Meta Financial Stock Forecast - Triple Exponential Smoothing
| FM7 Stock | EUR 70.50 1.00 1.40% |
The Triple Exponential Smoothing forecasted value of Meta Financial Group on the next trading day is expected to be 70.41 with a mean absolute deviation of 1.19 and the sum of the absolute errors of 70.24. Meta Stock Forecast is based on your current time horizon. We recommend always using this module together with an analysis of Meta Financial's historical fundamentals, such as revenue growth or operating cash flow patterns.
Meta |
Meta Financial Triple Exponential Smoothing Price Forecast For the 7th of January
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Meta Financial Group on the next trading day is expected to be 70.41 with a mean absolute deviation of 1.19, mean absolute percentage error of 2.87, and the sum of the absolute errors of 70.24.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 Financial's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Meta Financial Stock Forecast Pattern
| Backtest Meta Financial | Meta Financial Price Prediction | Buy or Sell Advice |
Meta Financial Forecasted Value
In the context of forecasting Meta Financial's 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 Financial's downside and upside margins for the forecasting period are 68.02 and 72.79, respectively. We have considered Meta Financial's 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 Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Meta Financial stock data series using in forecasting. Note that when a statistical model is used to represent Meta Financial 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 | Huge |
| Bias | Arithmetic mean of the errors | 0.226 |
| MAD | Mean absolute deviation | 1.1905 |
| MAPE | Mean absolute percentage error | 0.0165 |
| SAE | Sum of the absolute errors | 70.237 |
Predictive Modules for Meta Financial
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 Financial Group. 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.Other Forecasting Options for Meta Financial
For every potential investor in Meta, whether a beginner or expert, Meta Financial's 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 Financial's price trends.Meta Financial 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 Financial stock to make a market-neutral strategy. Peer analysis of Meta Financial could also be used in its relative valuation, which is a method of valuing Meta Financial by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Meta Financial Group 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 Financial's 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 Financial's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Meta Financial Market Strength Events
Market strength indicators help investors to evaluate how Meta Financial 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 Financial shares will generate the highest return on investment. By undertsting and applying Meta Financial stock market strength indicators, traders can identify Meta Financial Group entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 0.99 | |||
| Day Median Price | 70.5 | |||
| Day Typical Price | 70.5 | |||
| Price Action Indicator | (0.50) | |||
| Period Momentum Indicator | (1.00) |
Meta Financial Risk Indicators
The analysis of Meta Financial's 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 Financial's 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.
| Mean Deviation | 1.6 | |||
| Semi Deviation | 1.68 | |||
| Standard Deviation | 2.33 | |||
| Variance | 5.42 | |||
| Downside Variance | 4.77 | |||
| Semi Variance | 2.83 | |||
| Expected Short fall | (1.99) |
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.
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Additional Information and Resources on Investing in Meta Stock
When determining whether Meta Financial Group offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Meta Financial's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Meta Financial Group Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Meta Financial Group Stock:Check out Historical Fundamental Analysis of Meta Financial to cross-verify your projections. You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.