-
1 Comment
Silly Monks Entertainment Limited is currently in a long term downtrend where the price is trading 6.0% below its 200 day moving average.
From a valuation standpoint, the stock is 95.2% cheaper than other stocks from the Communication Services sector with a price to sales ratio of 0.7.
Silly Monks Entertainment Limited's total revenue sank by 29.2% to $101M since the same quarter in the previous year.
Its net income has dropped by 668.1% to $-36M since the same quarter in the previous year.
Finally, its free cash flow fell by 280.5% to $-3M since the same quarter in the previous year.
Based on the above factors, Silly Monks Entertainment Limited gets an overall score of 1/5.
ISIN | INE203Y01012 |
---|---|
Industry | Entertainment |
Sector | Communication Services |
CurrencyCode | INR |
Exchange | NSE |
Target Price | None |
---|---|
Dividend Yield | 0.0% |
Beta | 0.45 |
PE Ratio | None |
Market Cap | 180M |
Silly Monks Entertainment Limited engages in the production, publishing, distribution, and marketing of audio and video content in India and internationally. The company is involved in the digital media publishing; movie/series/music/other creator content production; celebrity digital management; marketing and promotion on digital and traditional mediums; content distribution and syndication on satellite channels, cinema theatres, airborne, and other offline platforms; and online advertising for films with Google AdWords. Silly Monks Entertainment Limited was incorporated in 2013 and is based in Hyderabad, India.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for SILLYMONKS.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 2024