30 Day Commodity Forward View
| ZQUSD Commodity | 96.39 0.01 0.01% |
Momentum 0
Sell Peaked
Oversold | Overbought |
Using 30 Day hype-based prediction, you can estimate the value of 30 Day Fed from the perspective of 30 Day response to recently generated media hype and the effects of current headlines on its competitors.
The Naive Prediction forecasted value of 30 Day Fed on the next trading day is expected to be 96.39 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.14. 30 Day after-hype prediction price | USD 96.39 |
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as commodity price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
ZQUSD |
30 Day Additional Predictive Modules
Most predictive techniques to examine ZQUSD price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for ZQUSD using various technical indicators. When you analyze ZQUSD 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.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
30 Day Naive Prediction Price Forecast For the 16th of February 2026
Given 90 days horizon, the Naive Prediction forecasted value of 30 Day Fed on the next trading day is expected to be 96.39 with a mean absolute deviation of 0.02, mean absolute percentage error of 0, and the sum of the absolute errors of 1.14.Please note that although there have been many attempts to predict ZQUSD Commodity prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that 30 Day's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
30 Day Commodity Forecast Pattern
30 Day Forecasted Value
In the context of forecasting 30 Day's Commodity 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. 30 Day's downside and upside margins for the forecasting period are 96.33 and 96.45, respectively. We have considered 30 Day'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 30 Day commodity data series using in forecasting. Note that when a statistical model is used to represent 30 Day commodity, 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 | 111.6458 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0187 |
| MAPE | Mean absolute percentage error | 2.0E-4 |
| SAE | Sum of the absolute errors | 1.1417 |
Predictive Modules for 30 Day
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as 30 Day Fed. Regardless of method or technology, however, to accurately forecast the commodity market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the commodity 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 30 Day's 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.
30 Day Estimiated After-Hype Price Volatility
As far as predicting the price of 30 Day at your current risk attitude, this probability distribution graph shows the chance that the prediction will fall between or within a specific range. We use this chart to confirm that your returns on investing in 30 Day or, for that matter, your successful expectations of its future price, cannot be replicated consistently. Please note, a large amount of money has been lost over the years by many investors who confused the symmetrical distributions of Commodity prices, such as prices of 30 Day, with the unreliable approximations that try to describe financial returns.
Next price density |
| Expected price to next headline |
30 Day Commodity Price Outlook Analysis
Have you ever been surprised when a price of a Commodity such as 30 Day is soaring high without any particular reason? This is usually happening because many institutional investors are aggressively trading 30 Day backward and forwards among themselves. Have you ever observed a lot of a particular company's price movement is driven by press releases or news about the company that has nothing to do with actual earnings? Usually, hype to individual companies acts as price momentum. If not enough favorable publicity is forthcoming, the Commodity price eventually runs out of speed. So, the rule of thumb here is that as long as this news hype has nothing to do with immediate earnings, you should pay more attention to it. If you see this tendency with 30 Day, there might be something going there, and it might present an excellent short sale opportunity.
| Expected Return | Period Volatility | Hype Elasticity | Related Elasticity | News Density | Related Density | Expected Hype |
0.00 | 0.06 | 0.00 | 0.00 | 0 Events / Month | 0 Events / Month | Any time |
| Latest traded price | Expected after-news price | Potential return on next major news | Average after-hype volatility | |
96.39 | 96.39 | 0.00 |
|
30 Day Hype Timeline
30 Day Fed is at this time traded for 96.39. This commodity is not elastic to its hype. The commodity elasticity to the hype of similar commodities is 0.0. ZQUSD is projected not to react to the next headline, with the price staying at about the same level, and average media hype impact volatility is insignificant. The immediate return on the next news is projected to be very small, whereas the daily expected return is at this time at 0.0%. %. The volatility of related hype on 30 Day is about 0.0%, with the expected price after the next announcement by competition of 96.39. Assuming the 90 days horizon the next projected press release will be any time. Check out Your Current Watchlist to better understand how to build diversified portfolios. Also, note that the market value of any commodity could be closely tied with the direction of predictive economic indicators such as signals in producer price index.30 Day Related Hype Analysis
Having access to credible news sources related to 30 Day's direct competition is more important than ever and may enhance your ability to predict 30 Day's future price movements. Getting to know how 30 Day's peers react to changing market sentiment, related social signals, and mainstream news is a great way to find investing opportunities and time the market. The summary table below summarizes the essential lagging indicators that can help you analyze how 30 Day may potentially react to the hype associated with one of its peers.
Other Forecasting Options for 30 Day
For every potential investor in ZQUSD, whether a beginner or expert, 30 Day's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. ZQUSD Commodity price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in ZQUSD. Basic forecasting techniques help filter out the noise by identifying 30 Day's price trends.View 30 Day Related Equities
| Risk & Return | Correlation |
30 Day Market Strength Events
Market strength indicators help investors to evaluate how 30 Day commodity reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading 30 Day shares will generate the highest return on investment. By undertsting and applying 30 Day commodity market strength indicators, traders can identify 30 Day Fed entry and exit signals to maximize returns.
30 Day Risk Indicators
The analysis of 30 Day'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 30 Day's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting zqusd commodity 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 | 0.0234 | |||
| Standard Deviation | 0.056 | |||
| Variance | 0.0031 | |||
| Downside Variance | 0.0043 | |||
| Semi Variance | (0.0003) | |||
| Expected Short fall | (0.04) |
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.
Story Coverage note for 30 Day
The number of cover stories for 30 Day depends on current market conditions and 30 Day's risk-adjusted performance over time. The coverage that generates the most noise at a given time depends on the prevailing investment theme that 30 Day is classified under. However, while its typical story may have numerous social followers, the rapid visibility can also attract short-sellers, who usually are skeptical about 30 Day's long-term prospects. So, having above-average coverage will typically attract above-average short interest, leading to significant price volatility.
Other Macroaxis Stories
Our audience includes start-ups and big corporations as well as marketing, public relation firms, and advertising agencies, including technology and finance journalists. Our platform and its news and story outlet are popular among finance students, amateur traders, self-guided investors, entrepreneurs, retirees and baby boomers, academic researchers, financial advisers, as well as professional money managers - a very diverse and influential demographic landscape united by one goal - build optimal investment portfolios