Mongodb Stock Market Value
| MDB Stock | USD 357.77 13.42 3.90% |
| Symbol | MongoDB |
Is Internet Services & Infrastructure space 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. Expected growth trajectory for MongoDB significantly influences the price investors are willing to assign. The financial industry is built on trying to define current growth potential and future valuation accurately. Comprehensive MongoDB assessment requires weighing all these inputs, though not all factors influence outcomes equally.
Earnings Share (0.83) | Revenue Per Share | Quarterly Revenue Growth 0.187 | Return On Assets | Return On Equity |
Understanding MongoDB requires distinguishing between market price and book value, where the latter reflects MongoDB's accounting equity. The concept of intrinsic value - what MongoDB's is actually worth based on fundamentals - guides informed investors toward better entry and exit points. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Market sentiment, economic cycles, and investor behavior can push MongoDB's price substantially above or below its fundamental value.
Understanding that MongoDB's value differs from its trading price is crucial, as each reflects different aspects of the company. Evaluating whether MongoDB represents a sound investment requires analyzing earnings trends, revenue growth, technical signals, industry dynamics, and expert forecasts. In contrast, MongoDB's trading price reflects the actual exchange value where willing buyers and sellers reach mutual agreement.
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.
| 11/12/2025 |
| 02/10/2026 |
If you would invest 0.00 in MongoDB on November 12, 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 CyberArk Software, Super Micro, Samsara, Sandisk Corp, VeriSign, Teradyne, and Affirm Holdings. 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 | 3.12 | |||
| Information Ratio | (0) | |||
| Maximum Drawdown | 31.24 | |||
| Value At Risk | (5.91) | |||
| Potential Upside | 5.3 |
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 | 0.0247 | |||
| Jensen Alpha | (0.05) | |||
| Total Risk Alpha | (0.37) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.0507 |
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 February 10, 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 | 0.0247 | |||
| Market Risk Adjusted Performance | 0.0607 | |||
| Mean Deviation | 2.56 | |||
| Semi Deviation | 3.02 | |||
| Downside Deviation | 3.12 | |||
| Coefficient Of Variation | 4794.63 | |||
| Standard Deviation | 4.03 | |||
| Variance | 16.25 | |||
| Information Ratio | (0) | |||
| Jensen Alpha | (0.05) | |||
| Total Risk Alpha | (0.37) | |||
| Sortino Ratio | (0) | |||
| Treynor Ratio | 0.0507 | |||
| Maximum Drawdown | 31.24 | |||
| Value At Risk | (5.91) | |||
| Potential Upside | 5.3 | |||
| Downside Variance | 9.72 | |||
| Semi Variance | 9.11 | |||
| Expected Short fall | (2.99) | |||
| Skewness | 2.35 | |||
| Kurtosis | 13.39 |
MongoDB Backtested Returns
At this point, MongoDB is very steady. MongoDB has Sharpe Ratio of 0.0111, which conveys that the firm had a 0.0111 % return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for MongoDB, which you can use to evaluate the volatility of the firm. Please verify MongoDB's Risk Adjusted Performance of 0.0247, downside deviation of 3.12, and Mean Deviation of 2.56 to check out if the risk estimate we provide is consistent with the expected return of 0.0465%. The company secures a Beta (Market Risk) of 1.46, which conveys a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, MongoDB will likely underperform. MongoDB right now secures a risk of 4.19%. Please verify MongoDB semi variance, rate of daily change, and the relationship between the value at risk and kurtosis , to decide if MongoDB will be following its current price movements.
Auto-correlation | -0.66 |
Very good reverse predictability
MongoDB has very good reverse predictability. Overlapping area represents the amount of predictability between MongoDB time series from 12th of November 2025 to 27th of December 2025 and 27th of December 2025 to 10th 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 -0.66 indicates that around 66.0% of current MongoDB price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.66 | |
| Spearman Rank Test | -0.56 | |
| Residual Average | 0.0 | |
| Price Variance | 860.65 |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether MongoDB offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of MongoDB's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Mongodb Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Mongodb Stock:Check out MongoDB Correlation, MongoDB Volatility and MongoDB Performance module to complement your research on MongoDB. For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.You can also try the Top Crypto Exchanges module to search and analyze digital assets across top global cryptocurrency exchanges.
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.