Stockopedia demonstrate how we can beat the stock market buy using specific factors.
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Today we look at the concept: Factor Investing, an approach which aims to quantify particular characteristics or ‘factors’ of a company. The factors are often categorised through metrics of Quality, Value, Momentum and Growth.
These known factors have been proven to be highly correlated to stock market returns.
To demonstrate the theory, I use a service called Stockopedia, they give each company a score based on these individual factors. Each factor is scored between zero and 100 and the weighting of each factor translates into a total score for the company.
Here we can see the unquestionable correlation between the combined factor scores.
The chart in this example is based on all stocks within Europe, and the factor score used is a combination of Quality, Value and Momentum, or the QVM Stockrank score.
To the left we have the portfolio returns.
This benchmark line shows the return of the FTSE All Share index, and since the service began the benchmark is showing a return of around 10%.
The top green line shows the return of stocks which were ranked with a QVM score of between 90 and 100, suggesting they were the strongest stocks within the EU universe.
The next line shows stocks ranked between 80 and 90.
And then all the way down to the lowest ranked stocks, scoring between 0 and 30.
Also note the stockrank scores are rebalanced quarterly.
If you applied such a strategy against a portfolio of companies with a Stockrank score of between 90 and 100, you would have yielded a return of approximately 200%, in contrast to the FTSE all share index of just 10%.
In theory, this ‘factor’ investing approach relies heavily on the fundamental attributes of a stock. But imagine if you combined this approach with technical analysis and applied such analysis to stocks with the best combined ‘factor’ score.
This is the same approach I take, I put fundamental analysis first by evaluating the factors (made easy with the Stockopedia platform), and then follow up with specific technical analysis. Such an approach can be very effective indeed.
Let’s look at factor investing in more detail.
Described as a quantitative approach due to the ability to place a specific number against each piece of information, and condensed into factors of quality, value, and Momentum.
Personally, I give a higher weighting to the factors of quality and momentum, but only because its suits my style and philosophy.
Here we can see how my current portfolio is apportioned in terms of the Quality and Momentum factors.
As you can see by the cluster of blue bubbles, my portfolio is weighted towards good quality stocks which are also classed as leading stocks in terms of momentum.
This is another great analytical tool provided by the Stockopedia team. In addition, their research shows that good, leading stocks tend to outperform, and lagging, junk stocks tend to underperform.
Again, by applying your trading strategy to this portion of stocks can improve your chances of success considerably.
But what is the fundamental criteria used to form the Quality, Value and Momentum factors…..
First, we look at quality.
This chart shows the performance of quality factors measured from 2013 to 2018. To the left, the average annual returns, and at the bottom of the chart we have the stocks scored and ranked based on the quality criteria measured.
A quality company is often defined as such by having; Good profitability, high margins, positive cashflow, adequate liquidity and low levels of debt.
Using these quality factors as a filter to find good companies proved very effective. The correlation between the quality metrics being measured and the annual returns was near perfect.
We can see that stocks which were scored between zero and 10 and classed as very low quality, returned on average, a negative 12.5% annual return.
The correlation between quality scores and annual returns continued right through to the top ranked score, generating an average annual return of around 13%.
Perhaps eliminating this group of low-quality stocks from your strategy would be a good starting point.
Next we have the value factor and its performance over the same 6 year period.
The commonly used value components accepted by the investing community are shown in the example here, presented by Stockopedia for the company Rio Tinto.
We have the price to earnings, price to book, price to sales and the price to free cashflow ratios.
If we look at one of these ratios, we can see the company is given a rank from the universe of companies being measured.
We also have the dividend yield and earnings yield rankings.
These value factor rankings are then translated into a total value score. In this example Rio Tinto has a combined score of 71.
Once again, the scores are categorised from zero to 100 and the universe of stocks are placed accordingly into these groups.
We see the same high correlation between annual returns and value rank, with the most expensive stocks showing an average loss of 4% per year, whilst the cheapest stocks seen an average annual return of over 10% per year.
Whichever strategy you use it could be wise to avoid companies with a very low value score.
Next, we have the factor which I hold in higher regard, and that is the Momentum factor.
The momentum factor is an important metric regarding my trading strategy, which looks for improving stocks usually in a trend and often making new highs.
The factors chosen by Stockopedia are categorised by price, and by earnings.
The price factors consider four key metrics;
The 52-week high, whilst favouring stocks close to it.
The 50-day moving average against the 200-day moving average, whilst looking for the 50-day to be considerably higher than the 200-day.
And the relative strength of price over the past 6 to 12 months.
These key price metrics are considered to be strong ‘leading’ indicators of future price performance.
Next are the earnings factors, collectively looking for upgrades or surprises beyond market expectations. An earnings surprise is considered a catalyst for future price performance.
Just as before, we group the stocks into their overall momentum factor ranks.
We see the same strong correlation between the momentum ranks and average annual returns, although this time we see that the highest-ranking group see a commendable average annual return of 20% over the 6 years measured.
Again, avoiding the deteriorating stocks showing low momentum could be a wise strategy decision. Or perhaps applying your strategy to only the very best improving stocks, showing the highest momentum, an even smarter decision.
Remember, by combining the Quality, Value and Momentum factors together, Stockopedia formed what they refer to as the QVM Stockrank. And just as we did for each single factor, the collective Stockrank is scored into buckets ranging from zero to 100.
We saw that the highest stock ranked companies produced 200% in comparison to the index return of 10%, however we can take this dataset a step further to see that not only are the returns higher, but the probability of selecting a profitable stock is greater.
We can see here that the lowest ranked stocks which are a combination of quality, value and momentum factors, provided a 33% probability of picking a winning stock when measured over the following 12-month period. Conversely the highest ranked stocks provided a 67% probability of picking a winning stock.
Again the correlation between the factor rankings and the probability of success is profound.
Using these combined QVM factors, we can see that benefits are seen across a broad range of sectors too.
The stocks within the 80 to 100 Stockrank range saw a predominantly even distribution across the sectors, with Healthcare showing average annual returns of 31%, through to Energy returning an average 3%.
On the opposite side, stocks which were given a factor score of between zero to 20, saw a sporadic loss distribution of between 0% and 31%, but although sporadic, none of the sectors within this low Stockrank group saw a positive return.
Finally, we have market capitalisation. Using the same Stockrank scores based on the QVM factors, we can see that stocks which are considered Micro caps saw an average annual return of 28%. Interestingly and perhaps the only anomaly we have seen up to now, is that even the lowest ranked stocks managed positive annual returns of 8%.
The results for each market cap group thereafter speak for themselves.
Ultimately, whether you’re a fundamentalist or a pure technical analyst, factor investing certainly has its place.
By filtering the cheap from the expensive, the junk from the quality, or even the deteriorating from the improving, you can beat market returns significantly.
And remember, rather than hunting for these best performing factors yourself, you can join the Stockopedia service which I personally use, through the discounted link below.