Two weeks ago, we posted a simulation study on the performance of cheap and expensive stocks based on various valuation metrics. The dart-throwing monkeys simulations gave us a vivid look of how cheap stocks beats expensive stocks regarding compound annual growth rates (CAGR), standard deviation, and maximum drawdown. Here is the link to the older post: Never buy expensive stock. Period. We received over 50 emails asking that we do the same analysis, but on “momentum.”
You Asked; We Listened…The most basic momentum strategy buys stocks that have performed well in the past. This strategy is very different from a pure value strategy, which exclusively focuses on buying cheap stocks. CXOAdvisory, GestaltU, Gary Antonnaci, and Millennial Invest — as well as others — have discussed different angles on momentum. And of course, there is a slew of academic research on the topic.
How Does Our Simulation Work?For testing purposes, we create 2 samples. The first sample is from 1927 to 1962 and the second sample is from 1963 to 2013. The samples are selected in a way that we can compare the results of the momentum simulations to the value simulations, which run from 1963 to 2013. We sort stocks into deciles based on stock performance over the previous 12-month ranking-period returns (months t-12 through t-2, skipping the first month). We only focus on US mid/large cap to avoid weird micro/small cap outlier effects.
- Example: If there are 1000 stocks in the universe, stocks 1-100 go in the first decile (High mom/winners), stocks 901-1000 go in the tenth decile (Low mom/losers), and the stocks in between 101 and 900 go in their respective deciles.
- Example: We draw 30 random stocks each month from the top (winners) and bottom (losers) decile from 1927 to 1962. Again, image we have a monkey throwing 30 darts, every month during the 36 year period, to establish, in each month, a new 30 stock portfolio. Once our monkey has thrown his 30 darts in each month, we will then have 432 separate monthly portfolios (12 months * 36 years) and will have made 12,960 (30 stocks * 432 months) individual stock picks. This represents one simulation.