Applicability of online sentiment analysis for stock market prediction
|Author:||Bc. Petr Rýgr|
|Year:||2015 - summer|
|Leaders:|| prof. PhDr. Ladislav Krištoufek Ph.D.
|Work type:|| Bachelors
|Awards and prizes:|
|Abstract:||The purpose of this thesis is to explore various possibilities of performing online sentiment analysis
and utilizing obtained information in stock market prediction. Firstly, several tools and sources
available for sentiment analysis are presented and brief history of research related to each tool is
provided. Additionally, Google Trend model is designed to evaluate whether information about
searching volume of selected terms can be used to predict future movements of S&P 500 index.
Strategy based on such model is implemented on historical data and its cumulative return is
compared to classical buy and hold strategy. Furthermore, hypothesis whether it is possible to
utilize publicly released news as a leading indicator for future stock returns is tested. Lastly, process
of algorithmic sentiment analysis is described and its strengths and weaknesses are assessed.