Automated Advisory System for Long-term Investments

OData support
Supervisor:
Simon Gábor
Department of Automation and Applied Informatics

In today's environment of falling interest rates people are changing investment habits. In recent years the risk-free and fixed-term bank deposits wereone of the most popular forms of investment, however, due to today’s relatively low interest rates it is almost not worth it to invest in these forms anymore. Therefore, customers are trying to turn to other, less risky forms of investments which can achieve higher returns, such as mutual funds. The hope of higher returns, however, is definitely risky. Choosing the investment funds this risk is the uncertainty of future returns. Thus, the investor can not be sure, if good or bad investment fund was selected.

In my thesis I aimed at the creation of an application in which users can get automatic signals for their mutual fund. On this basis, the investor may consider to hold the current investments, or to choose better performing alternative funds. No one knows the future in advance, so the thesis is in part an attempt to combine the availabe investment funds to produce more profit (sell when it is expected to begin to fall, buy them when they are expected to start to rise) considering the present and past knowledge.

In the presented development I implemented an algorithm that can be tested by the completed application. which gives the opportunity to develop further algorithms or make an algorithm better.

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