MongoDB (Germany) Market Value
| 526 Stock | EUR 304.55 2.60 0.85% |
| Symbol | MongoDB |
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.
| 05/06/2024 |
| 12/02/2024 |
If you would invest 0.00 in MongoDB on May 6, 2024 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 210 days. MongoDB is related to or competes with REVO INSURANCE, CVW CLEANTECH, Nufarm, Ultra Clean, Penta-Ocean Construction, Goosehead Insurance, and INSURANCE AUST. 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 | 2.25 | |||
| Information Ratio | 0.0428 | |||
| Maximum Drawdown | 16.45 | |||
| Value At Risk | (4.26) | |||
| Potential Upside | 6.2 |
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 | 0.0748 | |||
| Jensen Alpha | 0.2029 | |||
| Total Risk Alpha | (0.25) | |||
| Sortino Ratio | 0.0578 | |||
| Treynor Ratio | 0.6041 |
MongoDB Backtested Returns
MongoDB appears to be very steady, given 3 months investment horizon. MongoDB has Sharpe Ratio of 0.1, which conveys that the firm had a 0.1% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for MongoDB, which you can use to evaluate the volatility of the firm. Please exercise MongoDB's Mean Deviation of 2.21, downside deviation of 2.25, and Risk Adjusted Performance of 0.0748 to check out if our risk estimates are consistent with your expectations. On a scale of 0 to 100, MongoDB holds a performance score of 8. The company secures a Beta (Market Risk) of 0.43, which conveys possible diversification benefits within a given portfolio. 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. Please check MongoDB's downside deviation, standard deviation, total risk alpha, as well as the relationship between the coefficient of variation and jensen alpha , to make a quick decision on whether MongoDB's current price movements will revert.
Auto-correlation | -0.36 |
Poor reverse predictability
MongoDB has poor reverse predictability. Overlapping area represents the amount of predictability between MongoDB time series from 6th of May 2024 to 19th of August 2024 and 19th of August 2024 to 2nd of December 2024. 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 -0.36 indicates that just about 36.0% of current MongoDB price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.36 | |
| Spearman Rank Test | -0.5 | |
| Residual Average | 0.0 | |
| Price Variance | 582.43 |
MongoDB lagged returns against current returns
Autocorrelation, which is MongoDB stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting MongoDB's stock expected returns. We can calculate the autocorrelation of MongoDB returns to help us make a trade decision. For example, suppose you find that MongoDB has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
MongoDB regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If MongoDB stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if MongoDB stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in MongoDB stock over time.
Current vs Lagged Prices |
| Timeline |
MongoDB Lagged Returns
When evaluating MongoDB's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of MongoDB stock have on its future price. MongoDB autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, MongoDB autocorrelation shows the relationship between MongoDB stock current value and its past values and can show if there is a momentum factor associated with investing in MongoDB.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Additional Information and Resources on Investing in MongoDB Stock
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 Alpha and Beta module to complement your research on MongoDB. For more detail on how to invest in MongoDB Stock please use our How to Invest in MongoDB guide.You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.
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.