-
1 Comment
Kewal Kiran Clothing Limited is currently in a long term uptrend where the price is trading 4.2% above its 200 day moving average.
From a valuation standpoint, the stock is 99.3% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 3.3.
Kewal Kiran Clothing Limited's total revenue sank by 6.5% to $1B since the same quarter in the previous year.
Its net income has dropped by 6.1% to $108M since the same quarter in the previous year.
Finally, its free cash flow grew by 12.9% to $61M since the same quarter in the previous year.
Based on the above factors, Kewal Kiran Clothing Limited gets an overall score of 3/5.
| Sector | Consumer Cyclical |
|---|---|
| Industry | Apparel Manufacturing |
| Exchange | NSE |
| CurrencyCode | INR |
| ISIN | INE401H01017 |
| Beta | 0.14 |
|---|---|
| Market Cap | 29B |
| PE Ratio | 18.91 |
| Target Price | 817 |
| Dividend Yield | None |
Kewal Kiran Clothing Limited manufacturing, marketing, and retailing of branded readymade garments and finished accessories in India and internationally. It offers jeans, shirts, trousers, t-shirt, and other products; and winterwear, athleisure, casual blazer, and accessories under the Killer, Easies, Lawman, Integriti, Desi Belle, Izel, and Iti brand names. The company distributes its products through exclusive brand outlets, large-format stores, traditional multi-brand outlets, and e-commerce platforms. Kewal Kiran Clothing Limited was founded in 1980 and is based in Mumbai, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for KKCL.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
