According to a study conducted by Cass Business School in London, even a monkey can easily beat the U.S. stock market by picking stocks at random. The academics were analyzing how the conventional market cap weighted index compared to smart beta indices purely on the basis of luck, reports Financial Times.
The Cass Business School researchers calculated 10 million monkey portfolios. They used computers to pick a thousand stocks at random from a list of the thousand largest American companies to create a monkey portfolio. They allotted 0.1 percent weight to each pick, and there was not any limit on the number of times a stock that could be chosen.
Researchers repeated the process 10 million times every year from 1968 through 2011. Andrew Clare who teaches asset management at Cass Business School, said that the results shocked everybody. If you had invested $100 in the U.S. stock market in early 1968, the sum would have multiplied to $5,000 at the end of 2011. However, over 50 percent of monkey investors generated $8,700, another 25 percent returned over $9,100. In addition, 10 percent of them earned more than $9,500. Almost every monkey performed better than the conventional market cap weighted index.
However, researchers noted that an equally weighted index, and other indices based on equal risk contribution and inverse risk methodologies outperformed most money indices. Conclusion of the study highlights how poorly the market capitalization weighted index has performed, especially since the beginning of 2000.
The market cap weighted index of the 1000 largest U.S. stocks has given annual return of a meager 0.4 percent since 2000, compared to 6.9 percent of minimum volatility index and 6.2 percent of an equally weighted index. Since professional investors cannot rely on a monkey to manage their money, Cass researchers also calculated the risk-adjusted returns of monkey portfolios. Here too, the monkeys handily beat the conventional market cap weighted index by giving higher returns.
Prof Clare said that it is possible to improve the returns and volatility of smart beta indices substantially by applying timing indicators.
