Meta Materials Stock Forecast - 20 Period Moving Average
| MMATQ Stock | 0.0001 0.00 0.000003% |
The 20 Period Moving Average forecasted value of Meta Materials on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0 and the sum of the absolute errors of 0. Meta Stock Forecast is based on your current time horizon. Although Meta Materials' naive historical forecasting may sometimes provide an important future outlook for the firm, we recommend always cross-verifying it against solid analysis of Meta Materials' systematic risk associated with finding meaningful patterns of Meta Materials fundamentals over time.
At this time, Meta Materials' Inventory Turnover is relatively stable compared to the past year. As of 12/05/2025, Asset Turnover is likely to grow to 0.14, while Payables Turnover is likely to drop 0.16. . As of 12/05/2025, Common Stock Shares Outstanding is likely to drop to about 3.8 M. Meta Materials 20 Period Moving Average Price Forecast For the 6th of December
Given 90 days horizon, the 20 Period Moving Average forecasted value of Meta Materials on the next trading day is expected to be 0.0001 with a mean absolute deviation of 0, mean absolute percentage error of 0, and the sum of the absolute errors of 0.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 Materials' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Meta Materials Stock Forecast Pattern
| Backtest Meta Materials | Meta Materials Price Prediction | Buy or Sell Advice |
Meta Materials Forecasted Value
In the context of forecasting Meta Materials' 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 Materials' downside and upside margins for the forecasting period are 0.0001 and 0.0001, respectively. We have considered Meta Materials' 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.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the 20 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Meta Materials stock data series using in forecasting. Note that when a statistical model is used to represent Meta Materials 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 | 25.2177 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0 |
| MAPE | Mean absolute percentage error | 0.0 |
| SAE | Sum of the absolute errors | 0.0 |
Predictive Modules for Meta Materials
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 Materials. 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.Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Meta Materials' 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.
Other Forecasting Options for Meta Materials
For every potential investor in Meta, whether a beginner or expert, Meta Materials' 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 Materials' price trends.Meta Materials 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 Materials stock to make a market-neutral strategy. Peer analysis of Meta Materials could also be used in its relative valuation, which is a method of valuing Meta Materials by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Meta Materials 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 Materials' 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 Materials' current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Meta Materials Market Strength Events
Market strength indicators help investors to evaluate how Meta Materials 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 Materials shares will generate the highest return on investment. By undertsting and applying Meta Materials stock market strength indicators, traders can identify Meta Materials entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 1.0E-4 | |||
| Day Typical Price | 1.0E-4 |
Pair Trading with Meta Materials
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 Materials 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 Materials will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Meta Materials 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 Materials 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 Materials - 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 Materials to buy it.
The correlation of Meta Materials is a statistical measure of how it moves in relation to other instruments. 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 Materials moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Meta Materials 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 Materials 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.Additional Tools for Meta Stock Analysis
When running Meta Materials' price analysis, check to measure Meta Materials' 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 Materials is operating at the current time. Most of Meta Materials' value examination focuses on studying past and present price action to predict the probability of Meta Materials' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Meta Materials' price. Additionally, you may evaluate how the addition of Meta Materials to your portfolios can decrease your overall portfolio volatility.