Investment monkeys and passive portfolios

Imagine for the moment that you had never heard the term ‘passive investing’ before, and that you are approached by a confident, investment manager resplendent in a very sharp suit. The well-dressed investment professional tells you about a new investment strategy that his investment team has been experimenting with.

He explains the strategy. It involves identifying the 100 stocks listed on the London Stock Exchange with the largest market capitalisation. A portfolio is then constructed of these 100 stocks where their portfolio weights are determined by dividing the market capitalisation of each stock by the sum of market capitalisations of all 100 stocks. This portfolio is held for three months.

At the end of the three months the process is repeated: the main adjustments that need to be made to the portfolio at this quarter end, and at all subsequent quarter ends, involves divesting from those stocks that have fallen out of the top 100, and to invest in those that have been elevated into the top 100.

This process is what investors understand to be passive investing. My example describes, more or less, how one could invest on this basis using the FTSE 100 as the benchmark index. But looked at like this, a more appropriate description of this investment strategy is that it is rules-based.

At Cass Business School we have been investigating whether there is anything special about investing on a market cap-weighted basis. Billions and billions of investors’ money is currently invested on this basis. As one way of determining how good market cap-weighted investing is as a rules-based investment strategy, we decided to come up with our own rules-based strategy.

We began by collecting return data on the largest 500 US stocks spanning the period from January 1964 to December 2014, updating this set at the end of each year. Using this data we constructed a market cap-weighted portfolio where we updated the portfolio weights annually. Using the same data we also constructed a portfolio using our own rules-based approach. These rules were based on the popular board game Scrabble. Here is out it works.

Every stock in the dataset that we collected has a ticker symbol, that is, a unique three or four letter code. For example, the ticker for the software group Apple is AAPL and for Exxon Mobil it is XOM. For each company we calculated its ticker Scrabble score based on the points awarded for each letter in the game.