Mongodb Stock Technical Analysis
| MDB Stock | USD 278.33 5.67 2.00% |
As of the 31st of January, MongoDB secures the Mean Deviation of 2.42, downside deviation of 4.32, and Risk Adjusted Performance of 0.0455. In connection with fundamental indicators, the technical analysis model lets you check existing technical drivers of MongoDB, as well as the relationship between them.
MongoDB Momentum Analysis
Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as MongoDB, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to MongoDBMongoDB |
MongoDB Analyst Consensus
| Target Price | Advice | # of Analysts | |
| 374.78 | Strong Buy | 36 | Odds |
Most MongoDB analysts issue ratings four times a year, at intervals of three months. Ratings are usually accompanied by a target price to helps potential investors understand MongoDB stock's fair price compared to its market value. Analysts arrive at stock ratings after researching public financial statements of MongoDB, talking to its executives and customers, or listening to MongoDB conference calls.
MongoDB technical stock analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, stock market cycles, or different charting patterns.
MongoDB Technical Analysis
The output start index for this execution was fourty-five with a total number of output elements of sixteen. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of MongoDB volatility. High ATR values indicate high volatility, and low values indicate low volatility.
MongoDB Trend Analysis
Use this graph to draw trend lines for MongoDB. You can use it to identify possible trend reversals for MongoDB as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual MongoDB price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.MongoDB Best Fit Change Line
The following chart estimates an ordinary least squares regression model for MongoDB applied against its price change over selected period. The best fit line has a slop of 0.96 , which may imply that the returns on investment in MongoDB will continue to fail. It has 122 observation points and a regression sum of squares at 34506.77, which is the sum of squared deviations for the predicted MongoDB price change compared to its average price change.About MongoDB Technical Analysis
The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of MongoDB on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of MongoDB based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on MongoDB price pattern first instead of the macroeconomic environment surrounding MongoDB. By analyzing MongoDB's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of MongoDB's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to MongoDB specific price patterns or momentum indicators. Please read more on our technical analysis page.
| 2022 | 2023 | 2024 | 2025 (projected) | Graham Number | 34.93 | 28.93 | 26.03 | 16.54 | Receivables Turnover | 4.5 | 5.17 | 4.65 | 3.22 |
MongoDB January 31, 2025 Technical Indicators
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 different 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 |
| Risk Adjusted Performance | 0.0455 | |||
| Market Risk Adjusted Performance | 0.2554 | |||
| Mean Deviation | 2.42 | |||
| Semi Deviation | 4.07 | |||
| Downside Deviation | 4.32 | |||
| Coefficient Of Variation | 2211.71 | |||
| Standard Deviation | 3.68 | |||
| Variance | 13.54 | |||
| Information Ratio | 0.0181 | |||
| Jensen Alpha | 0.0991 | |||
| Total Risk Alpha | (0.24) | |||
| Sortino Ratio | 0.0154 | |||
| Treynor Ratio | 0.2454 | |||
| Maximum Drawdown | 28.87 | |||
| Value At Risk | (4.69) | |||
| Potential Upside | 5.34 | |||
| Downside Variance | 18.67 | |||
| Semi Variance | 16.57 | |||
| Expected Short fall | (2.26) | |||
| Skewness | (1.05) | |||
| Kurtosis | 7.49 |
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.
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