Ing Series Mutual Fund Forecast - Polynomial Regression

AISBX Fund   13.87  0.01  0.07%   
The Polynomial Regression forecasted value of Ing Series Fund on the next trading day is expected to be 13.83 with a mean absolute deviation of 0.19 and the sum of the absolute errors of 11.84. Ing Mutual Fund Forecast is based on your current time horizon.
  
Ing Series polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Ing Series Fund as well as the accuracy indicators are determined from the period prices.

Ing Series Polynomial Regression Price Forecast For the 21st of December

Given 90 days horizon, the Polynomial Regression forecasted value of Ing Series Fund on the next trading day is expected to be 13.83 with a mean absolute deviation of 0.19, mean absolute percentage error of 0.06, and the sum of the absolute errors of 11.84.
Please note that although there have been many attempts to predict Ing 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 Ing Series' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Ing Series Mutual Fund Forecast Pattern

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Ing Series Forecasted Value

In the context of forecasting Ing Series' 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. Ing Series' downside and upside margins for the forecasting period are 12.69 and 14.98, respectively. We have considered Ing Series' 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
13.87
13.83
Expected Value
14.98
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 Ing Series mutual fund data series using in forecasting. Note that when a statistical model is used to represent Ing Series 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 Criteria115.2584
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1941
MAPEMean absolute percentage error0.0135
SAESum of the absolute errors11.8424
A single variable polynomial regression model attempts to put a curve through the Ing Series 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 Ing Series

There are currently many different techniques concerning forecasting the market as a whole, as well as predicting future values of individual securities such as Ing Series Fund. 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.
Hype
Prediction
LowEstimatedHigh
12.7213.8715.02
Details
Intrinsic
Valuation
LowRealHigh
12.8714.0215.17
Details
Bollinger
Band Projection (param)
LowMiddleHigh
13.8814.6715.46
Details
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Ing Series. Your research has to be compared to or analyzed against Ing Series' peers to derive any actionable benefits. When done correctly, Ing Series' competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Ing Series Fund.

Other Forecasting Options for Ing Series

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

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

Ing Series Fund 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 Ing Series' 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 Ing Series' current price.

Ing Series Market Strength Events

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

Ing Series Risk Indicators

The analysis of Ing Series' 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 Ing Series' investment and either accepting that risk or mitigating it. Along with some essential techniques for forecasting ing 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 Ing Mutual Fund

Ing Series financial ratios help investors to determine whether Ing 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 Ing with respect to the benefits of owning Ing Series security.
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