Bm Technologies Stock Overlap Studies Bollinger Bands
| BMTX Stock | USD 4.77 0.02 0.42% |
| Symbol |
The output start index for this execution was thirteen with a total number of output elements of fourty-eight. The Bollinger Bands is very popular indicator that was developed by John Bollinger. It consist of three lines. Bm Technologies middle band is a simple moving average of its typical price. The upper and lower bands are (N) standard deviations above and below the middle band. The bands widen and narrow when the volatility of the price is higher or lower, respectively. The upper and lower bands can also be interpreted as price targets for Bm Technologies. When the price bounces off of the lower band and crosses the middle band, then the upper band becomes the price target.
Bm Technologies Technical Analysis Modules
Most technical analysis of Bm Technologies help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for BMTX from various momentum indicators to cycle indicators. When you analyze BMTX charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.| Cycle Indicators | ||
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| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About Bm Technologies Predictive Technical Analysis
Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Bm Technologies. We use our internally-developed statistical techniques to arrive at the intrinsic value of Bm Technologies based on widely used predictive technical indicators. In general, we focus on analyzing BMTX Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Bm Technologies's daily price indicators and compare them against related drivers, such as overlap studies and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Bm Technologies's intrinsic value. In addition to deriving basic predictive indicators for Bm Technologies, we also check how macroeconomic factors affect Bm Technologies price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
| 2021 | 2022 | 2023 | 2024 (projected) | Days Sales Outstanding | 35.33 | 36.06 | 60.3 | 54.13 | PTB Ratio | 2.87 | 1.27 | 0.77 | 0.73 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Bm Technologies' price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
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Additional Tools for BMTX Stock Analysis
When running Bm Technologies' price analysis, check to measure Bm Technologies' market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Bm Technologies is operating at the current time. Most of Bm Technologies' value examination focuses on studying past and present price action to predict the probability of Bm Technologies' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Bm Technologies' price. Additionally, you may evaluate how the addition of Bm Technologies to your portfolios can decrease your overall portfolio volatility.