Market Trend Prediction using Sentiment Analysis:Lessons Learned and Paths Forward
Table 9. Market trend prediction using FT news articles and RWNC headlines (2011-2015).
['Type', 'Baseline Acc', 'Baseline  [ITALIC] Fup1', 'Baseline  [ITALIC] Fdown1', 'Financial Times Acc', 'Financial Times  [ITALIC] Fup1', 'Financial Times  [ITALIC] Fdown1', 'Reddit Headlines Acc', 'Reddit Headlines  [ITALIC] Fup1', 'Reddit Headlines  [ITALIC] Fdown1']
Sentiment attitudes and emotions were extracted from the FT news articles and the RWNC headlines in the time period from 2011 to 2015. This is consistent with the previous section, in which no correlation or causality link was established between headlines sentiments and stock prices. It might be explained by the fact that headlines are very short text snippets and therefore provide little chance for us to reliably detect sentiment attitudes and sentiment emotions. The sentiments extracted from FT news articles painted a quite different picture. The sentiment enriched model outperformed the baseline model in half of the scenarios: it demonstrated slightly better results for DJIA, JPM, and EUR/USD, but slightly worse results for AAPL and GBP/USD. These experimental results are consistent with the previous section and confirm again that for some stocks sentiment emotions could be used to improve the baseline model for market trend prediction.