The adoption of AI in the asset management industry is not a new trend. There has been growth in recent years, but it is still limited to a small number of market players, namely hedge funds, quantitative management offices, large research departments and financial institutions using IT services.
There are already many applications of AI:
Portfolio optimization
AI significantly improves the optimization process of portfolio construction. For example, the classic “Modern Portfolio Theory” approach of Markowitz, which relies on convex optimization concepts, serves as a precursor to modern AI-based methodologies. The reason why this foundational theory is so important is that it forms the foundation upon which AI algorithms can further modify and improve investment strategies.
Today, AI is extending this theory by exploring new dimensions of data and integrating advanced analytics. Advanced data processing capabilities allow for more detailed and informed decisions – a practice that is widely used in the industry.
Fundamental Analysis
Some artificial intelligence techniques are perfectly compatible with quantitative management, utilizing large amounts of data on a company’s key performance indicators, the macroeconomic environment or market conditions. Machine learning algorithms can find complex non-linear relationships between different variables and, of course, detect trends that analysts cannot.
Text analytics
Textual analysis is another application of AI in fundamental analysis. Using natural language processing (NLP), AI processes and analyzes textual sources such as corporate earnings reports, central bank press releases, and financial news. Using NLP, AI can extract economically and financially important information from this unstructured data. By doing so, it provides a quantitative and systematic measure that enhances and aids human interpretations.
Trading activities
AI capabilities are extremely useful in trading, where transaction complexity and the need for speed are in balance. AI supports algorithmic trading by automating many steps in the process, improving the efficiency of transactions managed in financial markets.
Investment Advisory Services
AI has opened up the possibility of a broader offering of personalized investment advisory services at a lower cost. These systems use sophisticated algorithms to process market data in real time, suggesting the most appropriate strategies for clients’ individual needs based on their return objectives and risk profiles.
Risk Management
In risk management, AI helps in modeling various “likely but undesirable” scenarios, which in turn reinforces traditional practices that focus only on the most likely outcomes.
