Environment Mutual Fund Forecast - Polynomial Regression

FSLEX Fund  USD 47.27  0.46  0.96%   
The Polynomial Regression forecasted value of Environment And Alternative on the next trading day is expected to be 48.59 with a mean absolute deviation of 0.63 and the sum of the absolute errors of 38.30. Environment Mutual Fund Forecast is based on your current time horizon.
At this time, the relative strength index (RSI) of Environment's share price is approaching 48. This usually indicates that the mutual fund is in nutural position, most likellhy at or near its support level. The main point of RSI analysis is to track how fast people are buying or selling Environment, making its price go up or down.

Momentum 48

 Impartial

 
Oversold
 
Overbought
The successful prediction of Environment's future price could yield a significant profit. We analyze noise-free headlines and recent hype associated with Environment And Alternative, which may create opportunities for some arbitrage if properly timed.
Using Environment hype-based prediction, you can estimate the value of Environment And Alternative from the perspective of Environment response to recently generated media hype and the effects of current headlines on its competitors.
The Polynomial Regression forecasted value of Environment And Alternative on the next trading day is expected to be 48.59 with a mean absolute deviation of 0.63 and the sum of the absolute errors of 38.30.

Environment after-hype prediction price

    
  USD 47.27  
There is no one specific way to measure market sentiment using hype analysis or a similar predictive technique. This prediction method should be used in combination with more fundamental and traditional techniques such as fund price forecasting, technical analysis, analysts consensus, earnings estimates, and various momentum models.
  
Check out Historical Fundamental Analysis of Environment to cross-verify your projections.

Environment Additional Predictive Modules

Most predictive techniques to examine Environment price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Environment using various technical indicators. When you analyze Environment charts, please remember that the event formation may indicate an entry point for a short seller, and look at other indicators across different periods to confirm that a breakdown or reversion is likely to occur.
Environment polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Environment And Alternative as well as the accuracy indicators are determined from the period prices.

Environment Polynomial Regression Price Forecast For the 2nd of January

Given 90 days horizon, the Polynomial Regression forecasted value of Environment And Alternative on the next trading day is expected to be 48.59 with a mean absolute deviation of 0.63, mean absolute percentage error of 0.63, and the sum of the absolute errors of 38.30.
Please note that although there have been many attempts to predict Environment Mutual Fund 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 Environment's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Environment Mutual Fund Forecast Pattern

Backtest EnvironmentEnvironment Price PredictionBuy or Sell Advice 

Environment Forecasted Value

In the context of forecasting Environment's Mutual Fund 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. Environment's downside and upside margins for the forecasting period are 47.56 and 49.61, respectively. We have considered Environment'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
47.27
48.59
Expected Value
49.61
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 Environment mutual fund data series using in forecasting. Note that when a statistical model is used to represent Environment mutual fund, 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 Criteria117.6498
BiasArithmetic mean of the errors None
MADMean absolute deviation0.6279
MAPEMean absolute percentage error0.0133
SAESum of the absolute errors38.3037
A single variable polynomial regression model attempts to put a curve through the Environment 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 Environment

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Environment And Alte. Regardless of method or technology, however, to accurately forecast the mutual fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the mutual fund 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 Environment'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
46.2547.2748.29
Details
Intrinsic
Valuation
LowRealHigh
45.8846.9047.92
Details
Bollinger
Band Projection (param)
LowMiddleHigh
47.0247.8548.68
Details

Other Forecasting Options for Environment

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

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

Environment And Alte Technical and Predictive Analytics

The mutual fund market is financially volatile. Despite the volatility, there exist limitless possibilities of gaining profits and building passive income portfolios. With the complexity of Environment'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 Environment's current price.

Environment Market Strength Events

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

Environment Risk Indicators

The analysis of Environment'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 Environment's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting environment mutual fund 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.

Also Currently Popular

Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

Other Information on Investing in Environment Mutual Fund

Environment financial ratios help investors to determine whether Environment Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Environment with respect to the benefits of owning Environment security.
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