Information and algorithmic support of a multi-level integrated system for the investment strategies formation

Abstract

The article summarizes the accumulated practical experience of the authors in the development of algorithms for the formation of investment strategies. For this purpose, the optimization of the studied parameters, information support of investment activities, verification, monitoring and adjustment in the testing mode and the subsequent practical application of the described tools are considered. The system is based on the main provisions of the Markowitz portfolio theory. The analytical block of the Information System Portfolio Investor includes Profitability-Risk model; empirical models of optimal complexity; hybrid predictive model systems; the principle of combining (integrating) both models and forecasts, as well as decision rules; optimization of the training sample length (modified Markowitz model); optimization of the frequency of monitoring and adjusting the composition of the investment portfolio. The principles of design and development of the information block of the system, its replenishment and functioning are described in detail. All the above listed components of the algorithmic content of the investment decision making system are described sequentially. The system modules have been successfully tested on a wide class of financial instruments: ordinary shares, preferred shares, government and corporate bonds, exchange commodities, stock, commodity, industry and bond indices, exchange-traded investment funds and real estate funds. The implemented Markowitz model with a dynamic database of historical data can significantly increase the efficiency of investment decisions, which is facilitated by taking into account the characteristics of both the markets under study and the corresponding financial instruments.