Fidelity Absolute Fund Forecast - Naive Prediction

FCAB Fund   25.16  0.01  0.04%   
The Naive Prediction forecasted value of Fidelity Absolute Income on the next trading day is expected to be 25.17 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.87. Investors can use prediction functions to forecast Fidelity Absolute's fund prices and determine the direction of Fidelity Absolute Income's future trends based on various well-known forecasting models. However, exclusively looking at the historical price movement is usually misleading. As of today the relative strength index (rsi) of Fidelity Absolute's share price is below 20 . This usually indicates that the fund is significantly oversold. The fundamental principle of the Relative Strength Index (RSI) is to quantify the velocity at which market participants are driving the price of a financial instrument upwards or downwards.

Momentum 0

 Sell Peaked

 
Oversold
 
Overbought
The successful prediction of Fidelity Absolute's future price could yield a significant profit. We analyze noise-free headlines and recent hype associated with Fidelity Absolute Income, which may create opportunities for some arbitrage if properly timed.
Using Fidelity Absolute hype-based prediction, you can estimate the value of Fidelity Absolute Income from the perspective of Fidelity Absolute response to recently generated media hype and the effects of current headlines on its competitors.
The Naive Prediction forecasted value of Fidelity Absolute Income on the next trading day is expected to be 25.17 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.87.

Fidelity Absolute after-hype prediction price

    
  CAD 25.16  
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 Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any fund could be closely tied with the direction of predictive economic indicators such as signals in employment.

Fidelity Absolute Additional Predictive Modules

Most predictive techniques to examine Fidelity price help traders to determine how to time the market. We provide a combination of tools to recognize potential entry and exit points for Fidelity using various technical indicators. When you analyze Fidelity 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.
A naive forecasting model for Fidelity Absolute is a special case of the moving average forecasting where the number of periods used for smoothing is one. Therefore, the forecast of Fidelity Absolute Income value for a given trading day is simply the observed value for the previous period. Due to the simplistic nature of the naive forecasting model, it can only be used to forecast up to one period.

Fidelity Absolute Naive Prediction Price Forecast For the 3rd of January

Given 90 days horizon, the Naive Prediction forecasted value of Fidelity Absolute Income on the next trading day is expected to be 25.17 with a mean absolute deviation of 0.03, mean absolute percentage error of 0, and the sum of the absolute errors of 1.87.
Please note that although there have been many attempts to predict Fidelity 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 Absolute's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Fidelity Absolute Fund Forecast Pattern

Fidelity Absolute Forecasted Value

In the context of forecasting Fidelity Absolute's 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 Absolute's downside and upside margins for the forecasting period are 25.03 and 25.30, respectively. We have considered Fidelity Absolute'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
25.16
25.17
Expected Value
25.30
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Naive Prediction forecasting method's relative quality and the estimations of the prediction error of Fidelity Absolute fund data series using in forecasting. Note that when a statistical model is used to represent Fidelity Absolute 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 Criteria111.7153
BiasArithmetic mean of the errors None
MADMean absolute deviation0.0307
MAPEMean absolute percentage error0.0012
SAESum of the absolute errors1.8697
This model is not at all useful as a medium-long range forecasting tool of Fidelity Absolute Income. This model is simplistic and is included partly for completeness and partly because of its simplicity. It is unlikely that you'll want to use this model directly to predict Fidelity Absolute. Instead, consider using either the moving average model or the more general weighted moving average model with a higher (i.e., greater than 1) number of periods, and possibly a different set of weights.

Predictive Modules for Fidelity Absolute

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 Absolute Income. Regardless of method or technology, however, to accurately forecast the fund market is more a matter of luck rather than a particular technique. Nevertheless, trying to predict the 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.

Other Forecasting Options for Fidelity Absolute

For every potential investor in Fidelity, whether a beginner or expert, Fidelity Absolute's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better. Fidelity 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 Absolute's price trends.

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

Fidelity Absolute Income Technical and Predictive Analytics

The 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 Absolute'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 Absolute's current price.

Fidelity Absolute Market Strength Events

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

Fidelity Absolute Risk Indicators

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

Pair Trading with Fidelity Absolute

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Fidelity Absolute position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Fidelity Absolute will appreciate offsetting losses from the drop in the long position's value.

Moving together with Fidelity Fund

  0.760P0000S9O5 PIMCO Monthly IncomePairCorr
  0.770P0000S9O7 PIMCO Monthly IncomePairCorr
  0.860P000072KJ RBC Canadian DividendPairCorr
The ability to find closely correlated positions to Fidelity Absolute could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Fidelity Absolute when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Fidelity Absolute - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Fidelity Absolute Income to buy it.
The correlation of Fidelity Absolute is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Fidelity Absolute moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Fidelity Absolute Income moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Fidelity Absolute can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching
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