MongoDB Stock Forecast - Simple Exponential Smoothing

MDB Stock  USD 332.50  17.06  5.41%   
The Simple Exponential Smoothing forecasted value of MongoDB on the next trading day is expected to be 332.50 with a mean absolute deviation of 5.96 and the sum of the absolute errors of 357.69. 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.
  
MongoDB simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for MongoDB are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as MongoDB prices get older.

MongoDB Simple Exponential Smoothing Price Forecast For the 26th of November

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of MongoDB on the next trading day is expected to be 332.50 with a mean absolute deviation of 5.96, mean absolute percentage error of 66.58, and the sum of the absolute errors of 357.69.
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 328.84 and 336.16, 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
332.50
328.84
Downside
332.50
Expected Value
336.16
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing 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 Criteria120.471
BiasArithmetic mean of the errors -0.6952
MADMean absolute deviation5.9615
MAPEMean absolute percentage error0.021
SAESum of the absolute errors357.69
This simple exponential smoothing model begins by setting MongoDB forecast for the second period equal to the observation of the first period. In other words, recent MongoDB observations are given relatively more weight in forecasting than the older observations.

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
329.61333.27336.93
Details
Intrinsic
Valuation
LowRealHigh
299.25388.31391.97
Details
Bollinger
Band Projection (param)
LowMiddleHigh
310.73326.81342.90
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 Content Syndication module to quickly integrate customizable finance content to your own investment portal.
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.
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.