Meta Platforms Stock Momentum Indicators Moving Average Convergence Divergence

FB -  USA Stock  

USD 193.54  2.25  1.18%

Meta Platforms momentum indicators tool provides the execution environment for running the Moving Average Convergence Divergence indicator and other technical functions against Meta Platforms. Meta Platforms value trend is the prevailing direction of the price over some defined period of time. The concept of trend is an important idea in technical analysis, including the analysis of momentum indicators indicators. As with most other technical indicators, the Moving Average Convergence Divergence indicator function is designed to identify and follow existing trends. Momentum indicators of Meta Platforms are pattern recognition functions that provide distinct formation on Meta Platforms potential trading signals or future price movement. Analysts can use these trading signals to identify current and future trends and trend reversals to provide buy and sell recommendations. Please specify Fast Period, Slow Period and Signal Period to execute this model.
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The output start index for this execution was thirty-three with a total number of output elements of twenty-eight. The Moving Average Convergence/Divergence line is a predictive momentum indicator that shows the relationship between Meta Platforms price series and its peer or benchmark.
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Meta Platforms Technical Analysis Modules

Most technical analysis of Meta Platforms help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for Meta Platforms from various momentum indicators to cycle indicators. When you analyze Meta Platforms 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.

About Meta Platforms Predictive Technical Analysis

Predictive technical analysis modules help investors to analyze different prices and returns patterns as well as diagnose historical swings to determine the real value of Meta Platforms. We use our internally-developed statistical techniques to arrive at the intrinsic value of Meta Platforms based on widely used predictive technical indicators. In general, we focus on analyzing Meta Platforms Stock price patterns and their correlations with different microeconomic environment and drivers. We also apply predictive analytics to build Meta Platforms's daily price indicators and compare them against related drivers, such as momentum indicators and various other types of predictive indicators. Using this methodology combined with a more conventional technical analysis and fundamental analysis, we attempt to find the most accurate representation of Meta Platforms's intrinsic value. In addition to deriving basic predictive indicators for Meta Platforms, we also check how macroeconomic factors affect Meta Platforms price patterns. Please read more on our technical analysis page or use our predictive modules below to complement your research.
 2021 2022 (projected)
Long Term Debt to Equity0.0027830.002856
Interest Coverage68.2154.75
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
189.74193.54197.34
Details
Intrinsic
Valuation
LowReal ValueHigh
174.19229.81233.61
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Naive
Forecast
LowNext ValueHigh
173.62177.42181.22
Details
28 Analysts
Consensus
LowTarget PriceHigh
300.00390.86460.00
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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.

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Meta Platforms pair trading

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Meta Platforms position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Meta Platforms will appreciate offsetting losses from the drop in the long position's value.

Meta Platforms Pair Trading

Meta Platforms Pair Trading Analysis

The ability to find closely correlated positions to Meta Platforms could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Meta Platforms when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Meta Platforms - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Meta Platforms to buy it.
The correlation of Meta Platforms is a statistical measure of how it moves in relation to other equities. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Meta Platforms moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Meta Platforms moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Meta Platforms can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
Please check Investing Opportunities. Note that the Meta Platforms 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 Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.

Complementary Tools for Meta Platforms Stock analysis

When running Meta Platforms 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 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.