Online trends and sentiment and their possible application in stock market prediction - Stehno, Josef; Nikolovová, Pavla, 1982-; Čermáková, Klára; Vysoká škola ekonomická v Praze. Národohospodářská fakulta (2015)
The goal of this thesis is to assess information contained in internet user's activity. I focus on two sources of data: Google Trends and sentiment contained in StockTwits posts. For both of them I examine the correlation of its percentage changes and percentage changes of variables describing the stock market development. Econometric testing consists of three phases, first is Least Squares Method, then ARIMA model, and lastly testing for Granger Causality. Conclusions are that activity of internet users does contain valuable information. The correlations are strongest for firms operating in IT business or generally focusing on modern technologies. Strong correlation is between trade volume or market volatility and Google Trends, whereas sentiment in post on StockTwits is statistically significant for stock price development.
Vedoucí práce: Pavla Vozárová
Bakalářská práce (Bc.)—Vysoká škola ekonomická v Praze. Národohospodářská fakulta, 2015
Obsahuje bibliografii
Textový (vysokoškolská kvalifikační práce)
Rok obhajoby 2015
Způsob přístupu: Internet
Keywords: ekonomie [obor bakal. práce]; bakalářské práce; bachelor's theses