Analysis of the Macroeconomic Uncertainty Based on the Newsbased Textual Data with Financial Market The uncertainty in the financial market, whether USChina trade war will slow down global economy or not, Federal Reserve Board (FRB) policy to increase the interest rates, or other similar macroeconomic events can have a crucial impact on the purchase or sale of financial assets. In this study, we aim to build a model for measuring the macroeconomic uncertainty based on the news text. Further, we proposed an extended topic model which uses not only news text data but also numeric data as a supervised signal for each news article. Subsequently, we used our proposed model to construct four macroeconomic uncertainty indices. All these indices were similar to those observed in the historical macroeconomic events, and the correlation was higher with the volatility of the market index with respect to the uncertainty index. We also applied the impulse response function to analyze the impact of the uncertainty indices on financial markets.

Do Emotions Determine Rumors and Impact the Financial Market? The Case of Demonetization in India Studies have identified that rumors circulate in social media and rumors influence different areas of decisionmaking. Given that rumors are essentially psychological phenomena, there are not enough studies that explore how textual contentbased emotions determine social media rumors. Further, while behavioral finance identifies rumors as influencing financial markets, the relationship between social media rumors and financial markets is not well studied. This paper attempts to provide a direction for understanding these two questions. In the context of demonetization in India it finds that while textbased emotion extraction helps identify rumors circulating on social media, these emotions do not impact the movement of the financial market.