ETFS Commodity OTC Etf Forecast - Polynomial Regression
| ECYAF Etf | USD 6.37 0.00 0.00% |
The Polynomial Regression forecasted value of ETFS Commodity Securities on the next trading day is expected to be 6.51 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.71. ETFS OTC Etf Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast ETFS Commodity stock prices and determine the direction of ETFS Commodity Securities's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of ETFS Commodity's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out fundamental analysis of ETFS Commodity to check your projections. ETFS |
Most investors in ETFS Commodity cannot accurately predict what will happen the next trading day because, historically, etf markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the ETFS Commodity's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets ETFS Commodity's price structures and extracts relationships that further increase the generated results' accuracy.
ETFS Commodity polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for ETFS Commodity Securities as well as the accuracy indicators are determined from the period prices. ETFS Commodity Polynomial Regression Price Forecast For the 3rd of June
Given 90 days horizon, the Polynomial Regression forecasted value of ETFS Commodity Securities on the next trading day is expected to be 6.51 with a mean absolute deviation of 0.04, mean absolute percentage error of 0, and the sum of the absolute errors of 2.71.Please note that although there have been many attempts to predict ETFS OTC 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 ETFS Commodity's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
ETFS Commodity OTC Etf Forecast Pattern
ETFS Commodity Forecasted Value
In the context of forecasting ETFS Commodity's OTC 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. ETFS Commodity's downside and upside margins for the forecasting period are 5.88 and 7.13, respectively. We have considered ETFS Commodity'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 Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of ETFS Commodity otc etf data series using in forecasting. Note that when a statistical model is used to represent ETFS Commodity otc 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 | 112.3874 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0445 |
| MAPE | Mean absolute percentage error | 0.0071 |
| SAE | Sum of the absolute errors | 2.7115 |
Predictive Modules for ETFS Commodity
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as ETFS Commodity Securities. Regardless of method or technology, however, to accurately forecast the otc etf market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the otc 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 ETFS Commodity'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 ETFS Commodity
For every potential investor in ETFS, whether a beginner or expert, ETFS Commodity's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. ETFS OTC Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in ETFS. Basic forecasting techniques help filter out the noise by identifying ETFS Commodity's price trends.ETFS Commodity 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 ETFS Commodity otc etf to make a market-neutral strategy. Peer analysis of ETFS Commodity could also be used in its relative valuation, which is a method of valuing ETFS Commodity by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
ETFS Commodity Securities Technical and Predictive Analytics
The otc etf market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of ETFS Commodity'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 ETFS Commodity's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
ETFS Commodity Market Strength Events
Market strength indicators help investors to evaluate how ETFS Commodity otc etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading ETFS Commodity shares will generate the highest return on investment. By undertsting and applying ETFS Commodity otc etf market strength indicators, traders can identify ETFS Commodity Securities entry and exit signals to maximize returns.
ETFS Commodity Risk Indicators
The analysis of ETFS Commodity'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 ETFS Commodity's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting etfs otc 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 | 0.1271 | |||
| Standard Deviation | 0.6185 | |||
| Variance | 0.3825 |
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
Check out fundamental analysis of ETFS Commodity to check your projections. Note that the ETFS Commodity Securities information on this page should be used as a complementary analysis to other ETFS Commodity's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Options Analysis module to analyze and evaluate options and option chains as a potential hedge for your portfolios.
Please note, there is a significant difference between ETFS Commodity's value and its price as these two are different measures arrived at by different means. Investors typically determine if ETFS Commodity is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, ETFS Commodity'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.