Meta Platforms Stock Forecast - Simple Exponential Smoothing

FB
 Stock
  

USD 160.03  1.22  0.76%   

Meta Platforms Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Meta Platforms historical stock prices and determine the direction of Meta Platforms Old's future trends based on various well-known forecasting models. However, solely looking at the historical price movement is usually misleading. Macroaxis recommends to always use this module together with analysis of Meta Platforms historical fundamentals such as revenue growth or operating cash flow patterns.
Please check Historical Fundamental Analysis of Meta Platforms to cross-verify your projections.
  
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Most investors in Meta Platforms cannot accurately predict what will happen the next trading day because, historically, stock markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Meta Platforms' time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Meta Platforms' price structures and extracts relationships that further increase the generated results' accuracy.
Meta Platforms 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 Meta Platforms Old are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Meta Platforms Old prices get older.

Meta Platforms Simple Exponential Smoothing Price Forecast For the 5th of July

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Meta Platforms Old on the next trading day is expected to be 160.03 with a mean absolute deviation of 5.75, mean absolute percentage error of 61.78, and the sum of the absolute errors of 344.93. Please note that although there have been many attempts to predict Meta Platforms 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 Meta Platforms' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Meta Platforms Stock Forecast Pattern

Backtest Meta PlatformsMeta Platforms Price PredictionBuy or Sell Advice 

Meta Platforms Forecasted Value

In the context of forecasting Meta Platforms' 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. Meta Platforms' downside and upside margins for the forecasting period are 155.89 and 164.17, respectively. We have considered Meta Platforms' 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 160.03
155.89
Downside
160.03
Expected Value
164.17
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 Meta Platforms stock data series using in forecasting. Note that when a statistical model is used to represent Meta Platforms 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 Criteria120.3962
BiasArithmetic mean of the errors 1.0545
MADMean absolute deviation5.7488
MAPEMean absolute percentage error0.0304
SAESum of the absolute errors344.93
This simple exponential smoothing model begins by setting Meta Platforms Old forecast for the second period equal to the observation of the first period. In other words, recent Meta Platforms observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Meta Platforms

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Meta Platforms Old. Regardless of method or technology, however, to accurately forecast the stock or bond 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, frequently view the market will even out over time. This tendency of Meta Platforms' 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. Please use the tools below to analyze the current value of Meta Platforms in the context of predictive analytics.
Hype
Prediction
LowEstimated ValueHigh
155.16159.30163.44
Details
Intrinsic
Valuation
LowReal ValueHigh
144.03212.54216.68
Details
Bollinger
Band Projection (param)
LowerMiddle BandUpper
150.79184.99219.18
Details
28 Analysts
Consensus
LowTarget PriceHigh
300.00390.86460.00
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Meta Platforms. Your research has to be compared to or analyzed against Meta Platforms' peers to derive any actionable benefits. When done correctly, Meta Platforms' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy towards taking a position in Meta Platforms Old.

Other Forecasting Options for Meta Platforms

For every potential investor in Meta Platforms, whether a beginner or expert, Meta Platforms' price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Meta Platforms Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Meta Platforms. Basic forecasting techniques help filter out the noise by identifying Meta Platforms' price trends.

View Currently 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 Meta Platforms stock to make a market-neutral strategy. Peer analysis of Meta Platforms could also be used in its relative valuation, which is a method of valuing Meta Platforms by comparing valuation metrics with similar companies.

Meta Platforms Old 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 Meta Platforms' 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 Meta Platforms' current price.

Meta Platforms Market Strength Events

Market strength indicators help investors to evaluate how Meta Platforms stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Meta Platforms shares will generate the highest return on investment. By undertsting and applying Meta Platforms stock market strength indicators, traders can identify Meta Platforms Old entry and exit signals to maximize returns.

Meta Platforms Risk Indicators

The analysis of Meta Platforms' basic risk indicators is one of the essential steps in helping accuretelly forecast its future price. The process involves identifying the amount of risk involved in Meta Platforms' investment and either accepting that risk or mitigating it. Along with some funamental techniques of forecasting Meta Platforms stock price, 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 stock investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Meta Platforms Investors Sentiment

The influence of Meta Platforms' 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 Meta Platforms. 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.
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 Meta Platforms 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, Meta Platforms' short interest history, or implied volatility extrapolated from Meta Platforms options trading.

Current Sentiment - FB

Meta Platforms Old Investor Sentiment

Nearly all of Macroaxis users are currently bullish on Meta Platforms Old. What is your trading attitude regarding investing in Meta Platforms Old? Are you bullish or bearish?
Bullish
Bearish
98% Bullish
2% Bearish

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Please check Historical Fundamental Analysis of Meta Platforms to cross-verify your projections. Note that the Meta Platforms Old information on this page should be used as a complementary analysis to other Meta Platforms' 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.

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When running Meta Platforms Old price analysis, check to measure Meta Platforms' 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 Meta Platforms is operating at the current time. Most of Meta Platforms' value examination focuses on studying past and present price action to predict the probability of Meta Platforms' future price movements. You can analyze the entity against its peers and financial market as a whole to determine factors that move Meta Platforms' price. Additionally, you may evaluate how the addition of Meta Platforms to your portfolios can decrease your overall portfolio volatility.
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Is Meta Platforms' 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 Meta Platforms. If investors know Meta Platforms 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 Meta Platforms 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 Meta Platforms Old is measured differently than its book value, which is the value of Meta Platforms that is recorded on the company's balance sheet. Investors also form their own opinion of Meta Platforms' value that differs from its market value or its book value, called intrinsic value, which is Meta Platforms' 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 Meta Platforms' market value can be influenced by many factors that don't directly affect Meta Platforms' 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 Meta Platforms' value and its price as these two are different measures arrived at by different means. Investors typically determine Meta Platforms value by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Meta Platforms' 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.