-
1 Comment
Showa Sangyo Co., Ltd is currently in a long term downtrend where the price is trading 3.1% below its 200 day moving average.
From a valuation standpoint, the stock is 61.9% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.4.
Showa Sangyo Co., Ltd's total revenue rose by 2.2% to $66B since the same quarter in the previous year.
Its net income has dropped by 8.2% to $2B since the same quarter in the previous year.
Based on the above factors, Showa Sangyo Co., Ltd gets an overall score of 2/5.
CurrencyCode | JPY |
---|---|
ISIN | JP3366400004 |
Sector | Consumer Defensive |
Industry | Packaged Foods |
Exchange | TSE |
Target Price | 3250 |
---|---|
Market Cap | 98B |
PE Ratio | 8.5 |
Beta | -0.01 |
Dividend Yield | 3.3% |
Showa Sangyo Co., Ltd. manufactures, processes, and sells food products in Japan. The company's flour milling business provides wheat flour, premix, pasta, and baking bread. Its vegetable oils business provides cooking oil, soy protein, and frozen food. The company's starches and sweeteners business offer sweeteners, cornstarch, and modified starch. Its animal feed business supplies compound feed for poultry, pigs, cattle, and fish. The company also provides warehousing business which stores and handlesimported grain, and the real estate business. It is also involved in the insurance agency business, the automobile leasing business, the transportation business, and agribusiness. The company was incorporated in 1936 and is headquartered in Tokyo, Japan.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 2004.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