Predicting Taiwan Stock Market Using Social Moods
Date Issued
2016
Date
2016
Author(s)
Chen, Chun-Fu
Abstract
In recent years, mining social media data to forecast the future has been a popular research. The stock market behavior and investor emotions are always bonded together. With the development of social media, people are willing the share their feelings on the social media including investor. In our study, we select PTT stock board as our platform, a forum gathering investors sharing their opinions, and crawl data on it. We calculate the emotion score through NTUSD and DUTIR sentiment dictionary and predict two representative stock market indices: Taiwan Futures Index and Taiwan Capitalization Weighted Stock Index. The concept of fixed-sized rolling window and fixed feature size are adopted in this thesis. That is, if the emotion cause the variation of stock market, the main causality might be different in different time span. The rolling window size and feature size are selected to our prediction model through lower Root Mean Square Error. There are four value recorded each day: opening value, intra-day highest value, intra-day lowest value and closing value. We classify these four value into three groups through K-means clustering algorithm and then conduct prediction.
Subjects
Taiwan Stock Market
Sentiment Analysis
Stock Market Prediction
PTT
Type
thesis
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