MongoDB Stock Forecast - Polynomial Regression
| 526 Stock | EUR 304.55 2.60 0.85% |
The Polynomial Regression forecasted value of MongoDB on the next trading day is expected to be 321.56 with a mean absolute deviation of 8.25 and the sum of the absolute errors of 503.01. MongoDB Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of MongoDB's historical fundamentals, such as revenue growth or operating cash flow patterns.
MongoDB |
MongoDB Polynomial Regression Price Forecast For the 3rd of December
Given 90 days horizon, the Polynomial Regression forecasted value of MongoDB on the next trading day is expected to be 321.56 with a mean absolute deviation of 8.25, mean absolute percentage error of 115.20, and the sum of the absolute errors of 503.01.Please note that although there have been many attempts to predict MongoDB Stock prices using its time series forecasting, we generally do not recommend using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that MongoDB's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
MongoDB Stock Forecast Pattern
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MongoDB Forecasted Value
In the context of forecasting MongoDB's Stock value on the next trading day, we examine the predictive performance of the model to find good statistically significant boundaries of downside and upside scenarios. MongoDB's downside and upside margins for the forecasting period are 318.52 and 324.59, respectively. We have considered MongoDB's daily market price to evaluate the above model's predictive performance. Remember, however, there is no scientific proof or empirical evidence that traditional linear or nonlinear forecasting models outperform artificial intelligence and frequency domain models to provide accurate forecasts consistently.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of MongoDB stock data series using in forecasting. Note that when a statistical model is used to represent MongoDB stock, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 122.8572 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 8.2461 |
| MAPE | Mean absolute percentage error | 0.031 |
| SAE | Sum of the absolute errors | 503.0148 |
Predictive Modules for MongoDB
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as MongoDB. Regardless of method or technology, however, to accurately forecast the stock market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the stock market accurately is still an essential part of the overall investment decision process. Using different forecasting techniques and comparing the results might improve your chances of accuracy even though unexpected events may often change the market sentiment and impact your forecasting results.Other Forecasting Options for MongoDB
For every potential investor in MongoDB, whether a beginner or expert, MongoDB's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. MongoDB Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in MongoDB. Basic forecasting techniques help filter out the noise by identifying MongoDB's price trends.MongoDB Related Equities
One of the popular trading techniques among algorithmic traders is to use market-neutral strategies where every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses. Below are some of the equities that can be combined with MongoDB stock to make a market-neutral strategy. Peer analysis of MongoDB could also be used in its relative valuation, which is a method of valuing MongoDB by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
MongoDB Technical and Predictive Analytics
The stock market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of MongoDB's price movements, a comprehensive understanding of forecasting methods that an investor can rely on to make the right move is invaluable. These methods predict trends that assist an investor in predicting the movement of MongoDB's current price.| Cycle Indicators | ||
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| Math Transform | ||
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| Overlap Studies | ||
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| Volume Indicators |
MongoDB Market Strength Events
Market strength indicators help investors to evaluate how MongoDB stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading MongoDB shares will generate the highest return on investment. By undertsting and applying MongoDB stock market strength indicators, traders can identify MongoDB entry and exit signals to maximize returns.
| Accumulation Distribution | 0.0106 | |||
| Daily Balance Of Power | (0.80) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 306.18 | |||
| Day Typical Price | 305.63 | |||
| Market Facilitation Index | 3.25 | |||
| Price Action Indicator | (2.92) | |||
| Period Momentum Indicator | (2.60) |
MongoDB Risk Indicators
The analysis of MongoDB's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in MongoDB's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting mongodb stock prices, we also provide a set of basic risk indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.
| Mean Deviation | 2.21 | |||
| Semi Deviation | 2.09 | |||
| Standard Deviation | 3.03 | |||
| Variance | 9.2 | |||
| Downside Variance | 5.04 | |||
| Semi Variance | 4.37 | |||
| Expected Short fall | (2.78) |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
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 Historical Fundamental Analysis of MongoDB to cross-verify your projections. For more detail on how to invest in MongoDB Stock please use our How to Invest in MongoDB guide.You can also try the Financial Widgets module to easily integrated Macroaxis content with over 30 different plug-and-play financial widgets.