G-bits Network Stock Forecast - Naive Prediction
| 603444 Stock | 207.23 0.74 0.36% |
The Naive Prediction forecasted value of G bits Network Technology on the next trading day is expected to be 200.29 with a mean absolute deviation of 8.01 and the sum of the absolute errors of 488.57. G-bits Stock Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast G-bits Network stock prices and determine the direction of G bits Network Technology's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of G-bits Network's historical fundamentals, such as revenue growth or operating cash flow patterns.
G-bits |
G-bits Network Naive Prediction Price Forecast For the 2nd of December
Given 90 days horizon, the Naive Prediction forecasted value of G bits Network Technology on the next trading day is expected to be 200.29 with a mean absolute deviation of 8.01, mean absolute percentage error of 102.54, and the sum of the absolute errors of 488.57.Please note that although there have been many attempts to predict G-bits 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 G-bits Network's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
G-bits Network Stock Forecast Pattern
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G-bits Network Forecasted Value
In the context of forecasting G-bits Network'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. G-bits Network's downside and upside margins for the forecasting period are 196.77 and 203.80, respectively. We have considered G-bits Network'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 Naive Prediction forecasting method's relative quality and the estimations of the prediction error of G-bits Network stock data series using in forecasting. Note that when a statistical model is used to represent G-bits Network 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 | 122.7407 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 8.0093 |
| MAPE | Mean absolute percentage error | 0.0376 |
| SAE | Sum of the absolute errors | 488.5674 |
Predictive Modules for G-bits Network
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as G bits Network. 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 G-bits Network
For every potential investor in G-bits, whether a beginner or expert, G-bits Network's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. G-bits Stock price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in G-bits. Basic forecasting techniques help filter out the noise by identifying G-bits Network's price trends.G-bits Network 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 G-bits Network stock to make a market-neutral strategy. Peer analysis of G-bits Network could also be used in its relative valuation, which is a method of valuing G-bits Network by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
G bits Network 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 G-bits Network'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 G-bits Network's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
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| Volume Indicators |
G-bits Network Market Strength Events
Market strength indicators help investors to evaluate how G-bits Network stock reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading G-bits Network shares will generate the highest return on investment. By undertsting and applying G-bits Network stock market strength indicators, traders can identify G bits Network Technology entry and exit signals to maximize returns.
G-bits Network Risk Indicators
The analysis of G-bits Network'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 G-bits Network's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting g-bits 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 | 2.68 | |||
| Semi Deviation | 3.13 | |||
| Standard Deviation | 3.46 | |||
| Variance | 11.97 | |||
| Downside Variance | 10.39 | |||
| Semi Variance | 9.8 | |||
| Expected Short fall | (3.04) |
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.
Currently Active Assets on Macroaxis
Other Information on Investing in G-bits Stock
G-bits Network financial ratios help investors to determine whether G-bits 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 G-bits with respect to the benefits of owning G-bits Network security.