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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Taisiia Kulikova
Predicting the MICEX Index Using the Information About Public Mood
Economics
(Bachelor’s programme)
2018
Analytics in the field of social networks demonstrates prospects for forecasting financial markets. However, the true value of such data is unclear due to the lack of a single agreement on what tools can be predicted. In this paper, we investigate whether information on collective emotional states is compared from the Twitter network to changes in the Russian stock market.

As part of the study, we work with time series covering a time period of 10 years. The source of data on the public mood is a ready-made tool - the hedonometer, which, unlike other tools, is in open access.

In the presented study, for the first time an attempt is made to detect the existence of a connection between the average level of happiness of Twitter users worldwide and the dynamics of the closing price of the Russian MICEX index. In addition, this study tests the assumption that the quality of the forecast should improve when two classes - ARIMA and ARIMA-GARCH - are included in the model, which is responsible for the average level of happiness of the public.

During the work, a delayed effect of variable happiness was found for 2, 3 and 4 days. The difference in the predictive power between models without a variable happiness and with it can not be called meaningful. This study may be useful for further study of the relationship between the dynamics of the Russian stock market and public mood.

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