MongoDB Price to Earnings Ratio Trend from 2010 to 2023

MDB Stock  USD 224.01  15.78  7.58%   
MongoDB Price to Earnings Ratio are decreasing over the years with slightly volatile fluctuation. Price to Earnings Ratio are expected to dwindle to -82.82. From 2010 to 2023 MongoDB Price to Earnings Ratio quarterly data regression line had arithmetic mean of(34.90) and r-squared of  0.79. MongoDB Direct Expenses is projected to increase significantly based on the last few years of reporting. The past year's Direct Expenses was at 233.54 Million. The current year Cost of Revenue is expected to grow to about 322 M, whereas Consolidated Income is forecasted to decline to (283.4 M).
  
Check MongoDB financial statements over time to gain insight into future company performance. You can evaluate financial statements to find patterns among MongoDB main balance sheet or income statement drivers, such as Direct Expenses of 252 M, Cost of Revenue of 322 M or Gross Profit of 762.2 M, as well as many exotic indicators such as Long Term Debt to Equity of 1.57, PPandE Turnover of 14.01 or Receivables Turnover of 4.48. MongoDB financial statements analysis is a perfect complement when working with MongoDB Valuation or Volatility modules. It can also supplement MongoDB's financial leverage analysis and stock options assessment as well as various MongoDB Technical models . Additionally, see the analysis of MongoDB Correlation against competitors.

MongoDB Price to Earnings Ratio Breakdown

Showing smoothed Price to Earnings Ratio of MongoDB with missing and latest data points interpolated. An alternative to [PE] representing the ratio between [Price] and [EPSUSD].MongoDB's Price to Earnings Ratio historical data analysis aims to capture in quantitative terms the overall pattern of either growth or decline in MongoDB's overall financial position and show how it may be relating to other accounts over time.
ViewLast Reported (15.88) X10 Years Trend
Down
Slightly volatile
   Price to Earnings Ratio   
       Timeline  

MongoDB Price to Earnings Ratio Regression Statistics

Arithmetic Mean(34.90)
Geometric Mean19.70
Coefficient Of Variation(97.96)
Mean Deviation31.13
Median(7.66)
Standard Deviation34.18
Sample Variance1,169
Range77.63
R-Value(0.89)
Mean Square Error269.34
R-Squared0.79
Significance0.00002314
Slope(7.25)
Total Sum of Squares15,192

MongoDB Price to Earnings Ratio History

2018 -48.61
2019 -52.2
2020 -81.59
2021 -85.29
2022 -76.76
2023 -82.82

About MongoDB Financial Statements

There are typically three primary documents that fall into the category of financial statements. These documents include MongoDB income statement, its balance sheet, and the statement of cash flows. MongoDB investors use historical funamental indicators, such as MongoDB's Price to Earnings Ratio, to determine how well the company is positioned to perform in the future. Although MongoDB investors may use each financial statement separately, they are all related. The changes in MongoDB's assets and liabilities, for example, are also reflected in the revenues and expenses that we see on MongoDB's income statement, which results in the company's gains or losses. Cash flows can provide more information regarding cash listed on a balance sheet, but not equivalent to net income shown on the income statement. We offer a historical overview of the basic patterns found on MongoDB Financial Statements. Understanding these patterns can help to make the right decision on long term investment in MongoDB. Please read more on our technical analysis and fundamental analysis pages.
Last ReportedProjected for 2023
Price to Earnings Ratio(76.76) (82.82) 
Earnings Before Interest Taxes and Depreciation Amortization EBITDA-331.2 M-339.9 M
Earnings before Tax-272.6 M-279.8 M

MongoDB Investors Sentiment

The influence of MongoDB's investor sentiment on the probability of its price appreciation or decline could be a good factor in your decision-making process regarding taking a position in MongoDB. The overall investor sentiment generally increases the direction of a stock movement in a one-year investment horizon. However, the impact of investor sentiment on the entire stock markets does not have a solid backing from leading economists and market statisticians.
Investor biases related to MongoDB's public news can be used to forecast risks associated with investment in MongoDB. The trend in average sentiment can be used to explain how an investor holding MongoDB can time the market purely based on public headlines and social activities around MongoDB. Please note that most equiteis that are difficult to arbitrage are affected by market sentiment the most.
MongoDB's market sentiment shows the aggregated news analyzed to detect positive and negative mentions from the text and comments. The data is normalized to provide daily scores for MongoDB's and other traded tickers. The bigger the bubble, the more accurate is the estimated score. Higher bars for a given day show more participation in the average MongoDB's news discussions. The higher the estimated score, the more favorable is the investor's outlook on MongoDB.

MongoDB Implied Volatility

    
  73.2  
MongoDB's implied volatility exposes the market's sentiment of MongoDB stock's possible movements over time. However, it does not forecast the overall direction of its price. In a nutshell, if MongoDB's implied volatility is high, the market thinks the stock has potential for high price swings in either direction. On the other hand, the low implied volatility suggests that MongoDB stock will not fluctuate a lot when MongoDB's options are near their expiration.
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards MongoDB in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, MongoDB's short interest history, or implied volatility extrapolated from MongoDB options trading.

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Additionally, see the analysis of MongoDB Correlation against competitors. 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.

Complementary Tools for MongoDB Stock analysis

When running MongoDB 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 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.
Market Capitalization
15.5 B
Quarterly Revenue Growth
0.47
Return On Assets
(0.09) 
Return On Equity
(0.54) 
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 MongoDB value 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.