Yoshiyuki Suimon, Hiroki Sakaji, K. Izumi, T. Shimada, Hiroyasu Matsushima
{"title":"Japanese Interest Rate Forecast Considering the Linkage of Global Markets Using Machine Learning Methods","authors":"Yoshiyuki Suimon, Hiroki Sakaji, K. Izumi, T. Shimada, Hiroyasu Matsushima","doi":"10.52731/ijscai.v4.i1.500","DOIUrl":null,"url":null,"abstract":"In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.","PeriodicalId":179818,"journal":{"name":"International Journal of Smart Computing and Artificial Intelligence","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Smart Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52731/ijscai.v4.i1.500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In recent years, overseas financial system crises (e.g., Lehman shock and European debt crisis) and the effects of monetary policy changes by US and European central banks exerted major influence on the Japanese interest rates market. In this research, we developed a forecasting model of Japanese interest rate based on a variety of machine learning methods, by considering the information obtained from overseas rates markets and currency markets. Finally, we confirmed that the prediction accuracy of Japanese long-term interest rate improved by using the US interest rates data in addition to the Japanese interest rates data for machine learning. Furthermore, we confirmed that the prediction accuracy increased by using US and Japanese rates markets data in recent years, particularly after 2006. This result suggests that information of overseas interest rates can be used to forecast Japanese rates market nowadays.