JPMorgan Ultra Etf Forecast - Polynomial Regression

JMST Etf  USD 50.84  0.02  0.04%   
The Polynomial Regression forecasted value of JPMorgan Ultra Short Municipal on the next trading day is expected to be 50.88 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 0.92. JPMorgan Etf Forecast is based on your current time horizon.
  
JPMorgan Ultra polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for JPMorgan Ultra Short Municipal as well as the accuracy indicators are determined from the period prices.

JPMorgan Ultra Polynomial Regression Price Forecast For the 25th of November

Given 90 days horizon, the Polynomial Regression forecasted value of JPMorgan Ultra Short Municipal on the next trading day is expected to be 50.88 with a mean absolute deviation of 0.02, mean absolute percentage error of 0.0004, and the sum of the absolute errors of 0.92.
Please note that although there have been many attempts to predict JPMorgan 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 JPMorgan Ultra's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

JPMorgan Ultra Etf Forecast Pattern

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JPMorgan Ultra Forecasted Value

In the context of forecasting JPMorgan Ultra'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. JPMorgan Ultra's downside and upside margins for the forecasting period are 50.84 and 50.92, respectively. We have considered JPMorgan Ultra'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
50.84
50.88
Expected Value
50.92
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 JPMorgan Ultra etf data series using in forecasting. Note that when a statistical model is used to represent JPMorgan Ultra 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 Criteria110.2806
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0151
MAPEMean absolute percentage error3.0E-4
SAESum of the absolute errors0.9213
A single variable polynomial regression model attempts to put a curve through the JPMorgan Ultra 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 JPMorgan Ultra

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as JPMorgan Ultra Short. 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 JPMorgan Ultra'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
50.8050.8450.88
Details
Intrinsic
Valuation
LowRealHigh
46.7046.7455.92
Details
Bollinger
Band Projection (param)
LowMiddleHigh
50.8150.8350.85
Details

Other Forecasting Options for JPMorgan Ultra

For every potential investor in JPMorgan, whether a beginner or expert, JPMorgan Ultra's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. JPMorgan Etf price charts are filled with many 'noises.' These noises can hugely alter the decision one can make regarding investing in JPMorgan. Basic forecasting techniques help filter out the noise by identifying JPMorgan Ultra's price trends.

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

JPMorgan Ultra Short 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 JPMorgan Ultra'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 JPMorgan Ultra's current price.

JPMorgan Ultra Market Strength Events

Market strength indicators help investors to evaluate how JPMorgan Ultra etf reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading JPMorgan Ultra shares will generate the highest return on investment. By undertsting and applying JPMorgan Ultra etf market strength indicators, traders can identify JPMorgan Ultra Short Municipal entry and exit signals to maximize returns.

JPMorgan Ultra Risk Indicators

The analysis of JPMorgan Ultra'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 JPMorgan Ultra's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting jpmorgan 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 JPMorgan Ultra Short is a good investment, qualitative aspects like company management, corporate governance, and ethical practices play a significant role. A comparison with peer companies also provides context and helps to understand if JPMorgan Etf is undervalued or overvalued. This multi-faceted approach, blending both quantitative and qualitative analysis, forms a solid foundation for making an informed investment decision about Jpmorgan Ultra Short Municipal Etf. Highlighted below are key reports to facilitate an investment decision about Jpmorgan Ultra Short Municipal Etf:
Check out Historical Fundamental Analysis of JPMorgan Ultra to cross-verify your projections.
You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
The market value of JPMorgan Ultra Short is measured differently than its book value, which is the value of JPMorgan that is recorded on the company's balance sheet. Investors also form their own opinion of JPMorgan Ultra's value that differs from its market value or its book value, called intrinsic value, which is JPMorgan Ultra'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 JPMorgan Ultra's market value can be influenced by many factors that don't directly affect JPMorgan Ultra'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 JPMorgan Ultra's value and its price as these two are different measures arrived at by different means. Investors typically determine if JPMorgan Ultra is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, JPMorgan Ultra'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.