MongoDB Stock Forward View - Double Exponential Smoothing
| MDB Stock | USD 253.67 -19.58 -7.17% |
MongoDB's Double Exponential Smoothing reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use. The model is fitted to available historical daily prices for MongoDB. This page is updated as new daily closing prices become available for MongoDB.
The Double Exponential Smoothing forecasted value of MongoDB on the next trading day is expected to be 254.01 with a mean absolute deviation of 11.72 and the sum of the absolute errors of 691.72.When MongoDB prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any MongoDB trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent MongoDB observations are given relatively more weight in forecasting than the older observations. All Double Exponential Smoothing forecast figures shown for MongoDB are reference data reflecting model output based on available historical prices. Double Exponential Smoothing Price Forecast For the 25th of March
Given 90 days horizon, the Double Exponential Smoothing forecasted value of MongoDB on the next trading day is expected to be 254.01 with a mean absolute deviation of 11.72 , mean absolute percentage error of 278.60 , and the sum of the absolute errors of 691.72 .Please note that although there have been many attempts to predict MongoDB Stock prices using its time series forecasting, we generally do not suggest 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).
Stock Forecast Pattern
| Backtest MongoDB | MongoDB Price Prediction | Research Analysis |
Forecasted Value
This next-day forecast for MongoDB uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Double 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.| AIC | Akaike Information Criteria | Huge |
| Bias | Arithmetic mean of the errors | 3.4278 |
| MAD | Mean absolute deviation | 11.7241 |
| MAPE | Mean absolute percentage error | 0.0351 |
| SAE | Sum of the absolute errors | 691.72 |
Other Forecasting Options for MongoDB
Bollinger Bands applied to MongoDB Stock price data measure how far MongoDB has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to MongoDB's price data. On-balance volume for MongoDB Stock creates a running indicator of buying versus selling pressure in MongoDB. Price departures from the channel boundary often mean-revert, offering tactical signals for MongoDB's.MongoDB Related Equities
The peer firms below within the Information Technology space can help frame MongoDB's pricing and running costs in context. Checking cash flow across this peer set helps gauge MongoDB's relative financial strength.
| Risk & Return | Correlation |
MongoDB Market Strength Events
For investors tracking MongoDB, market strength indicators offer quantitative evaluation of stock behavior. These indicators add context to timing decisions around MongoDB positions. These indicators capture shifts in momentum that may precede significant price moves in MongoDB. These metrics provide actionable context for both entry and risk management decisions around MongoDB.
| Accumulation Distribution | 88627.6 | |||
| Daily Balance Of Power | -1.12 | |||
| Rate Of Daily Change | 0.93 | |||
| Day Median Price | 262.22 | |||
| Day Typical Price | 259.37 | |||
| Price Action Indicator | -18.34 | |||
| Period Momentum Indicator | -19.58 | |||
| Relative Strength Index | 35.99 |
MongoDB Risk Indicators
Analyzing MongoDB's basic risk indicators provides investors with a structured view of the risk-return trade-off for mongodb stock. By identifying the level of risk embedded in MongoDB's investment, investors can make informed decisions about position sizing. Analyzing MongoDB's risk indicators gives investors important context for price forecasting. Understanding the risk in MongoDB's investment allows investors to make informed choices about mitigating exposure.
| Mean Deviation | 3.03 | |||
| Standard Deviation | 4.49 | |||
| Variance | 20.14 |
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.
Story Coverage note for MongoDB
Story coverage around MongoDB often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.
Contributor Headline
Latest Perspective From Macroaxis
MongoDB Short Properties
A short-interest review of MongoDB provides context for understanding whether skepticism in the market is becoming more influential. A disciplined short-interest review can make timing decisions more informed under rising skepticism.
| Common Stock Shares Outstanding | 81.2 M | |
| Cash And Short Term Investments | 2.4 B |