Abstract
The uncertainty in the financial market, whether US—China 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.
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Yono, K., Izumi, K., Sakaji, H., Shimada, T., Matsushima, H. (2020). Measuring the Macroeconomic Uncertainty Based on the News Text by Supervised LDA for Investor’s Decision Making. In: Bucciarelli, E., Chen, SH., Corchado, J. (eds) Decision Economics: Complexity of Decisions and Decisions for Complexity. DECON 2019. Advances in Intelligent Systems and Computing, vol 1009. Springer, Cham. https://doi.org/10.1007/978-3-030-38227-8_15
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DOI: https://doi.org/10.1007/978-3-030-38227-8_15
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