A research collaboration between Aon Hewitt and Cass Business School has shown that alternative weighted indices offer better investment strategies than those of the market capitalisation index. Indeed, a computer simulation of random stock-picking, likened to the decision making of a monkey, outperformed a traditional market capitalisation weighted index every time.
There is now a dazzling array of alternatives to the market-cap approach to choosing constituent weights for equity indices. Using data on the 1,000 largest US stocks every year from 1968 to the end of 2011 we compare and contrast the performance of a set of alternative indexing approaches. The alternatives that we explore can be loosely categorised into two groups. First, a set of weighting techniques that Chow et al (2011) describe as “heuristic.” The second set are based upon “optimisation techniques,” since they all require the maximisation or minimisation of some mathematical function subject to a set of constraints to derive the constituent weights. We find that all of the alternative indices considered here would have produced a better risk-adjusted performance than could have been achieved by having a passive exposure to a market capitalisation-weighted index. However, the most important result of our work stems from our ten million Monte Carlo simulations. We find that choosing constituent weights randomly, that is, applying weights that could have been chosen by monkeys, would also have produced a far better risk-adjusted performance than that produced by a cap-weighted scheme.
In this paper we explore an alternative approach for determining constituent weights for equity indices. This approach makes use of alternative definitions of company size, and is referred to as Fundamental Indexation (Arnott et al (2005)). Based upon a data set that comprises the largest 1,000 US stocks for each year in our sample, our results show that between 1968 and 2011 the fundamental index alternatives that we consider have out-performed a comparable index constructed on the basis of the market capitalisation of the index constituents in risk-adjusted terms. Our Monte Carlo experiments show that this superior risk-adjusted performance cannot be attributed easily to luck. We also find that although the superior performance is achieved with higher constituent turnover than required using the Market-cap approach to index construction, the turnover is lower, and in some cases much lower, than required by some of the heuristic and optimised index construction techniques that we explored in our last paper. Finally, we find that although the application of a simple market-timing rule does not enhance the returns on these fundamentally-weighted indices very significantly, it does reduce the volatility of their returns and their maximum drawdown quite considerably.
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