Meta Platforms Stock Forecast - Double Exponential Smoothing

META Stock   36.20  0.68  1.91%   
Meta Stock outlook is based on your current time horizon. Investors can use this forecasting interface to forecast Meta Platforms stock prices and determine the direction of Meta Platforms CDR's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Meta Platforms' historical fundamentals, such as revenue growth or operating cash flow patterns.
As of today, The relative strength index (RSI) of Meta Platforms' share price is at 50. This indicates that the stock is in nutural position, most likellhy at or near its resistance level. The main idea of RSI analysis is to track how fast people are buying or selling Meta Platforms, making its price go up or down.

Momentum 50

 Impartial

 
Oversold
 
Overbought
The successful prediction of Meta Platforms' future price could yield a significant profit. Please, note that this module is not intended to be used solely to calculate an intrinsic value of Meta Platforms and does not consider all of the tangible or intangible factors available from Meta Platforms' fundamental data. We analyze noise-free headlines and recent hype associated with Meta Platforms CDR, which may create opportunities for some arbitrage if properly timed. Below are the key fundamental drivers impacting Meta Platforms' stock price prediction:
Quarterly Earnings Growth
0.374
Quarterly Revenue Growth
0.189
Using Meta Platforms hype-based prediction, you can estimate the value of Meta Platforms CDR from the perspective of Meta Platforms response to recently generated media hype and the effects of current headlines on its competitors.
The Double Exponential Smoothing forecasted value of Meta Platforms CDR on the next trading day is expected to be 36.92 with a mean absolute deviation of 0.63 and the sum of the absolute errors of 37.87.

Meta Platforms after-hype prediction price

    
  CAD 36.24  
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 Meta Platforms to cross-verify your projections.
For information on how to trade Meta Stock refer to our How to Trade Meta Stock guide.

Meta Platforms Additional Predictive Modules

Most predictive techniques to examine Meta price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Meta using various technical indicators. When you analyze Meta 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.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Meta Platforms works best with periods where there are trends or seasonality.

Meta Platforms Double Exponential Smoothing Price Forecast For the 28th of January

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Meta Platforms CDR on the next trading day is expected to be 36.92 with a mean absolute deviation of 0.63, mean absolute percentage error of 0.68, and the sum of the absolute errors of 37.87.
Please note that although there have been many attempts to predict Meta 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 Platforms  Meta Platforms Price Prediction  Buy 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 34.71 and 39.13, 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
36.20
36.92
Expected Value
39.13
Upside

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 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 CriteriaHuge
BiasArithmetic mean of the errors -0.1164
MADMean absolute deviation0.6312
MAPEMean absolute percentage error0.0183
SAESum of the absolute errors37.873
When Meta Platforms CDR 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 Meta Platforms CDR 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 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 CDR. 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.
Hype
Prediction
LowEstimatedHigh
34.0336.2438.45
Details
Intrinsic
Valuation
LowRealHigh
34.1036.3138.52
Details
Bollinger
Band Projection (param)
LowMiddleHigh
32.6334.8337.02
Details

Meta Platforms After-Hype Price Density Analysis

As far as predicting the price of Meta Platforms at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in Meta Platforms or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Stock prices, such as prices of Meta Platforms, with the unreliable approximations that try to describe financial returns.
   Next price density   
       Expected price to next headline  

Meta Platforms Estimiated After-Hype Price Volatility

In the context of predicting Meta Platforms' stock value on the day after the next significant headline, we show statistically significant boundaries of downside and upside scenarios based on Meta Platforms' historical news coverage. Meta Platforms' after-hype downside and upside margins for the prediction period are 34.03 and 38.45, respectively. We have considered Meta Platforms' daily market price in relation to the headlines to evaluate this method's predictive performance. Remember, however, there is no scientific proof or empirical evidence that news-based prediction models outperform traditional linear, nonlinear models or artificial intelligence models to provide accurate predictions consistently.
Current Value
36.20
36.24
After-hype Price
38.45
Upside
Meta Platforms is very steady at this time. Analysis and calculation of next after-hype price of Meta Platforms CDR is based on 3 months time horizon.

Meta Platforms Stock Price Outlook Analysis

Have you ever been surprised when a price of a Company such as Meta Platforms is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading Meta Platforms backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Stock price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with Meta Platforms, there might be something going there, and it might present an excellent short sale opportunity.
Expected ReturnPeriod VolatilityHype ElasticityRelated ElasticityNews DensityRelated DensityExpected Hype
  0.17 
2.21
  0.04 
  0.01 
1 Events / Month
2 Events / Month
Very soon
Latest traded priceExpected after-news pricePotential return on next major newsAverage after-hype volatility
36.20
36.24
0.11 
960.87  
Notes

Meta Platforms Hype Timeline

Meta Platforms CDR is now traded for 36.20on NEO Exchange of Canada. The entity has historical hype elasticity of 0.04, and average elasticity to hype of competition of -0.01. Meta is forecasted to increase in value after the next headline, with the price projected to jump to 36.24 or above. The average volatility of media hype impact on the company the price is over 100%. The price growth on the next news is forecasted to be 0.11%, whereas the daily expected return is now at -0.17%. The volatility of related hype on Meta Platforms is about 6548.15%, with the expected price after the next announcement by competition of 36.19. Assuming the 90 days trading horizon the next forecasted press release will be very soon.
Check out Historical Fundamental Analysis of Meta Platforms to cross-verify your projections.
For information on how to trade Meta Stock refer to our How to Trade Meta Stock guide.

Meta Platforms Related Hype Analysis

Having access to credible news sources related to Meta Platforms' direct competition is more important than ever and may enhance your ability to predict Meta Platforms' future price movements. Getting to know how Meta Platforms' peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how Meta Platforms may potentially react to the hype associated with one of its peers.

Other Forecasting Options for Meta Platforms

For every potential investor in Meta, 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 Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Meta. Basic forecasting techniques help filter out the noise by identifying Meta Platforms' price trends.

Meta Platforms 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.
 Risk & Return  Correlation

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 CDR 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 accurately forecasting 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 essential techniques for forecasting meta 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.

Story Coverage note for Meta Platforms

The number of cover stories for Meta Platforms depends on current market conditions and Meta Platforms' risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that Meta Platforms is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about Meta Platforms' long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.

Other Macroaxis Stories

Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios

Other Information on Investing in Meta Stock

Meta Platforms financial ratios help investors to determine whether Meta Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Meta with respect to the benefits of owning Meta Platforms security.