By Justin J. Carbonneau (@jjcarbonneau) —
An object at rest stays at rest and an object in motion stays in motion with the same speed and in the same direction unless acted upon by an unbalanced force.
Momentum investing, or buying stocks exhibiting strong price performance relative to other stocks nicely aligns with Newton’s principle. There are a numerous academic studies and white papers backing-up the robustness of the momentum factor. The knocks against momentum, however, are that often times these strategies are ultra-high in turnover, making them too costly to deploy in the real world, and they’re susceptible to crash risk – i.e. large pullbacks once the momentum breaks.
Investors who want pure momentum stocks in many cases don’t consider the fundamentals of the underlying stocks. They focus on price and let everything else fall as it may. Fundamental investors, on the other hand, typically don’t care so much about momentum, but rather look at financial metrics and valuations to determine if the company is a good investment.
But is there a sweet spot in combining the two that can get you superior returns compared to each on their own? This was a question Dashan Huang, Assistant Professor of Finance at the Lee Kong Chian School of Business at Singapore Management University, set out to answer with his co-authors Huacheng Zhang, Guofu Zhou and Yingzi Zhu in a research paper titled, Twin Momentum: Fundamental Trends Matter, in early 2017 (it’s since been updated).
We have recently added ten new quantitative models to Validea and over the next few months I will feature some of them and the unique methods they use to look at stock selection. This paper is the first I will look at.
In Twin Momentum, the authors developed and tested a stock selection model that combined two concepts — strong price momentum and strong fundamental momentum. Stocks that scored highly based on the combined rank of both types of momentum were considered “twin momentum” stocks and a long/short portfolio capturing the twin momentum strategy demonstrated long term robustness in their testing.
There are different ways to define stock price momentum, but the research is consistent in showing that momentum persists in the intermediate term time horizon and is generally not persistent in the very short term (i.e. a week or a month) and not in the long term (i.e. over 12 months). One way to uncover intermediate term momentum is to look at a stock’s price one month ago and compare it to 12 months ago. This captures the intermediate-term trend, while excluding short-term momentum from the most recent month.
In Twin Momentum, Huang grouped stocks by quintiles and stocks within the top quintile were eligible for inclusion in the final portfolio.
To calculate fundamental momentum, Huang constructed a formula to estimate a stock’s fundamental investment return (FIR) utilizing seven different fundamental variables. Rather than just focus on one or a few specific variables, the authors used a wide variety of profitability and earnings variables.
They used the following metrics: earnings
1 – earnings
2 – return on equity
3 – return on assets
4 – accrual operating profitability to equity
5- cash operating profitability to assets
6 – gross profit to assets
7 – net payout ratio
For our interpretation of the strategy, we score each stock in our investable universe based on the trend in of these seven factors. As with price momentum, stocks in the top quantile are eligible for inclusion in the final portfolio.
The paper show that price momentum tends to fall off in terms of performance four months after portfolios are constructed. Fundamental momentum, on the other hand, tends to show persistence in returns over longer periods of time (12-18 months). A combination of the two, however, did significantly better than either price or fundamental momentum in isolation as the chart below shows. As the authors’ suggest, “fundamental momentum and price momentum are largely complimentary, rather than overlapping”.
Making Twin Momentum Real
Of course, academic studies are one thing. Real world implementation can be more challenging. That is what we’ve attempted to do here at Validea. In the video below you’ll get a quick overview of how we have implemented Twin Momentum in our Guru Analysis engine, using Abode as an example and I also showcase the Twin Momentum model portfolio and the Guru Stock Screener.
For more market trends, visit ETF Trends.