Key points are not available for this paper at this time.
Intensive development of digitalisation tools and digital financial services significantly increases the range of societal actors who are interested and can make financial decisions about using available funds. Since there is a wide range of approaches towards investment making, choosing a method from the available menu has become a partly sociological decision. Institutional investors, SMEs and individual investors are increasingly using artificial intelligence algorithms. The paper offers an analysis of a specific AI investment decision method, i.e., the Cuckoo Selection algorithm. It is based on the logic of cuckoo breeding and was applied to stock selection and portfolio optimisation for three data sets in different markets. The goal of minimising risk was to reduce risk, but at the expense of profitability. When the Cuckoo Selection algorithm was applied to maximise the Sharpe ratio, both stock selection and portfolio optimisation showed an increase in diversification efficiency. The algorithm proved to be particularly useful when it was used for selection, and optimisation was performed by other known algorithms. This research can be useful in automating financial decisions and developing recommendation systems for investors who are interested in efficient allocation of available funds, whether it is financial fund management, investment of underused funds, or financial project management.
Maknickienė et al. (Thu,) studied this question.