-
1 Comment
K Group Holdings Limited is currently in a long term downtrend where the price is trading 74.2% below its 200 day moving average.
From a valuation standpoint, the stock is 79.3% cheaper than other stocks from the Consumer Cyclical sector with a price to sales ratio of 1.0.
K Group Holdings Limited's total revenue sank by 7.8% to $4M since the same quarter in the previous year.
Its net income has increased by 55.4% to $-216K since the same quarter in the previous year.
Finally, its free cash flow grew by 252.0% to $4M since the same quarter in the previous year.
Based on the above factors, K Group Holdings Limited gets an overall score of 3/5.
| Industry | Restaurants |
|---|---|
| Sector | Consumer Cyclical |
| CurrencyCode | HKD |
| Exchange | HK |
| ISIN | KYG525891019 |
| Market Cap | 29M |
|---|---|
| PE Ratio | None |
| Beta | 0.15 |
| Dividend Yield | 0.0% |
| Target Price | None |
K Group Holdings Limited, an investment holding company, engages in the restaurant and catering business in Singapore and Indonesia. It operates multi-branded restaurants that are mainly operated under a franchise model. The company offers Korean, Japanese, and Malaysian cuisines with casual dining concepts for the middle-income mass market. As of 31 August, 2022, it operates through 11 self-operated restaurants under Chir Chir, Masizzim, Kogane Yama, Nipong Naepong, NY Night Market, Sora Boru, Kota Zheng Zhong, and The Chir Cafe and Bar brands, as well as 1 central kitchen under the Gangnam Kitchen brand. The company was incorporated in 2014 and is headquartered in Singapore.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for 8475.HK 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 2024
