-
1 Comment
Suryalakshmi Cotton Mills Limited is currently in a long term uptrend where the price is trading 102.7% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.1.
Suryalakshmi Cotton Mills Limited's total revenue rose by 7.5% to $2B since the same quarter in the previous year.
Its net income has increased by 103.4% to $2M since the same quarter in the previous year.
Finally, its free cash flow fell by 69.7% to $164M since the same quarter in the previous year.
Based on the above factors, Suryalakshmi Cotton Mills Limited gets an overall score of 4/5.
ISIN | INE713B01026 |
---|---|
Sector | Consumer Cyclical |
Industry | Textile Manufacturing |
Exchange | NSE |
CurrencyCode | INR |
Market Cap | 1B |
---|---|
Target Price | None |
PE Ratio | 67.99 |
Beta | 0.65 |
Dividend Yield | None |
Suryalakshmi Cotton Mills Limited engages in the manufacture and sale of cotton and blended yarns, denim fabrics, and garments in India, Bangladesh, Ethiopia, Guatemala, Kenya, Mauritius, Madagascar, South Korea, and internationally. It operates through two segments: Spinning and Denim (Fabrics). The Spinning segment offers yarns, such as cotton, polyester, viscose, and ring spun fibres. The Denim segment provides a range of denim fabrics, including coloured, mercerized, dyed, coated, stretch, and rigid fabrics. It serves private labels, fashion brands, and retail chains. The company was incorporated in 1962 and is based in Secunderabad, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for SURYALAXMI.NSE 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