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.

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.

  • Next, each month we draw a random 30 stock portfolio drawn from either the “winners” decile or the “losers” decile.

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.

  • We conduct 1000 simulations for the top (winners) decile and 1000 simulations for the lowest (losers) decile as described above.
  • We then calculate the performance statistics for each simulated strategy over the designated time period (e.g. 1927 to 1962).

Each simulated strategy represents the returns a high-mom-investing monkey (past-winner buyer) or low-mom-investing monkey (past-losers buyer) would achieve over the sample time period analyzed. We calculate compound annual growth rates (CAGR), standard deviation, and maximum drawdown.

We compile the results in the charts/tables below.

What Do the Returns to Winners and Losers Look Like?

First, let’s look at the distribution of CAGRs. The high mom portfolios generate much higher returns than the low mom, almost 20% higher on average. The difference between returns of past winners and past losers is quite significant.

Momentum Investing 2014-07-14 11_10_54-Microsoft Excel (Product Activation Failed) - MOM_Sim_v02The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.Below is the table that outlines the simulation details. Take note of the difference in the distributions. Clearly, buying winner stocks has generated strong performance and buying losers has been a sucker’s bet.

Bin Low Mom High Mom
-2.00% 17 0
-0.50% 245 0
1.00% 558 0
2.50% 175 0
4.00% 6 0
5.50% 0 0
7.00% 0 0
8.50% 0 0
10.00% 0 0
11.50% 0 0
13.00% 0 0
14.50% 0 0
16.00% 0 10
17.50% 0 138
19.00% 0 433
20.50% 0 360
22.00% 0 56
23.50% 0 4
25.00% 0 0
26.50% 0 0
28.00% 0 0
more 0 0

 

How about the Risks?

Historically, high mom beats low mom on a CAGR basis–no doubt.

But let’s look at standard deviations of the portfolios from our dart-throwing monkeys. First, you’ll notice that standard deviations are tightly bound, even across 1000 simulations. No matter how you cut it, holding baskets of high mom stocks means less volatility. Low momentum stocks exhibit incredible volatility.

2014-07-14 11_15_39-Microsoft Excel (Product Activation Failed) - MOM_Sim_v02The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.Below is the table outlining the standard deviations.

Bin Low Mom High Mom
15.00% 0 0
17.00% 0 0
19.00% 0 0
21.00% 0 0
23.00% 0 0
25.00% 0 77
27.00% 0 924
29.00% 0 0
31.00% 0 0
33.00% 0 0
35.00% 0 0
37.00% 0 0
39.00% 98 0
41.00% 797 0
43.00% 106 0
45.00% 0 0
47.00% 0 0
49.00% 0 0
51.00% 0 0
53.00% 0 0
55.00% 0 0
more 0 0

Momentum strategies are known to crash and burn. This is best captured via drawdowns. The evidence below suggests that high mom stocks protect the downside better than low mom stocks, but let’s be honest–investing in momentum is a wild ride!

2014-07-14 11_16_29-Microsoft Excel (Product Activation Failed) - MOM_Sim_v02The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.Here is the table of observations:

Bin Low Mom High Mom
-97.00% 68 0
-94.50% 906 0
-92.00% 27 0
-89.50% 0 0
-87.00% 0 0
-84.50% 0 0
-82.00% 0 3
-79.50% 0 14
-77.00% 0 100
-74.50% 0 219
-72.00% 0 295
-69.50% 0 231
-67.00% 0 107
-64.50% 0 29
-62.00% 0 3
-59.50% 0 0
-57.00% 0 0
-54.50% 0 0
-52.00% 0 0
-49.50% 0 0
-47.00% 0 0
more 0 0

 

What are

1, 2  - View Full Page