Mongodb Stock Momentum Indicators Rate of change ratio 100 scale
| MDB Stock | USD 340.16 12.69 3.88% |
| Symbol |
Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Rate of change ratio 100 scale: (price/prevPrice)*100 indicator measures the change in MongoDB price from one period to the next using 100% scale.
MongoDB Technical Analysis Modules
Most technical analysis of MongoDB 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 MongoDB from various momentum indicators to cycle indicators. When you analyze MongoDB 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 | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
About MongoDB 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 MongoDB. We use our internally-developed statistical techniques to arrive at the intrinsic value of MongoDB based on widely used predictive technical indicators. In general, we focus on analyzing MongoDB Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build MongoDB's daily price indicators and compare them against related drivers, such as momentum indicators 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 MongoDB's intrinsic value. In addition to deriving basic predictive indicators for MongoDB, we also check how macroeconomic factors affect MongoDB 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) | Dividend Yield | 9.64E-4 | 3.88E-4 | 0.001532 | 0.001713 | Price To Sales Ratio | 29.93 | 11.45 | 16.96 | 15.31 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of MongoDB's 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.
MongoDB Implied Volatility | 56.5 |
MongoDB's implied volatility exposes the market's sentiment of MongoDB stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if MongoDB's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that MongoDB stock will not fluctuate a lot when MongoDB's options are near their expiration.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards MongoDB in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, MongoDB's short interest history, or implied volatility extrapolated from MongoDB options trading.
Trending Themes
If you are a self-driven investor, you will appreciate our idea-generating investing themes. Our themes help you align your investments inspirations with your core values and are essential building blocks of your portfolios. A typical investing theme is an unweighted collection of up to 20 funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of equities with common characteristics such as industry and growth potential, volatility, or market segment. | Driverless Cars Invested a lot of shares | |
 | Chemicals Invested over 40 shares | |
 | Investor Favorites Invested over 50 shares | |
 | ESG Investing Invested few shares | |
 | Momentum Invested over 70 shares | |
Check out Correlation Analysis to better understand how to build diversified portfolios, which includes a position in MongoDB. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in unemployment. For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.Note that the MongoDB information on this page should be used as a complementary analysis to other MongoDB's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
Complementary Tools for MongoDB Stock analysis
When running MongoDB's price analysis, check to measure MongoDB's 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 MongoDB is operating at the current time. Most of MongoDB's value examination focuses on studying past and present price action to predict the probability of MongoDB's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move MongoDB's price. Additionally, you may evaluate how the addition of MongoDB to your portfolios can decrease your overall portfolio volatility.
| AI Investment Finder Use AI to screen and filter profitable investment opportunities | |
| Global Correlations Find global opportunities by holding instruments from different markets | |
| Portfolio Rebalancing Analyze risk-adjusted returns against different time horizons to find asset-allocation targets | |
| Positions Ratings Determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
| AI Portfolio Architect Use AI to generate optimal portfolios and find profitable investment opportunities | |
| My Watchlist Analysis Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like | |
| Aroon Oscillator Analyze current equity momentum using Aroon Oscillator and other momentum ratios | |
| Portfolio Diagnostics Use generated alerts and portfolio events aggregator to diagnose current holdings | |
| Volatility Analysis Get historical volatility and risk analysis based on latest market data | |
| Correlation Analysis Reduce portfolio risk simply by holding instruments which are not perfectly correlated | |
| Fundamentals Comparison Compare fundamentals across multiple equities to find investing opportunities | |
| Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years |
Is MongoDB's industry expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of MongoDB. If investors know MongoDB will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about MongoDB listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share (2.49) | Revenue Per Share 23.622 | Quarterly Revenue Growth 0.268 | Return On Assets (0.05) | Return On Equity (0.20) |
The market value of MongoDB is measured differently than its book value, which is the value of MongoDB that is recorded on the company's balance sheet. Investors also form their own opinion of MongoDB's value that differs from its market value or its book value, called intrinsic value, which is MongoDB's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because MongoDB's market value can be influenced by many factors that don't directly affect MongoDB's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between MongoDB's value and its price as these two are different measures arrived at by different means. Investors typically determine if MongoDB is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, MongoDB's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.