Innovation Selection

ALPORA’s Innovation Funds each include the most innovation-efficient companies in a universe – for example, among all companies in Europe with a market capitalization of more than 300 million euros, as in the ALPORA INNOVATION EUROPA fund.

From a set of over a thousand candidates, ALPORA’s multi-step selection process initially identifies a few hundred and finally precisely those innovation-efficient companies that fit the fund’s objective.

ALPORA’s origins lie in scientific research into the relationship between innovation efficiency and stock performance – the foundation of innovation investing. The expertise of the founding team flowed then and flows now into the development of a selection process that selects fund components based on objective criteria and thus enables investment in innovation in various optimized funds:

Data Accumulation

The evaluation of information with Big Data algorithms, machine learning and ALPORA’s own mathematical optimization methods is based on the fact that this information, i.e. data volumes, must first be available in a “clean”, high-quality form.

In part, relevant information about companies is freely available, however, some of it must be specifically collected. ALPORA can offer companies an equally objective assessment of their innovation capability in return for objective key figures.

Only by bringing together and carefully preparing freely available and, above all, high-quality data that was specifically collected does a qualitatively valuable database emerge as the basis for further evaluation steps.

Evaluation and analysis

Based on databases, which are exclusively built by ALPORA, we combine selected Innovation Analytics methods to analyze the innovation efficiency of companies.

ALPORA ICA (Innovation Capability Analytics) and ALPORA OCA (Operational Capability Analytics) are the two most significant mathematical optimization methods currently developed and used by ALPORA to identify companies with maximum efficiency.

In this process, dozens of parameters, or more precisely information about all companies in a universe are related to each other and evaluated relative to the specific comparison group to position each individual company on the Efficient Frontier.

Fund Selection

The results of the evaluation and analysis produce a ranking of companies according to their innovation efficiency within the peer group.

The fundamental analysis to select the most suitable companies from the top innovators in a ranking are carried out by ALPORA or one of our selected partners, depending on the fund. Extensive stress tests ensure that problematic companies are removed. Big Data evaluations of scientific publications are also used to check whether the companies have also identified the innovation trends that will be relevant in the future.

At the end of the portfolio construction process, there are typically 30-40 companies per ALPORA Innovation Fund that remain in the respective fund for one year and drive its performance through their innovation efficiency.