日銀総裁会見の表情解析に基づく感情値の計測と金融政策変更との関係

抄録

After the Bank of Japan (BOJ)'s monetary policy meeting, the BOJ governor makes a press conference to explain the monetary policy. In this research, using facial expression recognition algorithms based on deep learning, we analyzed the governor's facial expressions in the press conference and estimated the emotional indexes such as "Happiness", "Anger", "Sadness", "Surprise". As a result, we found that the indexes of "Anger" and "Disgust" increased much just before making major policy changes. On the other hand, the index of "Sadness" tended to decline after the monetary policy changes. This suggests that the information based on the facial expression analysis can be a useful material for forecasting the future monetary policy.