This white paper explores Japanese market sentiment analysis by leveraging native Natural Language Processing (NLP) techniques. By utilizing the power of NLP models specifically trained on the nuances of the Japanese language, we aim to unlock valuable insights into the sentiment associated with trading Japanese equities. Our study employs several different approaches to classifying sentiment, including our journalist derived approach to interpret a wide range of Japanese textual data sources provided by FTRI News Dolphin through a propriety relationship with Alexandria Technology. Our final study, which combines all of our NLP techniques, has shown a Sharpe ratio of 5.87 across the entire out-of-sample period. With this analysis, we aim to provide traders and investors with a deeper understanding of market dynamics to exploit trading opportunities in Japan.