Meta Platforms, (Argentina) Market Value

META Stock   29,500  450.00  1.50%   
Meta Platforms,'s market value is the price at which a share of Meta Platforms, trades on a public exchange. It measures the collective expectations of Meta Platforms, investors about its performance. Meta Platforms, is trading at 29500.00 as of the 29th of December 2024, a 1.5% down since the beginning of the trading day. The stock's open price was 29950.0.
With this module, you can estimate the performance of a buy and hold strategy of Meta Platforms, and determine expected loss or profit from investing in Meta Platforms, over a given investment horizon. Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in board of governors.
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Meta Platforms, 'What if' Analysis

In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Meta Platforms,'s stock what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Meta Platforms,.
0.00
07/02/2024
No Change 0.00  0.0 
In 5 months and 30 days
12/29/2024
0.00
If you would invest  0.00  in Meta Platforms, on July 2, 2024 and sell it all today you would earn a total of 0.00 from holding Meta Platforms, or generate 0.0% return on investment in Meta Platforms, over 180 days.

Meta Platforms, Upside/Downside Indicators

Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Meta Platforms,'s stock current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Meta Platforms, upside and downside potential and time the market with a certain degree of confidence.

Meta Platforms, Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Meta Platforms,'s investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Meta Platforms,'s standard deviation. In reality, there are many statistical measures that can use Meta Platforms, historical prices to predict the future Meta Platforms,'s volatility.

Meta Platforms, Backtested Returns

At this point, Meta Platforms, is very steady. Meta Platforms, has Sharpe Ratio of 0.0065, which conveys that the firm had a 0.0065% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Meta Platforms,, which you can use to evaluate the volatility of the firm. Please verify Meta Platforms,'s Mean Deviation of 1.37, risk adjusted performance of 0.0324, and Downside Deviation of 1.91 to check out if the risk estimate we provide is consistent with the expected return of 0.0116%. The company secures a Beta (Market Risk) of -0.17, which conveys not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Meta Platforms, are expected to decrease at a much lower rate. During the bear market, Meta Platforms, is likely to outperform the market. Meta Platforms, right now secures a risk of 1.78%. Please verify Meta Platforms, maximum drawdown, potential upside, and the relationship between the treynor ratio and value at risk , to decide if Meta Platforms, will be following its current price movements.

Auto-correlation

    
  0.31  

Below average predictability

Meta Platforms, has below average predictability. Overlapping area represents the amount of predictability between Meta Platforms, time series from 2nd of July 2024 to 30th of September 2024 and 30th of September 2024 to 29th of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Meta Platforms, price movement. The serial correlation of 0.31 indicates that nearly 31.0% of current Meta Platforms, price fluctuation can be explain by its past prices.
Correlation Coefficient0.31
Spearman Rank Test0.04
Residual Average0.0
Price Variance1.4 M

Meta Platforms, lagged returns against current returns

Autocorrelation, which is Meta Platforms, stock's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Meta Platforms,'s stock expected returns. We can calculate the autocorrelation of Meta Platforms, returns to help us make a trade decision. For example, suppose you find that Meta Platforms, has exhibited high autocorrelation historically, and you observe that the stock is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
   Current and Lagged Values   
       Timeline  

Meta Platforms, regressed lagged prices vs. current prices

Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Meta Platforms, stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Meta Platforms, stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Meta Platforms, stock over time.
   Current vs Lagged Prices   
       Timeline  

Meta Platforms, Lagged Returns

When evaluating Meta Platforms,'s market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Meta Platforms, stock have on its future price. Meta Platforms, autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Meta Platforms, autocorrelation shows the relationship between Meta Platforms, stock current value and its past values and can show if there is a momentum factor associated with investing in Meta Platforms,.
   Regressed Prices   
       Timeline  

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