Exchange Listed Etf Forecast - Polynomial Regression

SHUS Etf  USD 45.05  0.08  0.18%   
The Polynomial Regression forecasted value of Exchange Listed Funds on the next trading day is expected to be 45.48 with a mean absolute deviation of 0.29 and the sum of the absolute errors of 17.70. Exchange Etf Forecast is based on your current time horizon.
  
Exchange Listed polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Exchange Listed Funds as well as the accuracy indicators are determined from the period prices.

Exchange Listed Polynomial Regression Price Forecast For the 29th of November

Given 90 days horizon, the Polynomial Regression forecasted value of Exchange Listed Funds on the next trading day is expected to be 45.48 with a mean absolute deviation of 0.29, mean absolute percentage error of 0.13, and the sum of the absolute errors of 17.70.
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 Listed's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Exchange Listed Etf Forecast Pattern

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Exchange Listed Forecasted Value

In the context of forecasting Exchange Listed'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 Listed's downside and upside margins for the forecasting period are 44.83 and 46.13, respectively. We have considered Exchange Listed'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.
Market Value
45.05
45.48
Expected Value
46.13
Upside

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 Exchange Listed etf data series using in forecasting. Note that when a statistical model is used to represent Exchange Listed 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.
AICAkaike Information Criteria116.0765
BiasArithmetic mean of the errors None
MADMean absolute deviation0.2901
MAPEMean absolute percentage error0.0067
SAESum of the absolute errors17.6981
A single variable polynomial regression model attempts to put a curve through the Exchange Listed historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm

Predictive Modules for Exchange Listed

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 Listed Funds. 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 Exchange Listed'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.
Hype
Prediction
LowEstimatedHigh
44.3845.0445.70
Details
Intrinsic
Valuation
LowRealHigh
43.9644.6245.28
Details
Bollinger
Band Projection (param)
LowMiddleHigh
43.2144.2745.33
Details

Other Forecasting Options for Exchange Listed

For every potential investor in Exchange, whether a beginner or expert, Exchange Listed'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 Listed's price trends.

Exchange Listed 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 Listed etf to make a market-neutral strategy. Peer analysis of Exchange Listed could also be used in its relative valuation, which is a method of valuing Exchange Listed by comparing valuation metrics with similar companies.
 Risk & Return  Correlation

Exchange Listed Funds 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 Listed'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 Listed's current price.

Exchange Listed Market Strength Events

Market strength indicators help investors to evaluate how Exchange Listed 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 Listed shares will generate the highest return on investment. By undertsting and applying Exchange Listed etf market strength indicators, traders can identify Exchange Listed Funds entry and exit signals to maximize returns.

Exchange Listed Risk Indicators

The analysis of Exchange Listed'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 Listed'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.
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

Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
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When determining whether Exchange Listed Funds offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Exchange Listed'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 Exchange Listed Funds Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Exchange Listed Funds Etf:
Check out Historical Fundamental Analysis of Exchange Listed to cross-verify your projections.
You can also try the Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.
The market value of Exchange Listed Funds 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 Listed's value that differs from its market value or its book value, called intrinsic value, which is Exchange Listed'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 Listed's market value can be influenced by many factors that don't directly affect Exchange Listed'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 Listed's value and its price as these two are different measures arrived at by different means. Investors typically determine if Exchange Listed is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Exchange Listed'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.