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Beating the market with data-driven strategies.

Stockopedia study



In today’s video, we discuss another interesting study completed by Stockopedia; Fine-tuning your strategy using factors, screens, and systems to improve the odds of beating the market.

The markets have become more efficient over time, and beating the market has become difficult for active discretionary fund managers. More than 77% of actively managed funds in the UK and more than 95% globally, failed to beat their respective benchmarks in the last 10 years. The data is disappointing for the US as well, where over 90% of the actively managed funds failed their investors over the past 20 years by delivering below-benchmark returns, whilst also charging hefty fees.

The irony is that we are talking about the best minds in the industry who screen through zillions of documents and data points, they are often well-connected, and have an army of highly qualified analysts at their service. It’s an embarrassingly poor use of resources to deliver such sub-par performance.

However, as an individual investor, you have an advantage. You can be much nimbler and more flexible and have more investing options to grow your account rapidly. The study by Stockpedia aims to equip you with the best techniques using factors, screens, and systems to beat the market year after year.

Let’s understand the importance of factors first. Rather than adding too much discretion to the portfolio management process, it’s wise to follow an investment philosophy that narrows down the list of potential investment candidates, and there could be no better way to do this than to focus on factors that favor your targeted market.

Let’s understand this with a potent example of US markets. Here is how the different factor portfolios have performed in the US vs the S&P500 in the 30 years through to 2021. The markets highly favored momentum, with quality being the distant second. A $10,000 portfolio invested in the momentum portfolio grew close to $900,000 in the period when compared to approximately $500,000 of the quality portfolio. Value was a relative laggard, but still outperformed the S&P500. My own analysis over the years has come to the same conclusion, Quality and Momentum factors are the driving force behind returns.

A factor may provide a multitude of stocks at a time, making it an exhaustive exercise for individual investors trying to build their portfolio. This is where the screening process comes in handy. A screen with your set filters can narrow down the list of stocks. For example, in this study, Stockopedia used screeners to build a Buffett-style portfolio and compared the backtested returns with Berkshire Hathway's public portfolio. The portfolio outperformed the Berkshire portfolio by a wide margin - a 1000x return against a 100x on the Berkshire portfolio.

This is a theoretical exercise because Berkshire would have missed many small and mid-cap opportunities simply because those stocks would not have absorbed the billions of dollars that Berkshire had to deploy. This primarily shrunk Berkshire’s investable universe. The key takeaway however is, that as an individual small investor with no such constraint, you could have used screens to massively outperform the legend himself. Stockpedia published the results of some of the guru screens run on the UK stocks since inception, which showed very high returns, with this Warren Buffett screen leading the pack, followed by the screen of screens.

In hindsight, the easiest way to clock such performance was to invest in the same stocks in the same proportion as advised in the guru screen and rebalance that portfolio by periodically running the screen. However, choosing one or two among many screens would have been quite difficult at inception. There is also no guarantee that these screens will continue to perform because the market-favored theme may change in the future. The reason why the Buffett style portfolio did so well in the UK is that the UK market favored the quality and value themes while growth didn’t do well. This was in sharp contrast to the US market where momentum and growth topped the charts.

An investor, no matter how informed, wouldn't have been able to foresee this disparity in two major world markets. In that case, the portfolio construction would have largely been dependent on personal preferences, and therefore would be immensely impacted by individual thought processes and behavior. A patient investor will choose value, a defensive investor will choose quality and an aggressive investor will choose growth.

Let’s say you have figured your style and it’s time to put money to work. Putting all your capital in one screen is easy when there are a few stocks. However, this will only happen when the screening rules are very tight. When those rules are loose, it will throw too many names and there would be a scope of discretionary stock picking that will lead to varied outcomes for different investors.

Let’s delve deeper into the study to understand this. Stockopedia ran UK stocks screens on these three common factors - quality, value and growth - with a very loose filtering criterion, which threw a large number of companies in results. An algorithm then randomly chose 20 stocks from the results and built a portfolio that would be rebalanced at the beginning of the next year. The system ran the same screens the next year and chose 20 random stocks to build a new portfolio from the liquidation proceeds of the previous portfolio.

The algorithm repeated the exercise for eight years and the portfolio ended up returning 40% for the period. Due to a wide number of possibilities in this investing approach, Stockopedia ran the simulations multiple times. In the first three runs, the portfolios delivered quite varying returns, with the second portfolio ending negatively and the third delivering closer to a 300% return. In 100 runs the results were quite tilted in favor of outliers as can be seen in this histogram. There were several outlier portfolios delivering 85% returns in the period, which was the top quartile return in the study. Moving a step further, when the portfolios were run 10,000 times, the distribution looked like this. Most times the returns were below 60%, with still many instances of outlier portfolio returns.

Let’s now turn to the key findings of the study for individual factors. Here is a box and whisker diagram of the results for all three factors. The diagram shows the median return of the strategy here with the blue box showing 25 to 75 percentile returns, and these lines or whiskers show the full range of returns excluding outliers, which are then shown here in blue dots. The benchmark return - FTSE all share in this case - is here at the blue dotted line.

Quality was the clear winner in this study with 41% median performance, and value was a distant second, underperforming the benchmark by a small margin. Surprisingly growth fared badly in the study delivering a negative three percent return, hugely underperforming the benchmark.

On the downside, the results were not too different as the worst return of the quality portfolio came in at negative 31%, as compared to a negative 40% of the value portfolio and negative 61% of the growth portfolio. Another metric that vindicated the results was the chance of loss, which was highest at 55% for the growth portfolio and lowest at 4% for the quality portfolio. The value portfolio fell in between the two at 17%.

One can also use a combination of these factors to further tighten the filters and shorten the prospective list of stocks to make stock analysis easier. Along the same lines, Stockopedia tweaked the screens a little bit by adding quality metrics to the value portfolio, which led to a better outcome in the value portfolio as the box in the diagram moved up with a median return above the benchmark.

Similarly, when quality metrics were added to the pure growth portfolio, it significantly altered the results with the median return jumping from a negative 3% to a positive 50%, which is nine percentage points higher than the pure quality portfolio.

The key takeaway from these results is that a lot depends on the filters you put to screen stocks in any factor. We saw that growth, which should ideally be leading the pack in any market, underperformed when the growth filter was too loose. It was only when the rules were topped up with that of the quality screen that the results changed meaningfully. Putting such tighter filters will also be in an investors’ favor as this will narrow down the list of qualifying stocks.

Only a few investors end up mechanically investing in the portfolio thrown by the screen. Most investors have the propensity to make the final choices themselves. Discretion in portfolio management will always be a little contentious because as soon as human factors are introduced to the process, the outcomes change based on personal preferences, styles, and biases. Two people can look at the same screen and build entirely different portfolios with entirely different results. Therefore, it’s always in the investor’s best interest to let the screens do the heavy lifting and focus on building a process.

Stockopedia provides a great platform to build screens across the globe using hundreds of metrics. To make it even easier for investors, Stockopedia has built a proprietary ranking mechanism called Stockrank, which ranks stocks using and analyzing different metrics for the three most used screens - quality, value, and momentum.

In the quality ranks, the system uses nine different ratios to rank the stocks from best to worst. These rankings start from 1 and go up to 99, with 99 being the best. So, let’s say if you put greater than 90 as the quality rank filter to screen stocks, the system will show the top decile of quality stocks and eliminate every other stock from the potential stocks’ list.

Similarly, the Value Stockrank system uses these six ratios to rank stocks. These ratios fall under three categories - earnings, assets, and income.

Lastly, there is the momentum screen, which focuses on ranking stocks based on their price and earnings momentum. The momentum rank uses nine different ratios - four for price momentum and five for earnings momentum - making the system rather robust.

The rankings make the job much easier for an investor, instead of putting a barrage of filters and criteria, the investor can select any factor and simply put a rank filter to get the list of stocks. Also, one can combine different factors by putting in far fewer filters.

Stockpedia also highlighted a couple of case studies showing how the average person can use their platform to do stock analysis, if they want to take a deeper look at some of the names from the screeners.

For example, here is a fundamental and technical snapshot of Plus 500 - a stock that showed up in the quality and value screen back in 2017. The stock had a quality ranking of 95 and value ranking of 89. The return ratios vindicated the high-quality rank of the company, and low readings on most valuation ratios, depicting the undervalued nature of the stock. A high Piotroski F-score highlighted improving efficiency, productivity, and liquidity.

For those interested in the Piotroski score we produced a video solely focused on its principles and performance over time.

The company also displayed an extraordinary long-term earnings growth trajectory with 65.8% Earnings Per Share over the last 6 years and 78% over the last 3 years. The operating margins and return metrics remained consistently at elevated levels.

Additionally, the company frequently beat analyst estimates and the management remained confident in the company’s outlook, as can be seen in regulatory releases by the company. The management’s confidence also percolated into generous buybacks amounting to £509 million since 2017. The company also adopted an aggressive yet effective marketing strategy that propelled its growth.

In a nutshell, the company displayed:

● Robust, Quality fundamentals

● Excellent growth and valuations

● Expectation-beating results and

● Regular share buybacks

Making is a perfect quality and value stock to be included in the portfolio. The stock also followed suit and more than doubled in less than a year.

The second case study was Kier Group, which ranked very high on the value parameters but languished on quality, momentum, and growth parameters. The company was extremely out of favor with the markets as its stock price fell from £9 to £4 in one year. Its operating margin was under pressure at 3% and was barely positive in the last 5 years. Its return ratios were below the industry average and quite volatile. The company was also facing liquidity pressure with its current ratio below 1x and quick ratio at 0.62x, with a high increase in debt. Average shares were also increasing, highlighting shareholder dilution to raise money for a cash-guzzling business.

The bad shape of fundamentals led to downward earnings revision by analysts covering the stock and the downward spiral was further accentuated by the resignation of the company’s CEO. To top it all up the industry was in bad shape with its peers going belly up.

In a nutshell, the company had:

● A downward momentum

● Under pressure quality

● Liquidity concerns

● Management changes and

● Collapsing peers

Unsurprisingly, the stock tanked further to less than 50p in 2020 before recovering to £1.30 now. Remember it is often the case that expensive gets more expensive and cheap often gets even cheaper, and Kier Group certainly got cheaper.

In my opinion, the study is a clear example of how to make your job much easier as an investor or trader, filtering out poor performing companies help you significantly narrow down the list of investable stocks based on your preferences. To make that job even easier, Stockpedia’s Stockrank system lets you set those screens with relative ease, saving you from getting confused with a sea of usable fundamental metrics, whilst moving the odds of success into your favour.

Finally, no matter which strategy you choose, there will always be some high fliers that you will miss in stock markets, but that’s not a tragedy. If you have a decent process and you follow it well, there will be little scope for disappointment in the long run despite facing volatility in the short run.

For those looking to take advantage of a 25% discount in the Stockopedia platform simply use the links below.

For those with a bias towards trading whilst also including key fundamental aspects, we also offer bespoke scanning software, looking for Quality stocks breaking out of consolidation, again simply use the links below.

Thanks for watching, and as always if you find value in the videos please do hit the like button, which in turn will help the algorithm find you.

For those interested, we have a highly engaged group that uses our bespoke breakout scanner to find some of the best trades, offering low-risk high reward potential. Feel free to use the links below, and as always thanks for watching.

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