-
1 Comment
Nishi-Nippon Railroad Co., Ltd is currently in a long term downtrend where the price is trading 8.7% below its 200 day moving average.
From a valuation standpoint, the stock is 38.8% cheaper than other stocks from the Industrials sector with a price to sales ratio of 0.7.
Nishi-Nippon Railroad Co., Ltd's total revenue sank by 1.0% to $91B since the same quarter in the previous year.
Its net income has dropped by 85.9% to $431M since the same quarter in the previous year.
Based on the above factors, Nishi-Nippon Railroad Co., Ltd gets an overall score of 1/5.
| ISIN | JP3658800002 |
|---|---|
| Sector | Industrials |
| Industry | Railroads |
| Exchange | TSE |
| CurrencyCode | JPY |
| PE Ratio | 7.92 |
|---|---|
| Target Price | 2350 |
| Beta | 0.21 |
| Dividend Yield | 1.7% |
| Market Cap | 161B |
Nishi-Nippon Railroad Co., Ltd. engages in the transportation business in Japan and internationally. It operates through five segments: Transportation, Real Estate, Retail, Logistics, and Leisure and Services. The company is involved in railway and bus business; real estate rental and sale business, and overseas development projects; Retail includes the Supermarkets/liquor stores business; Global Logistics business; developing agricultural and Intrapreneur business projects, as well as operates city hotels, accommodation-focused hotels, and upgraded accommodation-focused hotels; the amusement park and the aquarium. Nishi-Nippon Railroad Co., Ltd. was founded in 1908 and is headquartered in Fukuoka City, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 9031.TSE using our backtest tool. PyInvesting provides the backtesting software for you to backtest your investment strategy. Our backtest software is written using Python code and allows you to backtest stock, backtest etf, backtest options, backtest crypto and backtest forex online. Our backtesting Python framework is highly robust and gives you a realistic simulation of how your strategy would have performed in the past using backtest data.
© PyInvesting 2025
