Development of an Interactive Investor Risk Profiling Environment

Risk profiling is determination of investor's risk appetite and assigning investors to appropriate class. This is one of the most important stages of portfolio management, since the primary task of portfolio manager is to create a portfolio that is suitable for a particular investor with comfortable levels of risk and expected return. However, the current practice of risk profiling is limited to questionnaires and often reveals demographic characteristics and physical ability to bear risk, rather than risk tolerance, and many researchers consider the current approach is not effective. In addition, computer technologies are increasingly developing, and spread of robo-advisors generates large amounts of data and thus creates new opportunities for scientific research on the practice of risk profiling. Therefore, due to relevance of this topic and novelty of the idea, an interactive platform for risk profiling was built. Investors need to go through several game cases that simulate trading, and a conclusion about their risk appetite is made based on their behavior during the game. The algorithm was developed that clusters investors based on their sensitivity to changes of various parameters and assigns a risk profile to new investors using machine learning methods. Keywords: Risk profiling, interactive platform, clustering, machine learning