MongoDB (Germany) Technical Analysis
| 526 Stock | EUR 290.95 10.65 3.53% |
As of the 22nd of February, MongoDB secures the Downside Deviation of 3.34, risk adjusted performance of 0.0135, and Mean Deviation of 2.73. MongoDB technical analysis lets you operate historical price patterns with an objective to determine a pattern that forecasts the direction of the firm's future prices. Please verify MongoDB downside deviation, standard deviation, information ratio, as well as the relationship between the coefficient of variation and variance to decide if MongoDB is priced some-what accurately, providing market reflects its recent price of 290.95 per share.
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 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to MongoDB's stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of MongoDB.
| 11/24/2025 |
| 02/22/2026 |
If you would invest 0.00 in MongoDB on November 24, 2025 and sell it all today you would earn a total of 0.00 from holding MongoDB or generate 0.0% return on investment in MongoDB over 90 days. MongoDB is related to or competes with Cleanaway Waste, Waste Management, Corporate Travel, Ares Management, Jupiter Fund, LG Display, and TRAVEL LEISURE. MongoDB, Inc. provides general purpose database platform worldwide More
MongoDB Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure MongoDB's stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess MongoDB upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 3.34 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 32.11 | |||
| Value At Risk | (6.18) | |||
| Potential Upside | 5.28 |
MongoDB Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for MongoDB's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as MongoDB's standard deviation. In reality, there are many statistical measures that can use MongoDB historical prices to predict the future MongoDB's volatility.| Risk Adjusted Performance | 0.0135 | |||
| Jensen Alpha | (0.0006) | |||
| Total Risk Alpha | (0.36) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0682 |
MongoDB February 22, 2026 Technical Indicators
| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
| Risk Adjusted Performance | 0.0135 | |||
| Market Risk Adjusted Performance | 0.0782 | |||
| Mean Deviation | 2.73 | |||
| Semi Deviation | 3.28 | |||
| Downside Deviation | 3.34 | |||
| Coefficient Of Variation | 14182.49 | |||
| Standard Deviation | 4.14 | |||
| Variance | 17.13 | |||
| Information Ratio | (0.01) | |||
| Jensen Alpha | (0.0006) | |||
| Total Risk Alpha | (0.36) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0682 | |||
| Maximum Drawdown | 32.11 | |||
| Value At Risk | (6.18) | |||
| Potential Upside | 5.28 | |||
| Downside Variance | 11.14 | |||
| Semi Variance | 10.79 | |||
| Expected Short fall | (3.03) | |||
| Skewness | 2.26 | |||
| Kurtosis | 13.08 |
MongoDB Backtested Returns
At this point, MongoDB is very steady. MongoDB has Sharpe Ratio of 0.0269, which conveys that the firm had a 0.0269 % return per unit of risk over the last 3 months. We have found thirty technical indicators for MongoDB, which you can use to evaluate the volatility of the firm. Please verify MongoDB's Downside Deviation of 3.34, mean deviation of 2.73, and Risk Adjusted Performance of 0.0135 to check out if the risk estimate we provide is consistent with the expected return of 0.11%. MongoDB has a performance score of 2 on a scale of 0 to 100. The company secures a Beta (Market Risk) of 0.28, which conveys not very significant fluctuations relative to the market. As returns on the market increase, MongoDB's returns are expected to increase less than the market. However, during the bear market, the loss of holding MongoDB is expected to be smaller as well. MongoDB right now secures a risk of 4.25%. Please verify MongoDB standard deviation, total risk alpha, and the relationship between the coefficient of variation and jensen alpha , to decide if MongoDB will be following its current price movements.
Auto-correlation | -0.65 |
Very good reverse predictability
MongoDB has very good reverse predictability. Overlapping area represents the amount of predictability between MongoDB time series from 24th of November 2025 to 8th of January 2026 and 8th of January 2026 to 22nd of February 2026. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of MongoDB price movement. The serial correlation of -0.65 indicates that roughly 65.0% of current MongoDB price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.65 | |
| Spearman Rank Test | -0.66 | |
| Residual Average | 0.0 | |
| Price Variance | 523.93 |
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 ten with a total number of output elements of fifty-one. The Normalized Average True Range is used to analyze tradable apportunities for MongoDB across different markets.
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.
MongoDB February 22, 2026 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 | 0.0135 | |||
| Market Risk Adjusted Performance | 0.0782 | |||
| Mean Deviation | 2.73 | |||
| Semi Deviation | 3.28 | |||
| Downside Deviation | 3.34 | |||
| Coefficient Of Variation | 14182.49 | |||
| Standard Deviation | 4.14 | |||
| Variance | 17.13 | |||
| Information Ratio | (0.01) | |||
| Jensen Alpha | (0.0006) | |||
| Total Risk Alpha | (0.36) | |||
| Sortino Ratio | (0.02) | |||
| Treynor Ratio | 0.0682 | |||
| Maximum Drawdown | 32.11 | |||
| Value At Risk | (6.18) | |||
| Potential Upside | 5.28 | |||
| Downside Variance | 11.14 | |||
| Semi Variance | 10.79 | |||
| Expected Short fall | (3.03) | |||
| Skewness | 2.26 | |||
| Kurtosis | 13.08 |
MongoDB February 22, 2026 Daily Trend Indicators
Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as MongoDB stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.
| Accumulation Distribution | 0.05 | ||
| Daily Balance Of Power | (0.73) | ||
| Rate Of Daily Change | 0.96 | ||
| Day Median Price | 298.20 | ||
| Day Typical Price | 295.78 | ||
| Price Action Indicator | (12.58) | ||
| Market Facilitation Index | 14.50 |
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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