Mongodb Stock Statistic Functions Linear Regression Intercept

MDB Stock  USD 358.64  0.16  0.04%   
MongoDB statistic functions tool provides the execution environment for running the Linear Regression Intercept function and other technical functions against MongoDB. MongoDB value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of statistic functions indicators. As with most other technical indicators, the Linear Regression Intercept function function is designed to identify and follow existing trends. MongoDB statistical functions help analysts to determine different price movement patterns based on how price series statistical indicators change over time. Please specify Time Period to run this model.

Function
Time Period
Execute Function
Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Linear Regression Intercept is the expected mean value of MongoDB price seriese where values of its benchmark or peer price series are zero.

MongoDB Technical Analysis Modules

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 other indicators across different periods to confirm that a breakdown or reversion is likely to occur.

About MongoDB Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of MongoDB. We use our internally-developed statistical techniques to arrive at the intrinsic value of MongoDB based on widely used predictive technical indicators. In general, we focus on analyzing MongoDB Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build MongoDB's daily price indicators and compare them against related drivers, such as statistic functions and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of MongoDB's intrinsic value. In addition to deriving basic predictive indicators for MongoDB, we also check how macroeconomic factors affect MongoDB price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2021 2022 2023 2024 (projected)
Dividend Yield9.64E-43.88E-40.0015320.001713
Price To Sales Ratio29.9311.4516.9615.31
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.
Hype
Prediction
LowEstimatedHigh
355.26358.25361.24
Details
Intrinsic
Valuation
LowRealHigh
322.92383.10386.09
Details
34 Analysts
Consensus
LowTargetHigh
393.59432.52480.10
Details
Earnings
Estimates (0)
LowProjected EPSHigh
0.340.400.83
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as MongoDB. Your research has to be compared to or analyzed against MongoDB's peers to derive any actionable benefits. When done correctly, MongoDB's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in MongoDB.

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As an individual investor, you need to find a reliable way to track all your investment portfolios' performance accurately. However, your requirements will often be based on how much of the process you decide to do yourself. In addition to allowing you full analytical transparency into your positions, our tools can tell you how much better you can do without increasing your risk or reducing expected return.

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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 Correlation Analysis to better understand how to build diversified portfolios, which includes a position in MongoDB. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in unemployment.
For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.
Note that the MongoDB information on this page should be used as a complementary analysis to other MongoDB's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.

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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Is MongoDB's industry 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. If investors know MongoDB will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about MongoDB listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share
(2.48)
Revenue Per Share
23.622
Quarterly Revenue Growth
0.268
Return On Assets
(0.05)
Return On Equity
(0.20)
The market value of MongoDB is measured differently than its book value, which is the value of MongoDB that is recorded on the company's balance sheet. Investors also form their own opinion of MongoDB's value that differs from its market value or its book value, called intrinsic value, which is MongoDB's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because MongoDB's market value can be influenced by many factors that don't directly affect MongoDB's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between MongoDB's value and its price as these two are different measures arrived at by different means. Investors typically determine if MongoDB is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, MongoDB's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.