Exchange Traded Etf Forecast - Triple Exponential Smoothing
| OFOS Etf | 23.35 0.02 0.09% |
The Triple Exponential Smoothing forecasted value of Exchange Traded Concepts on the next trading day is expected to be 23.24 with a mean absolute deviation of 0.34 and the sum of the absolute errors of 20.28. Exchange Etf Forecast is based on your current time horizon.
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Exchange Traded Triple Exponential Smoothing Price Forecast For the 12th of December 2024
Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Exchange Traded Concepts on the next trading day is expected to be 23.24 with a mean absolute deviation of 0.34, mean absolute percentage error of 0.18, and the sum of the absolute errors of 20.28.Please note that although there have been many attempts to predict Exchange 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 Exchange Traded's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Exchange Traded Etf Forecast Pattern
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Exchange Traded Forecasted Value
In the context of forecasting Exchange Traded'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. Exchange Traded's downside and upside margins for the forecasting period are 21.65 and 24.83, respectively. We have considered Exchange Traded'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 Exchange Traded etf data series using in forecasting. Note that when a statistical model is used to represent Exchange Traded 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 | Huge |
| Bias | Arithmetic mean of the errors | 0.0638 |
| MAD | Mean absolute deviation | 0.3379 |
| MAPE | Mean absolute percentage error | 0.0138 |
| SAE | Sum of the absolute errors | 20.2751 |
Predictive Modules for Exchange Traded
There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Exchange Traded Concepts. 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.Other Forecasting Options for Exchange Traded
For every potential investor in Exchange, whether a beginner or expert, Exchange Traded's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Exchange Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in Exchange. Basic forecasting techniques help filter out the noise by identifying Exchange Traded's price trends.Exchange Traded 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 Exchange Traded etf to make a market-neutral strategy. Peer analysis of Exchange Traded could also be used in its relative valuation, which is a method of valuing Exchange Traded by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Exchange Traded Concepts 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 Exchange Traded'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 Exchange Traded's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Exchange Traded Market Strength Events
Market strength indicators help investors to evaluate how Exchange Traded etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading Exchange Traded shares will generate the highest return on investment. By undertsting and applying Exchange Traded etf market strength indicators, traders can identify Exchange Traded Concepts entry and exit signals to maximize returns.
| Daily Balance Of Power | 9.2 T | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 23.35 | |||
| Day Typical Price | 23.35 | |||
| Price Action Indicator | 0.01 | |||
| Period Momentum Indicator | 0.02 |
Exchange Traded Risk Indicators
The analysis of Exchange Traded'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 Exchange Traded's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting exchange 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 | 1.29 | |||
| Standard Deviation | 1.59 | |||
| Variance | 2.53 |
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.
Thematic Opportunities
Explore Investment Opportunities
Check out Historical Fundamental Analysis of Exchange Traded to cross-verify your projections. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
The market value of Exchange Traded Concepts is measured differently than its book value, which is the value of Exchange that is recorded on the company's balance sheet. Investors also form their own opinion of Exchange Traded's value that differs from its market value or its book value, called intrinsic value, which is Exchange Traded'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 Exchange Traded's market value can be influenced by many factors that don't directly affect Exchange Traded'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 Exchange Traded's value and its price as these two are different measures arrived at by different means. Investors typically determine if Exchange Traded is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Exchange Traded'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.