Forecast System for the BoJBoJ's Monetary Policy Change by Distributed Representation of Documents and Deep Belief Network

Abstract

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.