Financial markets are changing
After decades of shortening, institutional holding periods are growing longer, now almost double their eight-month long low of 2008. And as the economics of trading deteriorate, political pressures intensify and asset owner demands for greater stewardship grow more vocal, valuations of long-term growth stocks are all set to rise.
As a result, equity markets will increasingly be driven by companies’ long-term fundamentals, rather than short-term news and market sentiment that have previously contracted time horizons.
However, with sell side research still firmly rooted in a myopic, news-fuelled model, most of the industry is ill-equipped for this sea change.
So while more analysts than ever (15) are covering the average large company, fewer than ever (<10%) are attempting to forecast earnings beyond a standard three-year window.
Opportunities Are Being Missed
With so much focus on short-term research, little attempt is being made to rigorously analyse stocks as long-term investments or do so in a logically structured way that allows effective comparison between stocks and across sectors.
And those who do attempt such longer time frame forecasting have enjoyed minimal success historically. In fact, average long-term earnings forecasts over the last decade have been negatively correlated to actual performance.
“With sell side price targets changing three times a year on average, conditions will become ever more fluid.”
However, in markets that are increasingly noisy, crowded and dominated by newsflow, discrimination between the valuations of stocks with strong and weak long-term growth prospects has lessened and that creates investment opportunities for those who focus on long-term fundamentals.
Unfortunately, most investors lack the appropriate analytical tools to take advantage of these opportunities.
A New Approach
That’s why we have created an innovative research framework designed with one aim – to help you identify and generate better long-term returns in global equity markets.
Nothing distracts us from that. With this framework there is news flow. No results’ commentaries. No attempts to guess the state of the economy next year – just a pure focus on objectively and systematically identifying long-term investment opportunities in global equity markets.
However, the key to the framework’s success lies in the unique analytical method it employs to integrate fundamental company with stock valuation measures, an approach that leads to lower levels of portfolio turnover than is found with other strategies that try to exploit shorter-term gyrations in sentiment.
Our framework offers a consistent basis for identifying attractive stocks and screening portfolios, as well as investigating industry trends, their implications and those stocks best placed to benefit. It’s built on four core principles.
- Rigour – We systematically and methodologically relate structural trends and changes in global industries and stock market performance with business model analysis and performance drivers that ultimately determine total shareholder returns.
- Objectivity and method – In each area of our analysis, we identify and apply the most relevant performance measures using proprietary measures and unconventional sources when these provide greater insight.
- Data-driven – Our research process is built on the analysis of evidence rather than intuition or perceptions. So although many investors have views on which companies are more or less likely to over- or under-achieve relative to their potential, we believe in the importance of a separation between the objective output of our research and subjective assessment. So we don’t ‘tweak’ our analysis or conclusions to reflect judgement or opinions on individual stocks. To improve stock selection, we would rather find ways to change our analysis than to apply opaque intuition to the analysis we publish.
- Transparency and usability – We believe a rigorous and transparent process is a vital starting point, which is why we have developed the interactive Didas Dashboard. Covering 3,000 large global companies, each of which is analysed through a consistent framework, with metrics tailored to each sector and analysis that shows the reasons for our conclusions.
And because we believe investors should have a rounded view of stocks, our analysis is both comprehensive and detailed – It’s also highly accessible. So, all of our stock analysis is available to clients through an online, interactive dashboard that provides the detail you need without losing sight of the bigger picture.
What Drives Long-Term Equity Market Performance?
What drives equity market performance? The answer is more obvious than the reams of literature on this subject suggest.
Dissect total shareholder returns (TSR) and you can see that it’s made up of three components – changes in earnings multiples, earnings growth and dividend yield – with each making its own particular contribution to stocks’ outperformance or underperformance of the market (their contributions to overall R-squared) over short and long holding periods since 1996.
From this you can see that quarter-to-quarter, changes in sentiment and fluctuations in valuations dominate performance. However, over longer holding periods, earnings growth becomes the most important factor, explaining around 60% of the performance for time horizons longer than around three years, with re-rating one-third and dividend yield playing just a minor role. So though multiples are volatile they mean revert quickly, while earnings growth is more stable and mean reverts more slowly.
“Earnings growth becomes a more important performance driver the longer stocks are held.”
Perhaps surprisingly, there is little correlation between valuation changes and earnings growth. So fast growth companies are no more or less likely to see their multiples expand or contract than those that grow slowly.
Our bottom up analysis combines growth potential ranking (relative to the market) and valuation (earnings yield) rank across a range of measures. Difficulties with back-testing and recreating contemporary data accurately, mean of course that past performance is no guide to future performance. However, we have looked at past performance that would have been generated using our framework using historical data to calculate growth potential where accurate current data was unavailable.