Stock Market Forecasting Based on Text Mining Technology: A Support Vector Machine Method

no code implementations • 27 Sep 2019 • Yancong Xie, Hongxun Jiang

Series of contrast experiments show that: a) News has significant influence on stock market; b) Expansion input vector for additional situations when that day has no news data is better than normal input in SVR, yet is worse in SVC; c) SVR shows a fantastic degree of fitting in predicting stock fluctuation while such result has some time lag; d) News effect time lag for stock market is less than two days; e) In SVC, historic stock data has a most efficient time lag which is about 10 days, whereas in SVR this effect is not obvious.

Sentiment Analysis