Energy Fund Mutual Fund Forecast - 8 Period Moving Average

RYECX Fund  USD 212.13  3.19  1.48%   
The 8 Period Moving Average forecasted value of Energy Fund Class on the next trading day is expected to be 211.53 with a mean absolute deviation of 3.82 and the sum of the absolute errors of 202.20. Energy Mutual Fund Forecast is based on your current time horizon.
  
An 8-period moving average forecast model for Energy Fund is based on an artificially constructed time series of Energy Fund daily prices in which the value for a trading day is replaced by the mean of that value and the values for 8 of preceding and succeeding time periods. This model is best suited for price series data that changes over time.

Energy Fund 8 Period Moving Average Price Forecast For the 27th of November

Given 90 days horizon, the 8 Period Moving Average forecasted value of Energy Fund Class on the next trading day is expected to be 211.53 with a mean absolute deviation of 3.82, mean absolute percentage error of 20.75, and the sum of the absolute errors of 202.20.
Please note that although there have been many attempts to predict Energy 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 Energy Fund's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Energy Fund Mutual Fund Forecast Pattern

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Energy Fund Forecasted Value

In the context of forecasting Energy Fund'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. Energy Fund's downside and upside margins for the forecasting period are 210.30 and 212.77, respectively. We have considered Energy Fund'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
212.13
210.30
Downside
211.53
Expected Value
212.77
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 8 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of Energy Fund mutual fund data series using in forecasting. Note that when a statistical model is used to represent Energy Fund 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 Criteria106.4399
BiasArithmetic mean of the errors -1.7283
MADMean absolute deviation3.815
MAPEMean absolute percentage error0.0187
SAESum of the absolute errors202.195
The eieght-period moving average method has an advantage over other forecasting models in that it does smooth out peaks and valleys in a set of daily observations. Energy Fund Class 8-period moving average forecast can only be used reliably to predict one or two periods into the future.

Predictive Modules for Energy Fund

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Energy Fund Class. 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 Energy Fund'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
210.89212.13213.37
Details
Intrinsic
Valuation
LowRealHigh
200.28201.52233.34
Details
Bollinger
Band Projection (param)
LowMiddleHigh
204.08209.82215.56
Details

Other Forecasting Options for Energy Fund

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

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

Energy Fund Class 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 Energy Fund'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 Energy Fund's current price.

Energy Fund Market Strength Events

Market strength indicators help investors to evaluate how Energy Fund 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 Energy Fund shares will generate the highest return on investment. By undertsting and applying Energy Fund mutual fund market strength indicators, traders can identify Energy Fund Class entry and exit signals to maximize returns.

Energy Fund Risk Indicators

The analysis of Energy Fund'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 Energy Fund's investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting energy 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 Energy Mutual Fund

Energy Fund financial ratios help investors to determine whether Energy 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 Energy with respect to the benefits of owning Energy Fund security.
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