Enabling continuous improvement: Our research

Our unique, value-oriented investment strategy is based on facts, research and an independent mindset. We have been using self-developed valuation models for more than 25 years to systematically examine the stock market for undervalued companies.

We are among the pioneers of systematic value investors. Since our foundation we have relied on the interaction between man and machine in a holistic approach, ultimately combining the advantages of both worlds.

The constant development of our backtesting methods, screening processes and data analyses are the decisive drivers to ensure our competitiveness. This is achieved if we continuously identify new alpha sources and supplement the process with new knowledge - always with the aim of generating above-average investment results for our customers.

„Maintaining objectivity when analyzing the past is both our greatest strength and our greatest challenge.“

Goran Vasiljevic, Chief Investment Officer

Factor and process development

Our investment process comprises fundamental and quantitative research and brings them together in a complementary manner. The fundamental know-how and experience of portfolio managers and data experts form the basis of our model and process work. Cumulatively, we now have over 200 years of capital market expertise.

We are constantly striving to enhance our investment approach. Our focus is to create a process that evaluates the situation of companies from a business perspective and puts them in relation to the rest of the market. We aim to select stocks whose fundamental development is seen as more pessimistic than the results that will actually be realized in the future. In this way, we lay the foundation for systematically and sustainably generating excess returns.

The research process can be divided into two different activities:

On the one hand, there are improvements that focus on the meaningfulness of company key figures, processes and databases. This is usually triggered by ongoing quantitative research and fundamental analysis, academic studies and client feedback.

On the other hand, we carry out regular reviews and evaluate applied models annually on the basis of various quality standards. Structural weaknesses and fundamental properties such as the avoidance of value traps can trigger potential model revisions.

Data quality and resources

As a specialized investment boutique, ensuring the data quality and resources of the investment team is extremely important. We obtain company, economic and market data from a wide variety of providers who have constantly adapted the quality to the dynamic market conditions and increased requirements. These include:

  • S&P Capital IQ
  • Credit Suisse HOLT
  • MSCI (both index and ESG data)
  • Bloomberg

The data is processed in-house and mostly with proprietary systems. A modern and reliable IT infrastructure is an important success factor for us and the basis of our research activities. Our integrated team includes specialists with different skills: Financial market experts, mathematicians, data scientists and software developers. This diversity is the driver for the successful further development of our company's core competence.

A look ahead: Artificial intelligence and machine learning

Machine learning is finding more and more application in systematic investment processes. Currently, many quantitative models are still static and depend in particular on human input.

In the future, models could make their own decisions, learn from their own experience and improve continuously. It is quite conceivable that the system could be taught to analyze and learn for itself what is a healthy and what is an unhealthy cash flow.

While these developments would further pronounce the symbiosis of man and machine, they would not call our investment philosophy and consistent value orientation into question.


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