-
1 Comment
Prakash Pipes Limited is currently in a long term uptrend where the price is trading 52.2% above its 200 day moving average.
From a valuation standpoint, the stock is 99.9% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 0.6.
Prakash Pipes Limited's total revenue rose by 36.6% to $1B since the same quarter in the previous year.
Its net income has increased by 23.8% to $92M since the same quarter in the previous year.
Based on the above factors, Prakash Pipes Limited gets an overall score of 4/5.
Exchange | NSE |
---|---|
CurrencyCode | INR |
ISIN | INE050001010 |
Sector | Industrials |
Industry | Building Products & Equipment |
Beta | -0.01 |
---|---|
Market Cap | 7B |
Target Price | None |
Dividend Yield | 0.0% |
PE Ratio | 10.33 |
Prakash Pipes Limited manufactures and sells PVC pipes, fittings, and flexible packaging solutions in India and internationally. It offers uPVC pipes, casing pipes, plumbing uPVC pipes, soil waste rain (SWR) pipes, column pipes, agri pipes, garden pipes, water tanks, HDPE drums, and related fittings catering to applications in irrigation, drainage, housing, and sanitation. The company also provides flexible packaging products, including multilayer films and laminates, pouches, labels, blown PE films, rotogravure cylinders, and printing inks for packaging consumer goods, such as snacks, soaps, shampoos, food, beverages, oils, personal care, and pharmaceutical products. It offers its products under the Prakash brand name. Prakash Pipes Limited was founded in 1981 and is based in New Delhi, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for PPL.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