-
1 Comment
Brave Bison Group plc is currently in a long term uptrend where the price is trading 28.3% above its 200 day moving average.
From a valuation standpoint, the stock is 93.2% cheaper than other stocks from the Communication Services sector with a price to sales ratio of 0.7.
Based on the above factors, Brave Bison Group plc gets an overall score of 2/5.
Industry | Internet Content & Information |
---|---|
Sector | Communication Services |
ISIN | GB00BF8HJ774 |
CurrencyCode | GBP |
Exchange | LSE |
Target Price | 0.38 |
---|---|
PE Ratio | 0.0 |
Beta | 0.69 |
Dividend Yield | 0.0% |
Market Cap | 38M |
Brave Bison Group plc operates as a digital advertising agency in the United Kingdom, Europe, the Asia-Pacific, and internationally. It engages in the creation, distribution, and monetization of online video content through The Hook on Instagram; The Wave House on TikTok; and Slick on Snapchat, as well as on behalf of channel partners, such as PGA Tour and US Open on YouTube. The company also buys media across advertising platforms, as well as directly from creators; and manages transactional platforms for customers. It helps content owners, operators, brands, publishers, and advertisers to build and engage online audiences; and enables its clients to commercialize their content to audiences on various online video platforms, such as YouTube, Facebook, and Snapchat. The company was formerly known as Rightster Group Plc and changed its name to Brave Bison Group Plc in May 2016. Brave Bison Group plc was founded in 2011 and is based in London, the United Kingdom.
Learn MoreHere's how to backtest a trading strategy or backtest a portfolio for BBSN.LSE 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