Jelenlegi hely

Data science and Complex networks szeminárium

Félév: 
2017/18 II.félév
Helyszín: 
Árpád tér 2. II. em. 220. sz.
Dátum: 
2018-04-26
Időpont: 
15:00-16:00
Előadó: 
Branko Kavsek (University of Primorska; Faculty of Mathematics,Natural Sciences and Information Technologies; Jožef Stefan Institute; Artificial Intelligence Laboratory)
Cím: 
Using Words from Daily News Headlines to Predict the Movement of Stock Market Indices
Absztrakt: 

The next seminar on Data science, complex networks and mathematical modelling will be on the 26th of Apr, from 15:00.

The place of the seminar will be the 2nd floor seminar room of the Arpad ter building. The language of the seminar is English.

Speaker: Branko Kavsek (University of Primorska; Faculty of Mathematics,Natural Sciences and Information Technologies; Jožef Stefan Institute; Artificial Intelligence Laboratory): Using Words from Daily News Headlines to Predict the Movement of Stock Market Indices

Abstract: Stock market analysis is one of the biggest areas of interest for text mining. Many researchers proposed different approaches that use text information for predicting the movement of stock market indices. Many of these approaches focus either on maximising the predictive accuracy of the model or on devising alternative methods for model evaluation. On the seminar, we will describe a more descriptive approach focusing on the models themselves, trying to identify the individual words in the text that most affect the movement of stock market indices. Data from two sources will be used: the daily data for the Dow Jones Industrial Average index (“open” and “close” values for each trading day) and the headlines of the most voted 25 news on the Reddit WorldNews Channel for the previous “trading days” (data has been gathered for the past 8 years). By applying machine learning algorithms on these data and analysing individual words we will show that certain words have a "positive" effect on stock indices while other words have a clearly "negative" effect.