-
1 Comment
Indian Metals and Ferro Alloys Limited is currently in a long term uptrend where the price is trading 54.8% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Basic Materials sector with a price to sales ratio of 0.8.
Indian Metals and Ferro Alloys Limited's total revenue rose by 7.0% to $4B since the same quarter in the previous year.
Its net income has increased by 611.0% to $324M since the same quarter in the previous year.
Finally, its free cash flow grew by 310.4% to $1B since the same quarter in the previous year.
Based on the above factors, Indian Metals and Ferro Alloys Limited gets an overall score of 5/5.
Sector | Basic Materials |
---|---|
Exchange | NSE |
CurrencyCode | INR |
ISIN | INE919H01018 |
Industry | Steel |
PE Ratio | 8.34 |
---|---|
Dividend Yield | 3.5% |
Market Cap | 35B |
Target Price | 421 |
Beta | 0.12 |
Indian Metals and Ferro Alloys Limited engages in the production and sale of ferro chrome in India and internationally. The company operates through three segments: Ferro Alloys, Power, and Mining segments. It operates a power generation plant with a total capacity of 204.55 MW, including 4.55 MWp from solar; and two chrome ore mines, as well as manufacturing plant for low density aggregates and fly ash bricks for use in road construction and cement manufacturing units. The company offers its products to stainless steel manufacturers and international traders. It exports its products to South Korea, China, Taiwan, and Japan. The company was incorporated in 1961 and is headquartered in Bhubaneswar, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for IMFA.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