-
1 Comment
Coffee Day Enterprises Limited is currently in a long term uptrend where the price is trading 49.2% 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.
Coffee Day Enterprises Limited's total revenue sank by 63.7% to $1B since the same quarter in the previous year.
Its net income has increased by 11.3% to $-661M since the same quarter in the previous year.
Based on the above factors, Coffee Day Enterprises Limited gets an overall score of 3/5.
| Exchange | NSE |
|---|---|
| CurrencyCode | INR |
| Sector | Consumer Cyclical |
| Industry | Restaurants |
| ISIN | INE335K01011 |
| Market Cap | 6B |
|---|---|
| PE Ratio | None |
| Target Price | 350 |
| Beta | 0.19 |
| Dividend Yield | None |
Coffee Day Enterprises Limited, together with its subsidiaries, primarily operates Café Coffee Day outlets in India, Europe, Japan, and internationally. It operates through Coffee and Related Business, Hospitality services, and Others segments. The company operates Coffee Day Square, a premium café; and Coffee Day Xpress, an on-the-go food and beverages kiosk, as well as offers semi-automatic and automatic vending machines. It also retails coffee products; develops technology parks/ special economic zones; owns and operates luxury resorts located in Chikmangalur, Bandipur, and Kabini, Karnataka under The Serai brand; provides facilities for information technology (IT)/IT-enabled services; and investment services. Coffee Day Enterprises Limited was founded in 1993 and is based in Bengaluru, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for COFFEEDAY.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
