How do we know which are the best stocks to buy? Well, it’s not an exact science and can be subjective. But it often comes down to quantitative and qualitative research with a bit of macro thrown in.
Lots of novice investors don’t give the quantitative side of things enough consideration. And maybe that’s because it’s not all that easy to come across the data.
After all, we’re talking about constantly changing share prices and constantly changing earnings forecasts, among other things.
While it may be possible to do this for a handful of stocks, it’s nearly impossible to cover an entire index.
So, today I’m looking at some of the strongest stocks to buy, globally, according to data.
What goes into the data?
A quantitative data in finance takes in valuation metrics, growth indicators, earnings revisions, momentum, volatility, liquidity, and sentiment analysis. And these quantitative data sets can inform our investment decisions.
Different analysts will have different models that put varying degrees of importance on certain metrics. For example, some analysts may put greater weighting on growth-related metrics, while others might favour more predictable ones like ongoing profitability.
Moreover, despite some caveats, quantitative strategies have demonstrated the ability to outperform the market. Academic studies, such as those by Fama and French, highlight the efficacy of factors like value and momentum in beating market benchmarks.
Share price momentum
While many investors may think it’s dangerous to invest in a surging stock, momentum can be one of the strongest indicators of future performance.
Of course, this only applies if the valuation metrics are still attractive.
I note this because many models actually value momentum very highly. It can allow the stock to realise its fair value quicker than companies without momentum.
Why is the data so useful?
Quantitative data isn’t infallible and won’t guarantee finding me a surefire winner. But it’s invaluable for stock picking due to its systematic and data-driven nature.
Unlike subjective analyses, quantitative models use historical and real-time data to identify patterns and trends, helping investors make more objective decisions.
This approach also minimises emotional bias and allows for disciplined portfolio construction.
Emotional bias can be incredibly misleading for novice investors, who occasionally buy stocks because of a positive engagement with the company or similar. This can be a recipe for underperformance.
The stocks
So, here are the top five stocks I’ve come up with from the data, along with some of their metrics.
Of course, there’s plenty more metrics and numbers not included there. And to make informed investment decisions, I’d need to do further research into these shares.
| Price-to-earnings (Fwd) | 1 Year performance | Profit margin | Dividends | EPS growth (Fwd) | |
| Dorian LPG | 5.3 | +187.5% | 76.5% | 2.3% | 55.1% |
| Yalla | 8.9 | +33.2% | 64.4% | n.a. | 15.2% |
| Euroseas Ltd | 2.5 | +83.1% | 73.6% | 5.57% | n.a. |
| Celestica | 15.5 | +144% | 9.3% | n.a. | 38.2% |
| AppLovin | 13.4 | 280% | 63.6% | n.a. | 159% |
However, using this data, there are signs as to why these stocks rank above their peers. For example, four of them have extraordinarily strong margins, while Dorian offers an attractive valuation and strong earnings growth.
I already hold AppLovin, Celestica, and Dorian. However, given the strength of Yalla and Euroseas’s data, I’m going to do further research. I’d been following Yalla for a while, but the company was struggling with post-pandemic growth.
