MongoDB Stock Forecast - Simple Moving Average

MDB Stock  USD 399.65  20.04  4.77%   
The Simple Moving Average forecasted value of MongoDB on the next trading day is expected to be 399.65 with a mean absolute deviation of 8.68 and the sum of the absolute errors of 512.14. MongoDB Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast MongoDB stock prices and determine the direction of MongoDB's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of MongoDB's historical fundamentals, such as revenue growth or operating cash flow patterns.
At the present time the relative strength indicator of MongoDB's share price is below 20 . This indicates that the stock is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards.

Momentum 0

 Sell Peaked

 
Oversold
 
Overbought
The successful prediction of MongoDB's future price could yield a significant profit. We analyze noise-free headlines and recent hype associated with MongoDB, which may create opportunities for some arbitrage if properly timed. Below are the key fundamental drivers impacting MongoDB's stock price prediction:
EPS Estimate Current Year
4.8001
EPS Estimate Next Year
5.5512
Wall Street Target Price
441.9884
EPS Estimate Current Quarter
0.7941
Quarterly Revenue Growth
0.187
Using MongoDB hype-based prediction, you can estimate the value of MongoDB from the perspective of MongoDB response to recently generated media hype and the effects of current headlines on its competitors. We also analyze overall investor sentiment towards MongoDB using MongoDB's stock options and short interest. It helps to benchmark the overall future attitude of investors towards MongoDB using crowd psychology based on the activity and movement of MongoDB's stock price.

MongoDB Short Interest

A significant increase or decrease in MongoDB's short interest from the previous month could be a good indicator of investor sentiment towards MongoDB. Short interest can provide insight into the potential direction of MongoDB stock and how bullish or bearish investors feel about the market overall.
200 Day MA
265.4552
Short Percent
0.0461
Short Ratio
1.62
Shares Short Prior Month
3.5 M
50 Day MA
375.8404

MongoDB Hype to Price Pattern

Investor biases related to MongoDB's public news can be used to forecast risks associated with an 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 equities that are difficult to arbitrage are affected by market sentiment the most.
Some investors profit by finding stocks that are overvalued or undervalued based on market sentiment. The correlation of MongoDB's market sentiment to its price can help taders to make decisions based on the overall investors consensus about MongoDB.

MongoDB Implied Volatility

    
  0.75  
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.
The Simple Moving Average forecasted value of MongoDB on the next trading day is expected to be 399.65 with a mean absolute deviation of 8.68 and the sum of the absolute errors of 512.14.

MongoDB after-hype prediction price

    
  USD 398.9  
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as stock price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
Check out Historical Fundamental Analysis of MongoDB to cross-verify your projections.
For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.The current year's Fixed Asset Turnover is expected to grow to 23.41, whereas Payables Turnover is forecasted to decline to 27.18. . As of January 4, 2026, Common Stock Shares Outstanding is expected to decline to about 60.2 M. The current year's Net Loss is expected to grow to about (295.3 M).

Open Interest Against 2026-03-20 MongoDB Option Contracts

Although open interest is a measure utilized in the options markets, it could be used to forecast MongoDB's spot prices because the number of available contracts in the market changes daily, and new contracts can be created or liquidated at will. Since open interest in MongoDB's options reflects these daily shifts, investors could use the patterns of these changes to develop long and short-term trading strategies for MongoDB stock based on available contracts left at the end of a trading day.
Please note that to derive more accurate forecasting about market movement from the current MongoDB's open interest, investors have to compare it to MongoDB's spot prices. As Ford's stock price increases, high open interest indicates that money is entering the market, and the market is strongly bullish. Conversely, if the price of MongoDB is decreasing and there is high open interest, that is a sign that the bearish trend will continue, and investors may react by taking short positions in MongoDB. So, decreasing or low open interest during a bull market indicates that investors are becoming uncertain of the depth of the bullish trend, and a reversal in sentiment will likely follow.

MongoDB Additional Predictive Modules

Most predictive techniques to examine MongoDB price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for MongoDB using various technical 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.
A two period moving average forecast for MongoDB is based on an daily price series in which the stock price on a given day is replaced by the mean of that price and the preceding price. This model is best suited to price patterns experiencing average volatility.

MongoDB Simple Moving Average Price Forecast For the 5th of January

Given 90 days horizon, the Simple Moving Average forecasted value of MongoDB on the next trading day is expected to be 399.65 with a mean absolute deviation of 8.68, mean absolute percentage error of 186.16, and the sum of the absolute errors of 512.14.
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

Backtest MongoDBMongoDB Price PredictionBuy or Sell Advice 

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 396.16 and 403.14, 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.
Market Value
399.65
396.16
Downside
399.65
Expected Value
403.14
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Moving Average 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.
AICAkaike Information Criteria119.6613
BiasArithmetic mean of the errors -1.773
MADMean absolute deviation8.6803
MAPEMean absolute percentage error0.0231
SAESum of the absolute errors512.135
The simple moving average model is conceptually a linear regression of the current value of MongoDB price series against current and previous (unobserved) value of MongoDB. In time series analysis, the simple moving-average model is a very common approach for modeling univariate price series models including forecasting prices into the future

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.
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
395.41398.90402.39
Details
Intrinsic
Valuation
LowRealHigh
359.69449.92453.41
Details
Bollinger
Band Projection (param)
LowMiddleHigh
318.41397.71477.00
Details
40 Analysts
Consensus
LowTargetHigh
402.21441.99490.61
Details

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.

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.

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.
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.

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 Historical Fundamental Analysis of MongoDB to cross-verify your projections.
For information on how to trade MongoDB Stock refer to our How to Trade MongoDB Stock guide.
You can also try the Latest Portfolios module to quick portfolio dashboard that showcases your latest portfolios.
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. 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
(0.84)
Revenue Per Share
28.826
Quarterly Revenue Growth
0.187
Return On Assets
(0.03)
Return On Equity
(0.03)
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.