In a world with crypto-trading hamsters, stock-trading cats, and all manner of arbitrary stock-selecting mechanisms, perhaps it's not so surprising that someone has looked at the use of board games to inform portfolio decisions.

At least that's one takeaway from a presentation by Cass Business School's Nick Motson, who found that a "Scrabbled-weighted portfolio" — one in which stocks are held in proportion to their tickers' corresponding tile values — outperforms the market over a long horizon. The presentation yields eye-popping figures showing 1.5% higher returns to the Scrabble Index over the market-cap weighted benchmark:

Of course, the larger point of his presentation is not that investors should go long the Scrabble Index, but rather that in the space of possible portfolio weights, there are bound to be portfolios that ex post dominate the market portfolio (the implication being that one should be skeptical of "smart beta" strategies that purport to deliver higher sharpe ratios).

Scrabble Tile Value Distribution. Under the Scrabble Index, the ticker AAPL would have a value of 1.5 (calculated as (1 + 1 + 3 + 1)/4), while Tesla (TSLA) would have a value of 1 ((1 + 1 + 1 + 1)/4). Apple is thus held 3:2 in proportion to Tesla.

As a former competitive scrabble player turned finance PhD student, I couldn't help but dig deeper into the implications of a Scrabble-weighted portfolio. As a first pass, it is worth replicating the figure from Motson's presentation to check that the overall methodology is correct. Although I obtain slightly different numbers, the Scrabble Index does indeed **outperform the market-cap weighted index from 1969-2014, with annualized returns of 12.1% vs 10.3% for the value-weighted portfolio.

Scrabble-Weighted Portfolio. Portfolios use 500 largest stocks at each month-end with at least 5 years of continuous trading history.

It also achieves a higher Sharpe ratio of 0.132 vs. 0.114.

One answer for what's going on might be that the letters truly do have some meaning. Perhaps, for example, tech or growth companies are more likely to have X, Q, J, and Z in their tickers (think Xerox, Amazon, Zoom, etc.). Or, given the "size factor", where small stocks have historically outperformed large ones, it could be that tile value is correlated with its ticker's market cap.

None of this is really true. The correlation between ticker value and market cap rank is a mere 6%. The average returns by letter show some heterogeneity, but not one that reveals a clear split by tile value. (The error bars, not shown, are monstrous).

In tile value - return space, the lack of correlation is even more stark: