The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. The RSI is most typically used on a 14-day period, measured on a scale from 0 to 100. Traditionally, an asset is considered overbought or overvalued when the RSI is above 70 and oversold or undervalued when it is below 30. A shorter period RSI is more reactive to recent price changes, so it can show early signs of reversals. 9-Day RSI is sometimes used together with 14-Day RSI in a two period divergence strategy.
As of today (2024-04-23), Predictive Oncology's 9-Day RSI is 13.29.
The industry rank for Predictive Oncology's 9-Day RSI or its related term are showing as below:
POAI's 9-Day RSI is ranked better than 98.64% of 884
companies
in the Medical Devices & Instruments industry
Industry Median: 39.37
vs POAI: 13.29
Competitive Comparison
For the Medical Instruments & Supplies subindustry, Predictive Oncology's 9-Day RSI, along with its competitors' market caps and 9-Day RSI data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Predictive Oncology 9-Day RSI Distribution
For the Medical Devices & Instruments industry and Healthcare sector, Predictive Oncology's 9-Day RSI distribution charts can be found below:
* The bar in red indicates where Predictive Oncology's 9-Day RSI falls into.
* Note that the formula uses a positive value for the average loss.
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD. * For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
The Relative Strength Index (RSI), developed by J. Welles Wilder in his book “New Concepts in Technical Trading Systems.”, is a momentum oscillator that measures the speed and change of price movements. The RSI is most typically used on a 14-day period, measured on a scale from 0 to 100.
Traditionally, an asset is considered overbought or overvalued when the RSI is above 70 and oversold or undervalued when it is below 30. A RSI surpasses the 30 level indicates a bullish sign, when it slides below 70 level, it’s a bearish sign. This level can be adjusted depending on the security’s pattern and the market’s underlying trend. In an uptrend or bullish market, the RSI might range within a higher interval, investors could set the support level higher. If a downtrend or bearish market occurs, investors may need to lower the resistance level.
RSI can also be used in trading techniques to indicate the trading signal, such as Divergences and Swing Rejections. A shorter period RSI is more reactive to recent price changes, so it can show early signs of reversals. 9-Day RSI is sometimes used together with 14-Day RSI in a two period divergence strategy.
Predictive Oncology 9-Day RSI Related Terms
Thank you for viewing the detailed overview of Predictive Oncology's 9-Day RSI provided by GuruFocus.com. Please click on the following links to see related term pages.
Predictive Oncology (Predictive Oncology) Business Description
Predictive Oncology Inc functions in the healthcare domain. The firm's reportable segments are Helomics, zPREDICTA, Soluble and Skyline. It derives prime revenue from the Skyline segment which consists of the STREAMWAY System product sales, and TumorGenesis subsidiary (Research and Development) is included within corporate. The STREAMWAY System virtually eliminates staff exposure to blood, irrigation fluid, and other potentially infectious fluids found in the healthcare environment. Its Helomics division is focused on improving the effectiveness of cancer therapy using proprietary, multi-omic tumor profiling platform, a one-of-a-kind database of historical tumor data, and the power of AI to build predictive models of tumor drug response.
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