-
1 Comment
Gokul Agro Resources Limited is currently in a long term uptrend where the price is trading 74.3% above its 200 day moving average.
From a valuation standpoint, the stock is 100.0% cheaper than other stocks from the Consumer Defensive sector with a price to sales ratio of 0.0.
Gokul Agro Resources Limited's total revenue rose by 41.1% to $23B since the same quarter in the previous year.
Its net income has increased by 70.2% to $122M since the same quarter in the previous year.
Finally, its free cash flow grew by 111.7% to $2B since the same quarter in the previous year.
Based on the above factors, Gokul Agro Resources Limited gets an overall score of 5/5.
Exchange | NSE |
---|---|
CurrencyCode | INR |
ISIN | INE314T01025 |
Sector | Consumer Defensive |
Industry | Packaged Foods |
Market Cap | 36B |
---|---|
PE Ratio | 14.7 |
Target Price | None |
Beta | 0.28 |
Dividend Yield | None |
Gokul Agro Resources Limited engages in the manufacture and trading of edible and non-edible oils, meals, and other agro products in India. It offers edible oils, such as refined soyabean and sunflower, kachi ghani mustard, refined and filtered groundnut, palm, refined cottonseed and rice bran, vanaspati, and palmolein oils, as well as ultimate frying oil. The company also provides castor oils and derivatives; castor, mustard, and soya feed cake; and specialty fats for the bakery and confectionery industries. It offers its products under the Vitalife, Mahek, Pride, and Richfield brand names. The company also exports its products. Gokul Agro Resources Limited was incorporated in 2014 and is based in Ahmedabad, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for GOKULAGRO.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