Fidelity Dividend Mutual Fund Forecast - Polynomial Regression
| FDGKX Fund | USD 38.65 0.06 0.15% |
The Polynomial Regression forecasted value of Fidelity Dividend Growth on the next trading day is expected to be 33.99 with a mean absolute deviation of 0.40 and the sum of the absolute errors of 24.63. Fidelity Mutual Fund Forecast is based on your current time horizon. Investors can use this forecasting interface to forecast Fidelity Dividend stock prices and determine the direction of Fidelity Dividend Growth's future trends based on various well-known forecasting models. We recommend always using this module together with an analysis of Fidelity Dividend's historical fundamentals, such as revenue growth or operating cash flow patterns.
Check out Historical Fundamental Analysis of Fidelity Dividend to cross-verify your projections. Fidelity |
Most investors in Fidelity Dividend cannot accurately predict what will happen the next trading day because, historically, fund markets tend to be unpredictable and even illogical. Modeling turbulent structures requires applying different statistical methods, techniques, and algorithms to find hidden data structures or patterns within the Fidelity Dividend's time series price data and predict how it will affect future prices. One of these methodologies is forecasting, which interprets Fidelity Dividend's price structures and extracts relationships that further increase the generated results' accuracy.
Fidelity Dividend polinomial regression implements a single variable polynomial regression model using the daily prices as the independent variable. The coefficients of the regression for Fidelity Dividend Growth as well as the accuracy indicators are determined from the period prices. Fidelity Dividend Polynomial Regression Price Forecast For the 24th of May
Given 90 days horizon, the Polynomial Regression forecasted value of Fidelity Dividend Growth on the next trading day is expected to be 39.85 with a mean absolute deviation of 0.35, mean absolute percentage error of 0.18, and the sum of the absolute errors of 21.52.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 Dividend's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Fidelity Dividend Mutual Fund Forecast Pattern
| Backtest Fidelity Dividend | Fidelity Dividend Price Prediction | Buy or Sell Advice |
Fidelity Dividend Forecasted Value
In the context of forecasting Fidelity Dividend'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. Fidelity Dividend's downside and upside margins for the forecasting period are 39.07 and 40.64, respectively. We have considered Fidelity Dividend'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.
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 Fidelity Dividend mutual fund data series using in forecasting. Note that when a statistical model is used to represent Fidelity Dividend 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.| AIC | Akaike Information Criteria | 116.3888 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.3528 |
| MAPE | Mean absolute percentage error | 0.0095 |
| SAE | Sum of the absolute errors | 21.5191 |
Predictive Modules for Fidelity Dividend
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 Dividend Growth. 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 Fidelity Dividend'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.
Other Forecasting Options for Fidelity Dividend
For every potential investor in Fidelity, whether a beginner or expert, Fidelity Dividend's 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 Dividend's price trends.Fidelity Dividend 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 Dividend mutual fund to make a market-neutral strategy. Peer analysis of Fidelity Dividend could also be used in its relative valuation, which is a method of valuing Fidelity Dividend by comparing valuation metrics with similar companies.
| Risk & Return | Correlation |
Fidelity Dividend Growth 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 Dividend'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 Fidelity Dividend's current price.| Cycle Indicators | ||
| Math Operators | ||
| Math Transform | ||
| Momentum Indicators | ||
| Overlap Studies | ||
| Pattern Recognition | ||
| Price Transform | ||
| Statistic Functions | ||
| Volatility Indicators | ||
| Volume Indicators |
Fidelity Dividend Market Strength Events
Market strength indicators help investors to evaluate how Fidelity Dividend 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 Dividend shares will generate the highest return on investment. By undertsting and applying Fidelity Dividend mutual fund market strength indicators, traders can identify Fidelity Dividend Growth entry and exit signals to maximize returns.
| Daily Balance Of Power | (9,223,372,036,855) | |||
| Rate Of Daily Change | 1.0 | |||
| Day Median Price | 38.65 | |||
| Day Typical Price | 38.65 | |||
| Price Action Indicator | (0.03) | |||
| Period Momentum Indicator | (0.06) | |||
| Relative Strength Index | 64.72 |
Fidelity Dividend Risk Indicators
The analysis of Fidelity Dividend'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 Fidelity Dividend's 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.
| Mean Deviation | 0.643 | |||
| Semi Deviation | 0.5093 | |||
| Standard Deviation | 0.7883 | |||
| Variance | 0.6214 | |||
| Downside Variance | 0.4736 | |||
| Semi Variance | 0.2594 | |||
| Expected Short fall | (0.77) |
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.| MSFT | Microsoft | |
| GM | General Motors | |
| CRM | Salesforce |
Check out Historical Fundamental Analysis of Fidelity Dividend to cross-verify your projections. You can also try the Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.