Electric cars manufactured by Tesla are still a rarity on the roads in the Cayman Islands, but on the stock market, the U.S. carmaker already is firmly in the fast lane.

The speed at which the group founded by Elon Musk is on its way is evident in its stock price, which appreciated by 2,327 percent percent from July 2010 until June 2017. 

The development of the market capitalization is even more impressive: With currently $58.67 billion, the newcomer has become even bigger than the long-established U.S. firms Ford Motor Co. and General Motors, with $44.54 billion and $55.95 billion, respectively.

Tesla ‘disrupts’ General Motors and Ford

Only the future can tell whether the early praise is justified. But as of today, Tesla is as an example of how big the explosive force of companies with disruptive potential can be.

There are also other impressive examples, including Apple, Amazon, Alphabet, Facebook and Netflix, which also made it with the help of disruptive products or services into the group of the largest companies worldwide.

On their way up, all these companies made their founders as well as many long-term shareholders very rich.

 No easy playground

The good thing about this: In the history of mankind, there have probably never been so many disruptive areas at the same time as is now the case. Even the list with only the most well-known sector names is quite long: digitalization, artificial intelligence, automation, industry 4.0, virtual reality, augmented reality, electric vehicles and batteries, self-driving cars, sharing economy, social networks, renewable energy, e-commerce, fintech, drones, biosimilars, genetic engineering, cloud computing, Internet of Things, Big Data, data analytics, 3D printing, LED, crypto-currencies/blockchain.

But with that, we are now in the “evil” part of the story: On the one hand, a truly disruptive company is not easy to identify with sufficient certainty. And on the other hand, if someone believes they have found a potential candidate, they may be confronted with a valuation problem. The latter has to do with the fact that disruptive companies often come with, at least azcase of disruptive stocks.

Jasperneite, the chief investment officer at private bank M. M. Warburg & Co. in Hamburg, Germany, claims to have found a way that investors can pick the best companies to benefit from disruptive developments.

On the hunt for structural breaks in key ratios

That strategy is based on the results derived from a joint research project with Professor Hanjo Allinger of the Institute of Technology in Deggendorf, Germany.

The idea behind the project was whether it may be possible that data analysis can deliver helpful results in finding out if a company is on the brink of causing disruption.

One of the underlying assumptions was that when looking for disruptive potential in companies, there should also be disruptions in the data, independent of the respective levels of their key ratios.

Disruptions in key ratio time series show as structural breaks. As such, the research project was looking for econometric methodologies that can identify structural breaks in key ratio time series.

One example of a company that exhibited such structural breaks in their return on equity at the end of last year was the multinational mining company Anglo American (as the accompanying graphic illustrates).

Of course, analysts do not only estimate the return on equity, but also a large set of key ratios. Analyzing this vast amount of estimate data with a view to structural breaks, and thus disruptions, should help to identify with above-average accuracy such companies that (for whatever reason) stand to gain from disruptive processes. That means the project partners were not looking for companies with an attractive valuation, high margin or low debt, but those that analysts found to be improving enormously, relative to their own trends.

Modern data processing has made this task relatively easy. The real trick, according to Jasperneite, is not to over-optimize, as this will cause unbelievably good results in back testing but in reality will not live up to the back test picture. To prove the feasibility of this approach, the project managers gave equal weight to all the key ratios used and calculated at the end of each month a “disruption score” for each company in the STOXX 600 Index in its historic composition.

If a company in a given month scored among the top 20 stocks, it was put into the portfolio for one year. This yielded a portfolio with about 70 stocks on average. Arithmetically, one may expect that this approach would yield 240 stocks (12×20) in the portfolio, but this was not the case because stocks often rank in the top 20 for several months and thus already are in the portfolio.

Recently, the following U.S. stocks scored positively: Agilent Technologies, Apple, Caterpillar, Cummins, Deere, H&R Block, Micron Technology, Oracle, Paccar, Rockwell Collins, Sherwin-Williams and Viacom B.

Disruption portfolio shows a clear outperformance

Whenever a stock scored in the top 20 again during its 12-month holding period, the one-year cycle started again, resulting in average holding times well in excess of one year.

Besides this, the project was conducted entirely without complicated portfolio construction to avoid the pitfalls of curve fitting, and all stocks in the portfolio were equally weighted at all times. The clear outperformance, especially from 2010 forward, may be interpreted as an indication that the effects one was looking for have become more evident in the past few years, as Jasperneite explains.

The outperformance relative to the benchmark and an equal-weighted portfolio of all STOXX 600 stocks was overall so significant that Jasperneite thinks it makes sense to further pursue the above-described approach of data and computer-aided disruption identification.

With this computer-aided process making inroads into asset management, it becomes, itself, another example of how disruptions are changing the world.

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