There has been a growing literature in finance that utilizes technique of information retrieval and sentiment detection to analyze news and other text document. This is a promising field in finance, as more text information becomes available and technique for analyzing such information gets more sophisticated. I will briefly survey this literature in finance and give examples for what specific questions in finance that information retrieval and sentiment detection might be helpful. One example is to understand the decision by central banks to move interest rates. Central bankers make statements that indicate their views on the economy. These statements have information about the likelihood of future action by central banks to move interest rates. To extract such information accurately from the statements, it requires close collaboration of computer scientists and financial economists.
Zhiwei Zhang is an economist at the Research Department of the International Monetary Fund. Before joining the IMF in 2002, I was an economist at the Bank of Canada. I hold a Ph.D. in economics from University of California, San Diego. I was born in Beijing, China.
This talk is part of the CLIP Colloquium Series, organized by Jimmy Lin (jimmylin -at- umd .dot. edu). For the complete schedule, please visit http://www.umiacs.umd.edu/research/CLIP/colloq/.