USCF ETF Etf Forecast - Simple Regression
| UDI Etf | USD 31.32 0.06 0.19% |
The Simple Regression forecasted value of USCF ETF Trust on the next trading day is expected to be 31.06 with a mean absolute deviation of 0.26 and the sum of the absolute errors of 16.37. USCF Etf Forecast is based on your current time horizon. We recommend always using this module together with an analysis of USCF ETF's historical fundamentals, such as revenue growth or operating cash flow patterns.
USCF |
USCF ETF Simple Regression Price Forecast For the 29th of November
Given 90 days horizon, the Simple Regression forecasted value of USCF ETF Trust on the next trading day is expected to be 31.06 with a mean absolute deviation of 0.26, mean absolute percentage error of 0.1, and the sum of the absolute errors of 16.37.Please note that although there have been many attempts to predict USCF Etf 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 USCF ETF's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
USCF ETF Etf Forecast Pattern
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USCF ETF Forecasted Value
In the context of forecasting USCF ETF's Etf 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. USCF ETF's downside and upside margins for the forecasting period are 30.27 and 31.86, respectively. We have considered USCF ETF'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 Simple Regression forecasting method's relative quality and the estimations of the prediction error of USCF ETF etf data series using in forecasting. Note that when a statistical model is used to represent USCF ETF etf, 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 | 117.6203 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.264 |
| MAPE | Mean absolute percentage error | 0.0088 |
| SAE | Sum of the absolute errors | 16.3687 |
Predictive Modules for USCF ETF
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as USCF ETF Trust. Regardless of method or technology, however, to accurately forecast the etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the etf 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 USCF ETF'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.
Other Forecasting Options for USCF ETF
For every potential investor in USCF, whether a beginner or expert, USCF ETF's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. USCF Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in USCF. Basic forecasting techniques help filter out the noise by identifying USCF ETF's price trends.USCF ETF 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 USCF ETF etf to make a market-neutral strategy. Peer analysis of USCF ETF could also be used in its relative valuation, which is a method of valuing USCF ETF by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
USCF ETF Trust Technical and Predictive Analytics
The etf market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of USCF ETF'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 USCF ETF's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
USCF ETF Market Strength Events
Market strength indicators help investors to evaluate how USCF ETF etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading USCF ETF shares will generate the highest return on investment. By undertsting and applying USCF ETF etf market strength indicators, traders can identify USCF ETF Trust entry and exit signals to maximize returns.
USCF ETF Risk Indicators
The analysis of USCF ETF'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 USCF ETF's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting uscf etf 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 | 0.5604 | |||
| Semi Deviation | 0.4351 | |||
| Standard Deviation | 0.781 | |||
| Variance | 0.6099 | |||
| Downside Variance | 0.3857 | |||
| Semi Variance | 0.1893 | |||
| Expected Short fall | (0.65) |
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
When determining whether USCF ETF Trust offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of USCF ETF'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 Uscf Etf Trust Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Uscf Etf Trust Etf:Check out Historical Fundamental Analysis of USCF ETF to cross-verify your projections. You can also try the Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
The market value of USCF ETF Trust is measured differently than its book value, which is the value of USCF that is recorded on the company's balance sheet. Investors also form their own opinion of USCF ETF's value that differs from its market value or its book value, called intrinsic value, which is USCF ETF's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because USCF ETF's market value can be influenced by many factors that don't directly affect USCF ETF's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between USCF ETF's value and its price as these two are different measures arrived at by different means. Investors typically determine if USCF ETF is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, USCF ETF's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.