DATA ANALYSIS OF THE PROFITABILITY OF FINANCIAL INSTRUMENTS TO DEVELOP FINANCIAL SOLUTIONS TO INVESTORS WITH DIFFERENT RISK ATTITUDES

Authors

  • Vitalii Kobets

DOI:

https://doi.org/10.32999/ksu2307-8030/2019-33-49

Keywords:

robo-advisers, Markowitz and Tobin model, data analysis, cluster analysis, investment risk

Abstract

The paper proposes the development of new financial services, such as robo-advisers, which are widespread in the US and the EU, but are not used in Ukraine, which allows investors to increase their income in the long run period. The research demonstrated the development of an investment plan for investors with different propensities to take risks by the means of robo-adviser services. Investment portfolios were categorized for clients with different risk attitudes, Markowitz and Tobin models were developed for making investment decisions based on ration ‘profitability-risk’, investment portfolios were created using financial instruments through robo-adviser service and a cluster analysis of client characteristics was carried out to develop representative investment plans. Using open data about financial instruments (e.g., cryptocurrencies) and the Markowitz model, we identified following types of investors: 1) risk-averse investor whose profitability is 0.657% daily or 24.5% annually with 0.44% risk; risk seeking investors, whose profitability is 0.87% daily or 31.6% annually with a risk of 1.06%; hybrid type of investor has profitability 0.45% daily or 16.5% annually with a risk of 0.28%. By the means of clustering of investors, based on the received data, we categorized the users of robo-advisor services into two main groups: risk-averse workers of working age who need more than average returns (52%); risk-neutral pensioners who need less than average returns (48%). For these representative investors, we have developed proposals for investment plans whish correspond 2nd and 3rd type correspondingly. The developed by us robo-advisor service is intended primarily for individuals who invest in financial instruments during long-run period to provide a permanent passive income. Our challenge is to maintain a constant level of consumption for investors throughout their life by automatically analyzing how much he or she should consume and save each year.

Published

2019-03-25

Issue

Section

SECTION 9 MATHEMATICAL METHODS, MODELS AND INFORMATION TECHNOLOGIES IN ECONOMY