thought that qualified. You can see an obvious problem–I recognized "OSSI" as significant only because I'm familiar with the Aussie theme of the steakhouse. I'm familiar with that only because it's a successful company. If it had fallen apart soon after 1996, I could have forgotten all about the chain and the "Bloomin' Onion" and all that. (As an aside, I've tried to visit the Outback in Norwalk, Connecticut about ten times, and the wait was always too long. It's not that good, is it?)

So here is the list of companies in the Russell 1000 as of 1/1/1997 that had clever tickers, as assessed by me, today.

Column 1: company name as of 1997
Column 2: company ticker as of 1997
Column 3: total return from 1997 to present (*) in percent

Franklin Resources        ben   445
Anheuser Busch            bud   197
Nextel                         call    410
Brinker                         eat   321
Callaway Golf                ely    -39
Sprint                          fon    28
NICOR                         gas   106
Santa Fe Pacific Gold     gld    0
Coca Cola                    ko     9
Southwest Airlines         luv    261
Philip Morris                 mo    279
Quaker Oats                oat    192
Bank One                    one   62
Outback                      ossi   132
Everest Reinsurance      re     264
Transocean Resources   rig    152
Panamsat                    spot  7
Lone Star Steakhouse   star   28
Toys R Us                    toy   -10
Dentsply                      xray  303

avg 157%    stdev 148%

Stats for all 1000 Russell 1000 companies:

avg 132%    stdev 200%

(*) I need to investigate the exact algorithm that my expensive software uses for calculating total return. That is especially important when there are mergers, spinoffs, etc. It is crucial that whatever it does for the novel-ticker companies, it also does for all the other Russell 1000 companies, so that our comparison is unbiased.

Results: The novel ticker companies on average made 157% and the average Russell 1000 stock made 132%. The standard deviation for the novel ticker returns was 148%, and there were 20 novel tickers. The standard statistical error then from taking 20 novel ticker companies is 148%/square root(20), or 33%. So the average novel ticker return of 157% is not significantly different from that of the average Russell 1000 stock, 132%.

The bias factor discussed earlier–which one would guess would make me prone to pick currently successful companies as having novel tickers–would tend to make the novel tickers appear to perform better. Even with that presumed bias they don't seem to perform much better.

Net result: I don't believe the idea that novel tickers tend to outperform.


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