Stock forecasting is a significant and challenging task. The recent development of web
technologies has transformed the communication channel to allow the public to share …

In finance, the momentum spillovers of listed firms is well acknowledged. Only few studies
predicted the trend of one firm in terms of its relevant firms. A common strategy of the pilot …

Corporate mergers and acquisitions (M&A) account for billions of dollars of investment
globally every year, and offer an interesting and challenging domain for artificial intelligence …

Existing surveys on stock market prediction often focus on traditional machine learning
methods instead of deep learning methods. This motivates us to provide a structured and …

In recent years, the process humans adopt to learn a foreign language has moved from the
strict" Grammar–Translation" method, which is based mainly on grammar and syntax rules …

Stock trend forecasting, aiming at predicting the stock future trends, is crucial for investors to
seek maximized profits from the stock market. Many event-driven methods utilized the events …

In the literature, an increasing amount of information from various sources related to the
stock market is being considered for stock movement prediction. However, previous studies …

Financial forecasting has been an important and active area of machine learning research
because of the challenges it presents and the potential rewards that even minor …

Stock prediction is a challenging task due to multiple influencing factors and complex market
dependencies. Traditional solutions are based on a single type of information. With the …

Considering event structure information has proven helpful in text-based stock movement
prediction. However, existing works mainly adopt the coarse-grained events, which loses the …