美國聯準會會議紀要的文字探勘與台灣經濟變數預測
Other Title
Text mining of the FOMC minutes and forecasts of Taiwan economic variables
Journal
經濟論文叢刊
Journal Volume
47
Journal Issue
3
Pages
363-391
Date Issued
2019
Author(s)
黃裕烈
Abstract
In this paper we extract useful information from the minutes of the Federal Open Market Committee (FOMC) and examine how such information can help predict economic/financial variables. Based on the minutes during 1993–2016, we conduct sentiment analysis to determine the FOMC’s attitude towards different topics, i.e., the mandates of the FED. Our approach is different from related studies in the following respects. First, we identify compound words which carry more specific meaning than do single words. Second, we adopt the topic model, MAP-PLSA, for estimating the conditional probabilities of these words/terms, which in turn can be used to classify sentences in the minutes under different topics. Third, the attitude towards each topic is determined by the “tone” of its sentences. We then proceed to evaluate whether the FOMC’s attitude towards different topics can be used to improve economic forecasts.
Type
review