Fidelity Series Mutual Fund Forecast - Double Exponential Smoothing

FIOOX Fund  USD 16.52  0.14  0.85%   
The Double Exponential Smoothing forecasted value of Fidelity Series 1000 on the next trading day is expected to be 16.49 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.38. Fidelity Mutual Fund Forecast is based on your current time horizon.
  
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Fidelity Series works best with periods where there are trends or seasonality.

Fidelity Series Double Exponential Smoothing Price Forecast For the 26th of December

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Fidelity Series 1000 on the next trading day is expected to be 16.49 with a mean absolute deviation of 0.11, mean absolute percentage error of 0.02, and the sum of the absolute errors of 6.38.
Please note that although there have been many attempts to predict Fidelity 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 Fidelity Series' next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fidelity Series Mutual Fund Forecast Pattern

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Fidelity Series Forecasted Value

In the context of forecasting Fidelity 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. Fidelity Series' downside and upside margins for the forecasting period are 15.66 and 17.32, respectively. We have considered Fidelity 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
16.52
16.49
Expected Value
17.32
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Fidelity Series mutual fund data series using in forecasting. Note that when a statistical model is used to represent Fidelity 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 CriteriaHuge
BiasArithmetic mean of the errors -0.0045
MADMean absolute deviation0.1064
MAPEMean absolute percentage error0.0062
SAESum of the absolute errors6.3819
When Fidelity Series 1000 prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any Fidelity Series 1000 trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Fidelity Series observations are given relatively more weight in forecasting than the older observations.

Predictive Modules for Fidelity 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 Fidelity Series 1000. 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
15.6716.5017.33
Details
Intrinsic
Valuation
LowRealHigh
15.8316.6617.49
Details

Other Forecasting Options for Fidelity Series

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

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

Fidelity Series 1000 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 Fidelity 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 Fidelity Series' current price.

Fidelity Series Market Strength Events

Market strength indicators help investors to evaluate how Fidelity 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 Fidelity Series shares will generate the highest return on investment. By undertsting and applying Fidelity Series mutual fund market strength indicators, traders can identify Fidelity Series 1000 entry and exit signals to maximize returns.

Fidelity Series Risk Indicators

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

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