-
1 Comment
Apollo Pipes Limited is currently in a long term uptrend where the price is trading 33.2% above its 200 day moving average.
From a valuation standpoint, the stock is 62.8% cheaper than other stocks from the Industrials sector with a price to sales ratio of 3.1.
Apollo Pipes Limited's total revenue rose by 28.0% to $1B since the same quarter in the previous year.
Its net income has increased by 145.0% to $163M since the same quarter in the previous year.
Based on the above factors, Apollo Pipes Limited gets an overall score of 4/5.
Exchange | NSE |
---|---|
CurrencyCode | INR |
ISIN | INE126J01016 |
Sector | Industrials |
Industry | Building Products & Equipment |
Beta | 0.48 |
---|---|
PE Ratio | 52.89 |
Target Price | 481.875 |
Dividend Yield | 0.3% |
Market Cap | 18B |
Apollo Pipes Limited manufactures and trades in polyvinyl chloride (PVC) pipes and fittings in India. The company offers cPVC, uPVC, and PPR-C plumbing systems; uPVC pressure pipes and fittings; uPVC SWR drainage system; and HDPE pipes, coils, and sprinkler systems. It also provides underground drainage, column, PVC-O, garden, and casing pipes; water tanks, solvent cement, and kitchen sink. In addition, the company offers bath fittings, which include faucets, showers, health faucets, cistern, seat covers, accessories, and allied products. It provides its products to agriculture, water management, construction, infrastructure, and telecom ducting industries. Apollo Pipes Limited was incorporated in 1985 and is headquartered in Noida, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for APOLLOPIPE.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