Managers are responsible for providing financial statements and they might try to make a good picture of their firm's conditions. Therefore, they try to delay the disclosure of bad news and release the good news as soon as possible. The ten-dency of managers toward hiding bad news increases the stock price crash risk. The protection of investor is one of the factors that can prevent from fallin...

In light of recent research that has begun to examine the link between textual “big data” and social phenomena such as stock price increases, this chapter takes a novel approach to treating news as big data by proposing the intelligent investment decision-making support model based on opinion mining. In an initial prototype experiment, the researchers first built a stock domain-specific sentime...

Social media-based forecasting has received significant attention from academia and industries in recent years. With a focus on Twitter, this paper investigates whether sentiments of the tweets regarding the 7 largest US financial service companies (in U.S. dollars) are related to the stock price changes of these companies. The authors’ findings indicate, in the financial services context, nega...

We investigate the ability of a tax-based fundamental—the ratio of tax-to-book income— to predict earnings growth and stock returns and to explain the earnings-price ratio. This tax fundamental reflects both temporary and permanent book-tax differences as well as tax accruals, such as changes in the tax valuation allowance. We find that the tax-to-book income ratio predicts subsequent five-year...

BACKGROUND Phase III clinical trials and Food and Drug Administration (FDA) regulatory decisions are critical for success of new drugs and can influence a company's market valuation. Knowledge of trial results before they are made public (ie, "inside information") can affect the price of a drug company's stock. We examined the stock prices of companies before and after public announcements rega...

We propose improved methods to identify stock groups using the correlation matrix of stock price changes. By filtering out the market-wide effect and the random noise, we construct the correlation matrix of stock groups in which nontrivial high correlations between stocks are found. Using the filtered correlation matrix, we successfully identify the multiple stock groups without any extra knowl...

The research of impacts between the Internet stock news (ISN) and the stock price movements emerges with the era of the popular usage of the Internet. In this paper, first, the ISN is empirically related to the stock returns based on the neural networks. Second, the relationship between the significant increases of the ISN volume and the significant changes of stock prices is addressed, also im...

Stock price, been studied for hundreds of years, is one of the most versatile thus hardly predictable things that is deeply rooted in the modern economy. With the trading frequency reaching sub-second and beyond, more advanced real-time stock price prediction tools would be highly demanded in addition to traditional financial analysis. In this work, we applied SVM and Naïve Bayes algorithms to ...

This study constructs a panel threshold regression model to explore the price impact of foreign institutional herding of firms listed in the Taiwan Stock Exchange during January 2000 to June 2008. Our panel threshold model is constructed to explore the price impact of foreign institutional investors’ herding in the Taiwan stock market after controlling the firm size. By examining the presence o...

The announcement of European Union enlargement coincided with a dramatic rise in stock prices in accession countries. This paper investigates the hypothesis that the rise in stock prices was the result of the integration of accession countries into the world market, and the subsequent repricing of systematic risk. The results show that firm-specific stock price changes are not related to firmsp...