A market screener is the technical analysis tool for minimizing the task of narrowing down relevant data to help your customers make more precise decisions. Market screeners are available to financial institutions as an out-of-the-box solution, as SaaS with the capacity for easy integration with native Java and universal REST APIs for brokerages, stock trading courses, and financial media outlets.
An Added Value Service for Brokerages
Brokerages can offer market screeners as a tool for traders to create customizable alerts and rating systems. By using a market screener as part of a brokerage’s service, traders can receive notifications from within their own criteria and metrics, then seamlessly transition a trader onto the brokerage’s platform to double check their analysis and charts against the trading book and make the trade.
Filters can be totally customizable, and users may create searches and alerts by integrating intuitive scripting languages— an easy to use algorithmic method of monitoring all your favorite criteria and indicators, saving huge amounts of time and increasing the accuracy of the analysis.
Brokerages can easily add new unique features to their trading or analysis software. Market screeners can be customized and integrated into any trading platform or a web page. It delivers strong competitive advantages without the need for costly development, licenses and hardware investments.
Let’s say an investor is looking to invest in the retail market according to the following criteria:
- P/E less than Retail Industry Median
- EV/EBITDA 12 Months-Most Recent less than Retail-Industry Median
- P/S less than Retail-Industry Median
- Current Price greater than or equal to $5
For the found set of stocks, if a user is looking for a buying opportunity, the following can be done:
Using embedded filters for Technical analysis, the user looks for stocks with RSI below 40. If he is not very satisfied and wants to make the request more precise, he can switch to the code editor and implement his idea:
Fetch stocks with daily volume around 100k for which the RSI(14) has been decreasing for a 3 day-period that ended 2 days ago, increasing for the last 2 days and is below 40. Sort it by market capitalization.
By using the following code in a scripting language:
def avgVol = avg(volume, 30); // calculate average 30 days volume filter 90000 < avgVol && avgVol < 110000; // fetch stocks with average volume around 100k def rsi = RSI(n=14); // 14 days RSI // calculate RSI(14) filter isDecreasing(rsi, 3) && isIncreasing (rsi, 2) && rsi < 40; // set parameters for RSI (14) sort marketCap; // sort by market capitalization set limit = 50; // take top 50
He gets a small number of stocks which match his precise criteria. He clicks on tickers to see charts for them and if the radar tool is integrated with the trading platform of a broker he can further open a chart in his trading platform for a better appearance.
Educational Platforms can Offer Traders a Unique Educational Experience
A Market Screener can be used by educational platforms to teach traders how to make decisions or find entry and exit points. As well, prospective traders will be able to find instruments with very high potential for growth or decline, and select instruments that fall into multiple criteria that no one else can select; instruments that combine fundamental and technical analysis, with historical performance.
An educational platform is able to integrate their own unique infrastructure or platform and customize it to suit their needs. Traders are able to test strategies on historical market data. With a scripting language feature, educational platforms can create incrementally advanced programs and scenarios as well as offer niche and specific training on isolated metrics and criteria.
Educational companies can teach students how to select certain criteria to achieve their desired result and prove their investment strategies.
Financial Media will know more and offer more
A market screener offers additional value for their readers. It can be offered as a free service, a pro-subscription, or both. This allows the media outlet to offer additional features and services to keep readers coming back. A fully customizable market screener can act as a unique tool for readers to further educate themselves with concrete data, with the option of offering a more advanced pro-subscription tool.
A Financial Media outlet can support its news or market analysis departments to help generate more up-to-date content. Copywriters and market analysts can be alerted quickly to market changes by honing in on particular market instruments with an extensive array of metrics and use a scripting language for narrowed analysis thereby being able to offer more timely and accurate news for their readers.
To illustrate the benefits for financial media, think of how news today is consumed, as opposed to 7-10 years ago.
Nowadays, everything is moving online, including newspapers, making it worthwhile for the editors to invest more money in their news web portal. Before that, in a printed magazine that was issued in the early mornings, the quotes of most popular indexes were printed, and thus static. Now, these quotes are live and constantly being updated on financial news websites.
As well, many media outlets request that their readers be registered and logged users. An online news source can learn what a specific user is interested in and adjust the displayed quotes on the website according to the requests they’ve entered into a market screener that has been integrated into their services.
Not only will the quotes become targeted, but also news articles, e.g. if the user is consistently interested in the oil sector (because that’s what he requests in the market scanner), he will be shown articles about the oil and gas sector, selected among thousands of other articles published daily in a popular online news source. That will make the reader feel more informed and individually approached. In other words, the filters set by a user in an integrated market scanner is an opportunity for news outlets to offer individual user experiences.