文書の分散表現と深層学習を用いた日銀政策変更予想
2016 年 2016 巻 FIN-016 号 p. 66-
詳細
2016 年 2016 巻 FIN-016 号 p. 66-
The author utilized texttext-mining and deep deep-learning technic technics to forecast a monetary policy change by the BoJ BoJ. More specifically, the classifier of the BoJ's documents was developed, which picks up the document containing any trait of previouslypreviously-experienced precursor for monetary policy change. Such classifier was constructed by obtaining distributed representation of documents via Doc2Vec and feeding them into Deep Belief Network with economic timetime-series datadata. The back back-test for the period from Jan 2014 to Jan 2016 showed a fair performance of the classifier to send precursory signalsignals against two cases of additional monetary easing easing.
